A method for managing a distributed battery arrangement, wherein the arrangement comprises a pool of battery assets. The arrangement allows capacity limits to be set for the battery assets. The capacity limits are a first capacity limit (C1) defining minimum charge that is to be maintained in the battery asset; and a second capacity limit (C2) defining maximum charge; wherein capacity falling between the first capacity limit (C1) and the second capacity limit (C2) is a usable capacity range (C3). Usage of the usable capacity range (C3) of the battery assets is controlled for balancing and/or optimization tasks.
A computer implemented method for managing a distributed battery arrangement, wherein the arrangement comprises a pool of battery assets (121-125), wherein the battery assets of the pool are individually owned. The method is performed by obtaining real time data relating to current state of the battery assets of the pool, wherein the current state of the battery assets of the pool comprises at least information about capacity and wear profile of the battery assets of the pool; and selecting one or more battery assets from the pool based on the obtained real time data to fulfil a capacity requirement for frequency balancing of electric grid (151).
A method and system for modifying a state of a device using detected anomalous behaviour in a self-exciting point process includes receiving time series data for a time period of the self-exciting point process, selecting a first portion, corresponding to a first time period, from the received time-series data, characterizing a normal behaviour for the first time period of the self-exciting point process, defining a baseline range for the self-exciting point process based, at least in part, on bounds of first point values in the selected first portion, processing a second portion based on the defined baseline range to detect one or more second point values exceeding the defined baseline range being characterized as the one or more anomalous events for at least the second time period of the self-exciting point process and modifying the state of the device based on the characterized one or more anomalous events.
H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
A computer implemented method for analyzing a target system for the purpose of controlling the target system. The method includes receiving (310) a matrix of observations, wherein rows of the matrix represent observations related to the target system and columns of the matrix represent values of different variables for each observation, or vice versa; performing (311) anomaly detection on the matrix of observations to obtain a matrix of anomaly coefficients; clustering (312) the matrix of anomaly coefficients to obtain clustered anomaly coefficients; determining (313) observations that substantially deviate from the core of any cluster in the clustered anomaly coefficients to be anomalous observations; and providing (314) results of the anomaly detection for detecting problems and taking corrective actions.
According to an example aspect of the present invention, there is provided a method comprising determining, by a first apparatus, sensitive information of a user and an identifier associated with said sensitive information, wherein the first apparatus is located in a first network domain of an organization, transmitting, by the first apparatus, the identifier associated with said sensitive information to a network domain of another organization, receiving by the first apparatus, from a second apparatus located in a second network domain of the organization, a request to get said sensitive information, the request comprising the identifier associated with said sensitive information and transmitting by the first apparatus, responsive to receiving the request, said sensitive information to the second apparatus, wherein the network domain of said another organization is classified by the first apparatus as less secure than the first and the second network domains of the organization.
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Software (computer-) [recorded]; computer programs (downloadable computer software); computer software; downloadable software for publishing and sharing digital media and information via global computer and communication networks; communication software for the electronic exchange of sound, data, video and graphics accessible via computer, mobile, wireless and telecommunication networks; computer software for use in developing computer programs; computer programs for data transmission; data recorded electronically; recording platforms [optical]; virtual reality models; plugin software; computer programmes for data processing; 3D animation software; 3D computer graphics software; CAD-CAM software; downloadable software applications for use with 3D printers; computer-aided manufacturing [CAM] software; computer application software for use in implementing the Internet of Things [IoT]; computer-aided design (CAD) software; computer software development tools; software for product development; virtual assistant software; smart manufacturing software; industrial software; product engineering software; Internet of Things [IoT] gateways; 3D editing software; collaboration software platforms [software]; computer software platforms; graphical user interface software; data and image processing software for making three dimensional models; downloadable computer software for designing and modelling of three dimensional printable products; data processing software for graphic representations; software for the planning, integration and optimization of 3D modelling; industrial automation software; downloadable software applications; software packages; software solutions for industry; software solutions for the medical field; software solutions for the pharmaceuticals industry; software solutions for the electronics industry; software solutions for the semiconductors industry; software for commerce over a global communications network; industrial process control software; software for industrial applications; software for monitoring, analysing, controlling and running industrial operations; electronic device software drivers that allow computer hardware and electronic devices to communicate with each other; computer hardware; computer networking hardware; data communications hardware; hardware solutions for the industry, namely, screens, computers, servers, modules; computer hardware for use in computer-assisted software engineering. (1) Telecommunication services; data transmission and reception services via telecommunications means; electronic exchange of audio, data, and graphics accessible via computer and telecommunication networks; telecommunications services, namely electronic transmission of data via global computer and communication networks; transmission of multimedia content among users; electronic transmission of data; providing a platform for 3D model delivery (data transfer); electronic transmission of documents; communication of data by means of telecommunications; transmission of data, messages and information; digital transmission of data; transmission of information by electronic communications networks; transmission of information for business purposes; information transmission services via digital networks; communication of information by electronic means; electronic transmission of messages, data and documents; electronic data interchange services; transmission of digital files; transferring information and data via computer networks and the Internet; transfer of information and data via online services and the Internet; electronic file transfer; providing access to information via the Internet; computer aided transmission of information and images; information, advisory and consultancy services relating to all the aforesaid services.
(2) Computer services, namely providing temporary use of a non-downloadable computer interface in order to create personalized online information services; providing temporary use of a non-downloadable computer interface for the development of data transmission networks; application provider services; providing temporary use of on-line non-downloadable software for the transmission and management of data; providing use of a non-downloadable computer interface in order to provide information concerning a wide range of text, electronic documents, databases, graphics and audio-visual information; providing a non-downloadable platform containing technology enabling the searching and using of directories, databases, text, images, 3d designs, electronic documents, graphic images and audio-visual data; providing a non-downloadable platform which updates and maintains digital information; providing temporary use of non-downloadable software to enable uploading and downloading or otherwise providing electronic media, images, text, photos, user-generated content, audio content, and information via the Internet or other computer and communication networks; providing temporary use of non-downloadable software to enable showing, editing, playing, viewing, previewing, displaying, tagging, sharing, manipulating, distributing, publishing, reproducing, or otherwise providing via the Internet or other computer and communication networks; design and development of electronic database software; development of systems for the transmission of data; development of systems for the processing of data; data migration services; providing information about the design and development of computer software, systems and networks; research and development services in the field of engineering; technical project planning; technological services and design relating thereto; design and development of engineering products; technological planning services; industrial development services; development of industrial machinery; development of industrial processes; design and development of industrial products; engineering consultancy relating to computer programming; engineering design; engineering design and consultancy; engineering and computer-aided engineering services; design of industrial machinery; computer aided design for manufacturing operations; computer-aided industrial design; computer aided part and mould design services; product development for others; product development; cross-platform conversion of digital content into other forms of digital content; design of models; design services relating to model making for display purposes; design and development of systems for data input, 3d printing, processing, display and storage; research relating to industrial machinery; industrial process research; consultancy services relating to computer networks using mixed software environments; software engineering; software development; custom design of software packages; providing temporary use of on-line non-downloadable software for importing and managing data; design, programming and development of software for importing and managing data; computer programming and software design; development of software solutions for industry; development of software solutions for the medical field; development of software solutions for the pharmaceuticals industry; development of software solutions for the electronics industry; development of software solutions for the semiconductors industry; industrial analysis and research services; industrial engineering design services; information, advisory and consultancy services relating to all the aforesaid services.
A computer implemented method for uplink power control in a mobile network. The method is performed by obtaining (301) signal to interference and noise ratio, SINR, of a first cell of the mobile network; comparing (302) the SINR to current uplink power parameter of the first cell; determining (303) a new value for the uplink power parameter based on the comparison so that, if the SINR is higher than the current uplink power parameter, the current uplink power parameter is increased to obtain the new value for the uplink power parameter, and if the SINR is lower than the current uplink power parameter, the current uplink power parameter is decreased to obtain the new value for the uplink power parameter; and providing (304) the determined new value of the uplink power parameter for use in uplink power control of the first cell.
H04W 52/14 - Separate analysis of uplink or downlink
H04W 52/24 - TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
H04W 52/36 - Transmission power control [TPC] using constraints in the total amount of available transmission power with a discrete range or set of values, e.g. step size, ramping or offsets
A computer-implemented method for automatically detecting a fraud call. A call request is received from a caller device to initiate a voice call with a called device at a local Public Land Mobile Network (PLMN). The call request is identified originating from a foreign Public Land Mobile Network (PLMN). In response to detecting that a caller ID of the caller device is associated to a local Public Land Mobile Network (PLMN), current location information is requested from a database of the local Public Land Mobile Network (PLMN). If the location information indicates the caller device is attached to the foreign Public Land Mobile Network (PLMN), determining the call request as authentic; and if the location information indicates the caller device is attached to the local Public Land Mobile Network (PLMN), determining the call request as fraud.
A computer implemented method for analyzing a target system for the purpose of controlling the target system. The method is performed by obtaining (301) a dataset comprising observations related to the target system; computing (302) alignment score for the dataset using a linear kernel to obtain a linear alignment score; computing (302) alignment score for the dataset using a non-linear kernel to obtain a non-linear alignment score; comparing (303) the linear alignment score and the non-linear alignment score; and if linear alignment score>non-linear alignment score, selecting (304) anomaly detection that uses Euclidean space measures, and else selecting anomaly detection that uses non-Euclidean space measures.
Disclosed herein is a computer-implemented method for detecting activity in an audio stream. In at least one embodiment, the method includes: obtaining an audio stream; and detecting activity in the audio stream based on detection criteria, where the detection criteria include at least two of: an audio amplitude threshold, where sections of the audio stream with an audio amplitude less than the audio amplitude threshold are classified as inactive; a detection delay defining a time interval of the audio stream during which activity in the audio stream is ignored; a minimum activity duration defining a minimum duration for an active section in the audio stream; and/or a maximum inactivity duration defining a maximum duration of inactivity in the audio stream.
Analysis of operation of a communications network. The analysis is performed by obtaining (301) time series of performance data of a cell of the communications network: selecting (302) a change point in the time series: determining (303) a first linear regression model before the selected change point and a second linear regression model after the selected change point; determining (304) offset difference between the first linear regression model and the second linear regression model; and determining (306) anomaly
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
H04L 41/142 - Network analysis or design using statistical or mathematical methods
H04L 41/147 - Network analysis or design for predicting network behaviour
H04L 41/149 - Network analysis or design for prediction of maintenance
12.
CENTRALLY MANAGED END USER CONTROLLED QUALITY OF SERVICE FOR 3GPP NETWORKS
Disclosed is a method comprising receiving, a request message (M1.2, M3.2A-B), from an User Equipment, UE (108, 210, 312A-B), operating in an operator's network (114, 216, 302A-B) via a User Plane Function, UPF (110, 218, 314A-B), by a Quality Assurance Server, QAS (104, 204,306, 602), residing in a network (106, 206, 308) which is separate from the operator's network (114, 216, 302A-B), reachable by the UE, to request a change in a Quality of Service, QoS, profile currently provided to the UE; identifying, a subscriber and the UE based on a Generic Public Subscriber Identifier, GPSI associated with the UE; creating a new QoS profile by comparing the request message and the currently provided QoS profile for the UE of the subscriber; and sending a response message (M1.4, M2.4, M3.4A-B) comprising the new QoS profile, by QAS to a Network Exposure Function, NEF (112, 214, 316A), to trigger requested change in operator's network.
According to an aspect, there is provided a computer- implemented method comprising the following. Initially, information on a plurality of anomaly events relating to operation of a target system is obtained. The information comprises one or more time series of anomaly score data. Segments satisfying one or more pre-defined criteria for anomalous operation are detected from the one or more time series. The one or more pre-defined criteria are defined to exclude fully non-anomalous anomaly score data. Anomaly durations and standardized anomaly scores are determined for the segments. Partition or density based clustering is performed in a two-dimensional space formed by the standardized anomaly scores and the anomaly durations to form n clusters, and m smallest clusters of the n clusters are identified. At least one of the following is performed: outputting information on the m smallest clusters or causing adjusting of operation of the target system based on the m smallest clusters.
Example embodiments relate to user driven optimization of a communication network. A computer-implemented method may comprise obtaining user level radio frequency data associated with a communication network; analysing the user level radio frequency data to identify a performance of at least one stationary user device in the communications network; and outputting, based on the analysis, optimization information to optimize the performance associated with the at least one stationary user device.
Example embodiments may relate to performance verification in a cellular communication network. A computer-implemented method may comprise: detecting a change in a configuration of a cellular communication network; determining a classification for a network object of the cellular communication network, wherein the classification is indicative of whether performance data obtained prior to the change is applicable for the network object; selecting a performance verification procedure for the network object based on the classification of the network object; and causing execution of the performance verification procedure for the network object.
A computer implemented method for defining neighbor relations in a communication network (110). The method comprises receiving (610) neighbor cell measurement data from a mobile user equipment, wherein said neighbor cell is of another radio access technology compared to the radio access technology of the current cell serving said mobile user equipment, comparing (620) the received measurement data with a threshold, and storing (630) a relational object connecting said serving cell and said neighbor cell based on said comparison.
According to an embodiment, a computer-implemented method for managing a plurality of assets of a virtual power plant, wherein each asset in the plurality of assets comprises at least one battery unit, comprises: assigning the plurality of assets into a plurality of groups, wherein the plurality of groups comprises at least a reserve group and at least one active group and each asset in the plurality of assets is assigned to one group in the plurality of groups; in response to receiving an activation signal for power grid frequency balancing, offering assets for the power grid frequency balancing from groups in the plurality of groups other than the reserve group; and in response to detecting a need for state of charge adjustment in the virtual power plant, performing the state of charge adjustment using the reserve group.
According to an example aspect of the present invention, there is provided a method for network optimization in a cellular communication network, the method comprising determining, by an apparatus, at least two first cells, wherein the at least two first cells are configured to use a first cell parameter value in the cellular communication network, determining, by the apparatus, a cause cell for each of the at least two first cells, wherein the cause cells are cells that are configured to use the first cell parameter value and each cause cell is within a predetermined number of hops from a respective first cell, sorting, by the apparatus, the cause cells into a list in the order of number of occurrences as a cause cell and configuring, by the apparatus, a first cell in the list to use a second cell parameter value.
According to an example aspect of the present invention, there is provided a method comprising determining a first cell and target cells of the first cell, wherein the target cells are neighbour cells of the first cell, determining a first list of neighbour relations, wherein the first list comprises priority indices of neighbour relations from the first cell to each of said target cells, determining a second list of neighbour relations, wherein the second list comprises priority indices of neighbour relations from each of said target cells to the first cell, determining a combined list of priorities of neighbour relations based at least on the first list and the second list, wherein the combined list comprises total priority indices of neighbour relations between each of said target cells and the first cell and configuring neighbour relations for the first cell based on the combined list.
According to an embodiment, a computer-implemented method for training at least one model for controlling as-set allocation in a distributed energy system comprises obtaining historical data about the distributed energy system; training a data simulator to generate future data for future distributed energy system conditions using the historical data; generating a plurality of new data for new distributed energy system conditions using the trained data simulator; and training at least one model for controlling asset allocation in the distributed energy system in the new distributed energy system conditions using the plurality of new data.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A method for optimizing fault detection in an Internet of Things (IoT) network includes determining a fault activity associated with an IoT device in IoT network; identifying a location information of IoT device; determining whether fault activity is associated with a mobile network corresponding to the location information; performing one of an automation activity of generating a service ticket for fault correction of mobile network, when fault activity is associated with mobile network, or generating a field service ticket for fault correction of the IoT device, when fault activity is not associated with mobile network. Disclosed also is a system for optimizing fault detection in an IoT network, system comprising a processor configured to perform the steps of the aforementioned method.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 41/0681 - Configuration of triggering conditions
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
H04L 41/5074 - Handling of user complaints or trouble tickets
22.
ACTIVATION OF NODES IN A DISTRIBUTED ENERGY STORAGE, DES, SYSTEM
A computer implemented method for activation of nodes in a distributed energy storage, DES, system, wherein the DES system comprises a plurality of nodes, each node comprising one or more battery units. The method comprises defining (310) a ruleset for the DES system, wherein the ruleset comprises for each node first rules for a more preferred combination of operating parameters and second rules for at least one less preferred combination of operating parameters; detecting (320) a required capacity; and responsively activating (330) nodes by using a combination of operating parameters derived based on the respective first rules until the required capacity is fulfilled or until all available nodes have been activated.
According to an embodiment, a computer-implemented method for managing a distributed energy storage system comprising a plurality of nodes coupled to a power grid, wherein each node comprises at least one energy storage, comprises: receiving an activation signal for power grid frequency balancing comprising a frequency balancing capacity requirement; selecting nodes out of the plurality of nodes to be activated and/or deactivated for the power grid frequency balancing according to the frequency balancing capacity requirement; activating and/or de-activating the selected nodes for the power grid frequency balancing; monitoring, during the power grid frequency balancing, whether a power quantity of the selected nodes deviates from the frequency balancing capacity requirement; and in response to the power quantity deviating from the frequency balancing capacity requirement, reselecting nodes out of the plurality of nodes to be activated and/or deactivated for the power grid frequency balancing according to the frequency balancing capacity requirement.
A method of improving fault tolerance of a network. The network includes a plurality of relay nodes, internet access node and plurality of customer nodes. The method includes identifying first set of relay nodes connecting one of customer nodes to internet access node, selecting a first relay node from first set of relay nodes, to be simulated as a first faulty node in the network, detecting, based on the simulation, number of customer nodes without at least one corresponding network path connecting to the internet access node due to the selection of the first relay node as the first faulty node, determining impact score of the first relay node based on the detected number of customer nodes without at least one corresponding network path connecting to the internet access node, and triggering one or more changes in topology of network according to the impact score to improve fault tolerance of network.
04 - Industrial oils and greases; lubricants; fuels
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
36 - Financial, insurance and real estate services
37 - Construction and mining; installation and repair services
38 - Telecommunications services
39 - Transport, packaging, storage and travel services
40 - Treatment of materials; recycling, air and water treatment,
42 - Scientific, technological and industrial services, research and design
Goods & Services
Electrical energy; electrical energy from renewable sources; electrical energy from solar or wind power; electricity. Computer databases and online databases, software platforms, software applications, computer software and hardware for energy and for the energy industry; computer software and hardware for power plants and virtual power plants; computer software for collecting, monitoring and analyzing energy production data of virtual power plants; computer hardware, computer software, displays and control units relating to energy generation, energy management, energy consumption, energy optimization and energy flexibility; cooperation software platforms for electricity transmission system operators and energy network operators; appliances, instruments, devices and systems to accumulate, store and supply electricity and electric power, for battery charging and energy storage solutions, to level electricity use with peak shaving and for grid stabilization with frequency containment reserves; computer software for transactions and mediation of electric power; software for setting and control of power system; apparatus and instruments for measuring, monitoring and analyzing energy and electricity consumption; energy control devices; distributed energy storage apparatus; distributed energy storage system for grid optimization and stabilization; distributed energy storage system for backup power batteries to control electricity supply in base stations; computer software for power grid data communication networks; software for monitoring, analyzing and controlling apparatus and installations for energy generation; application software for production of energy, distribution of power, storage of energy, energy use; apparatus and instruments for regulating, accumulating, conducting, switching, converting, transforming, controlling, distributing and storing electricity; computer software for monitoring, optimizing and regulating the storage, transmission and discharge of energy to and from electric battery systems; data communications apparatus for the energy industry; recorded content in relation to electricity industry; measuring, detecting and monitoring instruments, indicators and controllers for use in the electricity industry; batteries; sensors for measuring and controlling electric current, electric power, power consumption; electricity meters; electric power supply units; computer software and computer software platforms relating to the management of energy metering, the supply of energy and load balancing of energy and electricity; data processing programs, systems and apparatus for use in connection with the operation of virtual power plants; electric energy storage devices managed by a virtual power plant; energy monitoring and management system; battery management system; battery energy storage system; computer software for virtual power plants for energy and electricity generation; computer software for managing, controlling, monitoring and checking of virtual power plants; computer software and software applications for networking and/or cloud connection of decentralized energy systems and for the development of energy management systems for virtual power plants; battery and energy storage devices; computer hardware and software for monitoring and controlling the performance of batteries; computer software, application software and programs for use in monitoring and controlling decentralized distributed energy resources and distributed energy assets; computer software for the electronic commerce with energy; computer software programs for database management in virtual power plants; computer software for monitoring and detecting abnormalities of power plants and virtual power plants; databases, applications and computer systems for the management of energy storage, for monitoring and control supervision, for managing the assets of distribution networks; computer software to enable the provision of information via communications networks; software for monitoring, analyzing, controlling and running technical data relating to virtual power plants. Business management and administration in the energy sector; business management and administration of electricity transmission, supply and distribution apparatus, including business management and administration of electricity and energy demand response and load balancing services; business expertise in the field of energy production, energy distribution and energy storage; commercial management of projects for energy production, energy distribution, energy storage, energy optimization and energy flexibility; business management for the implementation and harnessing of the energy flexibility of virtual power plants; advertising, online advertising and promotional activities in the energy sector; compilation and systematization of information into databases in relation to virtual power plants; updating and maintenance of data in databases in relation to virtual power plants; computerized file management in relation to virtual power plants; commercial and business consultancy services relating to energy supply, generation, transmission, transportation, distribution, frequency regulation and grid stabilization; business consultancy and advisory services for energy grid balancing, optimization and management; business operation and management services in the fields of energy sales and marketing; promotion and marketing of power facilities and virtual power plants; business management and administration of virtual power plants; negotiation of contracts for the supply of electrical energy; sales promotion and marketing relating to energy production, energy distribution, energy storage and power plant equipment; business statistical information in the field of energy plant management; retail services and online retail services connected with the sale of computer software, computer hardware, computer systems, firmware, telecommunications networking hardware, internet technology applications, telecommunications networking apparatus, telecommunications networking instruments for computer network operations including accessories and parts and fittings therefor relating to virtual power plants; the bringing together, for the benefit of others, of a variety of electricity provider services, enabling customers to conveniently compare and purchase those services; electricity meter reading for billing purposes; procurement of contracts concerning energy supply; information, advisory and consultancy services relating to all the aforesaid services. Financing services; financing services relating to electric battery systems for the storage, discharge, supply, transmission and stabilization of electricity; monetary activities; real estate affairs; brokering service activities for power supply; financing services relating to virtual power plants; commodity trading including energy trading on the electricity market; the trading of electricity through a virtual power plant; real estate management; financial and monetary affairs in the fields of energy; market operation services for buying and selling of electricity; financial information and advice in the field of energy production, energy consumption, energy performance, energy optimization and energy flexibility; financial management assistance services in the energy field; energy brokerage services; information, advisory and consultancy services relating to all the aforesaid services. Maintenance and repair of energy generating installations and energy supply installations; repair of energy production plants and machines; installation, construction and repair of power plants; installation, repair and maintenance in relation to the equipment and installations for use in energy production, energy distribution, energy storage; installation, integration, maintenance and repair and upgrading of electric battery systems; maintaining electric battery systems for storage, discharge, supply, transmission and stabilization of electricity; installation, integration, maintenance and repair and upgrading of virtual power plant systems; construction, assembly, maintenance and servicing of electricity apparatus, installations and networks; installation of connections from energy generating and consumption installations to energy networks; machinery installation, maintenance and repair; repair of power lines; installation, maintenance and repair of electric apparatus and installations; construction or installation of energy supply infrastructure; repair and maintenance of power plant equipment; information, advisory and consultancy services relating to all the aforesaid services. Telecommunication services relating to energy sector, energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; providing telecommunication connections for virtual power plants; remote transmission of data for system control relating to virtual power plants; providing access to electronic communications networks relating to virtual power plants; electronic data transmission, namely, transmission of information by electronic means relating to virtual power plants; communication services for the electronic transmission of data relating to virtual power plants; communications via a global computer network or the internet relating to virtual power plants; providing access to online computer databases relating to virtual power plants; transfer of electronic information and data via computer networks and the Internet relating to virtual power plants; providing access to platforms and portals on the Internet relating to virtual power plants; Electronic, electric and digital transmission and distribution of measured data relating to energy via data networks; remote transmission of data relating to energy by means of telecommunications; provision of telecommunication operator services of virtual power plant and energy demand and supply management; information, advisory and consultancy services relating to all the aforesaid services. Transport, distribution, storage and supply of energy; transport, transmission, storage and supply of electricity; power supply services; distribution of electrical power; distribution of energy through a virtual power plant; energy storage, distribution and provision by way of virtual power plants; distribution and supply of energy including renewable energy by using batteries; energy network services, namely, distribution of energy; virtual power plant service, being electric power dispatching; operation of power distribution systems and networks for the provision of electricity; operation of virtual power plants for the distribution of electricity; management and control of electricity networks to distribute energy; management of energy and distribution networks to distribute energy; distribution of reserve power; operating and regulating electric battery systems for storage, discharge, supply, transmission and stabilization of electricity to distribute electricity; information, advisory and consultancy services relating to all the aforesaid services. Production of energy by power plants; production of energy by virtual power plants; generation of power; generation of energy; generation of electricity; processing and treatment of materials of all kinds for energy production; lease and rental of batteries; lease and rental of electricity generators; lease and rental of power inverters; operation of virtual power plants for the production of electricity; leasing services relating to electric battery systems for the storage, discharge, supply, transmission and stabilization of electricity; operating and regulating electric battery systems for storage, discharge, supply, transmission and stabilization of electricity to generate electricity; management and control of electricity networks to produce electricity; management of energy and distribution networks to produce electricity; information, advisory and consultancy services relating to all the aforesaid services. Design and development of energy distribution networks; design and development of software for control, regulation and monitoring of virtual energy systems; design and development of computer hardware and software for applications in the fields of energy production, energy management, energy distribution, energy storage, energy optimization and energy flexibility; design and development of infrastructure for virtual power plants; design and development of IT infrastructure, operating systems, database systems and web applications for virtual power plants; rental of IT infrastructure, operating systems, database systems and web applications for virtual power plants; scientific and technological services and research and design relating thereto in the field of energy production, energy distribution, energy storage, energy optimization and energy flexibility; designing alternative energy systems; monitoring and optimizing electric battery systems for storage, discharge, supply, transmission and stabilization of electricity; development of energy and power management systems; cloud services relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; design and development of energy supply networks; technical data analysis services relating to energy supply and distribution; platform as a service (PaaS) relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; providing online non-downloadable software for database management relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; hosting services, software as a service (SaaS) and rental of software relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; provision of Software as a Service (SaaS) or non-downloadable software for operating, maintaining, optimizing and regulating the distribution storage, discharge, supply, transmission and stabilization of energy including virtual power plants and electric battery systems; monitoring of power plants including virtual power plants, wirelessly connected electric battery systems with embedded firmware and software for storing and supplying electricity; technical planning, development and calculation services for combining decentralized power generation sources into a unit known as a virtual power plant; monitoring of network systems for control and operation, including ensuring the functionality and utilization of virtual power plants; design, development, implementation, update, maintenance, rental and adaptation of software and software packages for networking and/or cloud connection of decentralized energy systems and for the development of energy management systems for virtual power plants; software as a service for virtual power plant systems; providing temporary use of non-downloadable software for virtual power plant services; software as a service for use in monitoring and controlling distributed energy resources and distributed energy assets; engineering services in the energy sector and energy technology; consultancy in the field of energy-saving; software as a service for monitoring and analyzing virtual power plant management data; software as a service for remote controlling virtual power plant installations; software as a service for predicting the energy production; design and development of energy generation systems; testing, authentication and quality control of virtual power plants; cloud hosting provider services relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; development of communication systems relating to energy and power management; energy auditing services; energy optimization services; energy management services for the implementation and development of the energy flexibility; providing temporary use of online non-downloadable applications in order to manage energy; cloud storage services for electronic data relating to energy production, energy distribution, energy storage, energy optimization, energy flexibility and virtual power plants; energy usage monitoring services, namely recording and monitoring data; remote metering of energy; installation, maintenance and updating of computer software for virtual power plants; supervision of energy and distribution networks; information, advisory and consultancy services relating to all the aforesaid services.
26.
LAYERED CONTROL SYSTEM FOR MANAGEMENT OF A DISTRIBUTED ENERGY STORAGE, DES, SYSTEM
A layered control system for managing a distributed energy storage, DES, system, wherein the DES system comprises a plurality of nodes (121-125), each node comprising one or more battery units. The layered control system comprises a first control layer (301), a second control layer (302) and a third control layer (303). The first control layer (301) is configured to determine in advance an operating plan for the DES system for a plurality of time slots of a first time period based on aggregated properties of the DES system, wherein the operating plan comprises allocation of aggregated capacity of the DES system for the plurality of time slots; and to convey the operating plan to the second control layer. The second control layer (302) is configured to determine rules for selecting nodes of the DES system for obtaining the allocated aggregated capacity; to monitor operation of the DES system in real time and responsively adjust the rules; and to convey the rules to the third control layer. The third control layer (303) is configured to execute selection and activation of individual nodes of the DES system in accordance with the rules.
According to an embodiment, a computer-implemented method for managing voice call initiation comprises: performing at least one voice call according to a preconfigured script, wherein the preconfigured script comprises a plurality of steps; obtaining, during the at least one voice call, a time estimate for performing at least one step of the plurality of steps of the preconfigured script; computing, during the at least one voice call, a remaining time estimate for each voice call in the at least one voice call based on the time estimate for performing the at least one step of the plurality of steps of the preconfigured script; and determining whether to initiate a new voice call during the at least one voice call according to the remaining time estimate of each voice call in the at least one voice call.
Disclosed is a method (300) for managing a cellular network (100). The method comprises receiving information about a plurality of base stations (102) in cellular network and location coordinates of each base station; generating a triangulation diagram (104) representing base stations, with each one of base stations being considered as one of point sites in a plane corresponding to location coordinates; identifying for a target base station (102A), proximal base stations from plurality of base stations, based on cells (B1-B8, C1-C16) neighbouring a cell (A) corresponding to target base station up to a predefined nth level in triangulation diagram and configuring target base station based, at least in part, on known configuration of one or more of identified proximal base stations thereto.
Example embodiments may relate to mass outage detection in a communication network. A computer-implemented method may comprise: receiving a stream of alarm messages associated with cell sites of a communication network; detecting a mass outage associated with a group of the cell sites, in response to detecting, from the stream of alarm messages, a group of alarm messages originated at the group of the cell sites, wherein each of the group of the cell sites is located within a threshold distance from at least one of the group of the cell sites; and outputting an indication of the mass outage associated with the group of cell sites.
H04W 24/04 - Arrangements for maintaining operational condition
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
Example embodiments may relate to detection of overshooting cells in a radio network. A computer-implemented method may comprise: communicating data traffic via a first cell of a first access node of a communication network, wherein a sector of the first access node comprises the first cell and a second cell of the first access node; restricting amount of data traffic communicated via the first cell; and determining that a third cell of a second access node is overshooting, in response to determining, after restricting the amount of data traffic communicated via the first cell, that at least part of the data traffic is communicated via the third cell and not via the second cell.
Example embodiments relate to counteractions for remedying anomalies within a communication network. A computer-implemented method may comprise detecting an anomaly associated with at least a first cell; determining a counteraction for the first cell; identifying at least one second cell impacted by the counteraction; obtaining first performance indicator(s) the first cell and/or the at least one second cell, wherein the first performance indicator(s) are associated with a first time period before performance of the counteraction; causing performance of the counteraction at the first cell or providing an indication of the counteraction for performance of the counteraction at the first cell by a user; obtaining second performance indicator(s) associated with the first cell and/or the at least one second cell, wherein the second performance indicator(s) are associated with a second time period after performance of the counteraction; and verifying the counteraction based on first performance indicator(s) and the second performance indicator(s).
H04B 7/06 - Diversity systemsMulti-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
A computer implemented method for configuring a network device of a communications network operated by a network operator. The method comprises obtaining network device configuration data from a support system of the network operator, performing a configuration process to configure the network device in an event-based manner, and providing the support system with updated information of the communications network indicating a success of said configuration process.
A computer implemented method for controlling a communications network. It is checked whether amount of handover failures from a first cell to a second cell exceeds a first threshold. Responsive to identifying that the amount of handover failures from the first cell to the second cell exceeds (301) the first threshold, a new cell identifier code is set (306) for the second cell in the communication network.
Analyzing measurement results of a target system. Measurement results are obtained (401). The measurement results include multiple data entries, and each data entry includes multiple data values on a lowest hierarchy level and hierarchy information defining with which entities the entry is related to on different hierarchy levels. An aggregated anomaly score is determined (402) for each data entry. Data entries, wherein the aggregated anomaly score fulfils predefined criteria, are chosen for further analysis. Hierarchical clustering is performed (404) on the chosen entries based on dissimilarity of the chosen entries to combine at least some of the chosen entries together; and the hierarchically clustered entries are used (405) to identify one or more anomalous entities on hierarchy levels above the lowest hierarchy level.
Monitoring of a semiconductor manufacturing process. Wafer measurement data is obtained (301); Zernike polynomials are fitted (302) to the wafer measurement data to obtain representation of respective wafermap patterns; a knowledgebase of wafermap patterns is built (303) based on the respective coefficients of the Zernike polynomials; the wafermap patterns of the knowledgebase are grouped (304) to wafermap pattern groups based on the respective coefficients of the Zernike polynomials; and at least some of the wafermap pattern groups of the knowledgebase and the respective coefficients of the Zernike polynomials are used (305) for analyzing new wafer measurement data for the purpose of monitoring the semiconductor manufacturing process.
A computer implemented method for identifying a stationary user device of a communications network. This is performed by obtaining (301) usage data from the communications network; analysing (302) the usage data to check whether a user device fulfils the conditions of a stationary user device; responsive to finding that the user device fulfils said conditions of a stationary user device, concluding (303) that the user device is stationary; and outputting (304) information about the user device being stationary for the purpose of further analysis and/or management of the communications network. The conditions of a stationary user device require that the amount of data transmission to or from the user device exceeds a first threshold, and that the user device has been connected to a predefined maximum number or fewer base stations or cells.
A computer implemented method for recognizing an incorrectly operating beamforming antenna that serves a sector of a cell of a communication network. The method comprises obtaining samples comprising coordinates of locations within said sector linked with detected information identifying respective beams that served said locations, determining whether correct beams served correct locations, and providing output information indicating whether the target beamforming antenna is operating incorrectly based on said determination.
H04B 17/17 - Detection of non-compliance or faulty performance, e.g. response deviations
H01Q 3/26 - Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system varying the relative phase or relative amplitude of energisation between two or more active radiating elementsArrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an antenna or antenna system varying the distribution of energy across a radiating aperture
A computer implemented method for monitoring network performance relating to an application-level service used by a user. The method comprises obtaining first monitoring data measuring performance of a home network (11) of the user concerning the application-level service and/or type of a device used by the user, obtaining second monitoring data measuring performance of an operator network (20-40) concerning said application-level service and/or type of a device used by said user, linking the first monitoring data with the second monitoring data so as to obtain combined application-level and/or device type-level monitoring data concerning said particular service used by said particular user, and storing said combined application-level and/or device type-level monitoring data at a data lake (72).
According to an embodiment, a computer-implemented method (100) for performing a computational task using a machine learning model comprises obtaining (101) an indication about a computational task to be performed; obtaining (102) at least one minimum performance threshold for the computational task; obtaining (103) a plurality of machine learning models, wherein each machine learning model in the plurality of machine learning models is associated with at least one performance indicator and at least one resource consumption indicator; choosing (104) a machine learning model out of the plurality of machine learning models based at least on the at least one minimum performance threshold for the computational task, the at least one performance indicator of each machine learning model in the plurality of machine learning models and the at least one resource consumption indicator of each machine learning model in the plurality of machine learning models; and performing (105) the computational task using the chosen machine learning model.
According to an example aspect of the present invention, there is provided an apparatus comprising at least one processing core and at least one memory storing instructions that, when executed by the at least one processing core, cause the apparatus at least to store plural definitions of geographic areas, each one of the geographic areas enclosing all core network nodes of a single network domain area, determine, for each of the geographic areas, a number of alerting nodes therein, and trigger reverting, or trigger prompting of a user whether to revert, of at least a subset of core network nodes of a first network domain area to prior configurations based on determining that a number of alerting nodes in a geographic area enclosing the core network nodes of the first network domain area exceeds a threshold number.
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
H04L 41/0859 - Retrieval of network configurationTracking network configuration history by keeping history of different configuration generations or by rolling back to previous configuration versions
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
41.
METHOD AND SYSTEM FOR ELECTRICAL COMPONENT MATCHING
Disclosed is a method for electrical component matching. The method comprises receiving an input indicative of a given electrical component for which at least one matching electrical component is required to be identified; inferring specifications of the given electrical component using the input; determining a first set of electrical components from amongst the plurality of electrical components using rule-based cases applied corresponding to the specifications; determining a second set of electrical components from amongst the plurality of electrical components using machine learning; generating raw output data comprising product data of the electrical components of the first set and the second set; and processing the raw output data for generating processed output data.
According to an embodiment, a computer-implemented method for processing number words based on a word buffer comprises: obtaining a word buffer; filling a number word buffer based on the word buffer by repeatedly performing: obtaining a current word from the word buffer, determining whether the current word is a number word, in response to the current word being a number word, determining whether to combine the current word with a subsequent word in the word buffer based at least on a category of the current word and a category of the subsequent word, in response to determining that the current word should be combined with the subsequent word, combining the current word with the subsequent word thus producing a combined word, and adding the combined word to the number word buffer.
According to an embodiment, a computer-implemented method for obtaining a first search item and a second search item from text data, the method compris- ing: obtaining text data comprising a plurality of sections; searching for a first anchor section in the plurality of sections; dividing the text data into a first part and a second part based on a location of the first anchor section in the plurality of sections; searching for the second anchor section in the first part, and obtaining the first search item based at least on at least one location of the second anchor section in the first part; and searching for the second anchor section in the second part, and obtaining the second search item based at least on at least one location of the second anchor section in the second part.
Example embodiments may relate to detection of overshooting cells in a radio network. A computer-implemented method may comprise: communicating data traffic via a first cell of a first access node of a communication network, wherein a sector of the first access node comprises the first cell and a second cell of the first access node; restricting amount of data traffic communicated via the first cell; and determining that a third cell of a second access node is overshooting, in response to determining, after restricting the amount of data traffic communicated via the first cell, that at least part of the data traffic is communicated via the third cell and not via the second cell.
A computer implemented method for autoconfiguration of a first base station of a communications network. The method comprises: obtaining (320), from the network, base station configuration data, wherein the base station configuration data comprises parameter values from plurality of active base stations and/or cells of the communications network; obtaining (330) network planning data; predicting (340) autoconfiguration parameters for the first base station based on the obtained base station configuration data and the obtained network planning data; and configuring (360) the first base station using the predicted autoconfiguration parameters.
A computer implemented method for controlling a target system. The method is implemented by obtaining a first matrix (310) comprising a plurality of monitored variables as columns and a plurality of observations of the monitored variables measured from the target system as rows, wherein each row is associated with one or more dimensions; partitioning (402) the first matrix into a plurality of submatrices (412-416), each submatrix comprising a subset of rows of the first matrix; separately processing the submatrices by standardizing (403) values of the submatrix (412- 416) to obtain standardized submatrix (422-426); and processing (404) the standardized submatrix (422-426) by performing anomaly detection on the values of the standardized submatrix and by aggregating results of the anomaly detection by the respective one or more dimensions to a result matrix (430); and outputting the result matrix (430) or information derived from the result matrix (430) for the purpose of controlling the target system.
Optimization of a mobile network, performed by adjusting a proactive scheduling functionality in a target cell of the mobile network based on load in the target cell, wherein the proactive scheduling functionality is configured by a proactive scheduling parameter that defines a period of time over which an uplink connection is kept alive after sending the last bit of uplink data; responsive to the load in the target cell exceeding a first threshold, disabling the proactive scheduling functionality; responsive to the load in the target cell being below a second threshold, configuring the proactive scheduling parameter to a default value or gradually increasing the proactive scheduling parameter value; and responsive to the load in the target cell being between the first threshold and the second threshold, keeping the current proactive scheduling parameter value.
Disclosed is a method for managing a cellular network that includes receiving information about a plurality of coverage cells in the cellular network and location coordinates of each coverage cell; generating a triangulation diagram corresponding to the location coordinates of each coverage cell; identifying for a target mapped cell, corresponding to a target coverage cell, neighbouring mapped cells having a shared boundary in the triangulation diagram; determining a length of the shared boundary between the target mapped cell and each one of the neighbouring mapped cells; assigning a ranking to each one of the neighbouring mapped cells based on the corresponding length of the shared boundary with the target mapped cell; and generating a selected neighbour list for the target coverage cell based on the ranking of the corresponding neighbouring mapped cells.
A computer implemented method for controlling call capacity in a mobile network. The method includes: activating a mass event mode in a first cell of a first base station, wherein the first cell is a high frequency band cell, and wherein operating in the mass event mode comprises: checking if any low frequency band cells are available in a first sector served by the first cell; and responsive to detecting that one or more low frequency band cells are available, switching, at least some, voice call connections of the users of the first cell to at least some of the available low frequency band cells.
Example embodiments may relate to training of a supervised machine learning model for anomaly detection in a communication network. A computer-implemented method may comprise: detecting, by an unsupervised machine learning model, a plurality of anomalies in performance indicator data of a communication network; receiving labels for a first subset of the plurality of anomalies and labelling the first subset of the plurality of anomalies with the labels; training, based on the labelled first subset of the plurality of anomalies, a semi-supervised machine learning model for labelling anomalies; labelling, by the semi-supervised machine learning model, a second subset of the plurality of anomalies; and training, based on the labelled first and second subsets of the plurality of anomalies, a supervised machine learning model for detecting and/or classifying anomalies in the performance indicator data.
H04L 41/142 - Network analysis or design using statistical or mathematical methods
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
51.
CALL SECURITY USING A MUTUALLY AGREED ACOUSTIC FINGERPRINT
According to an embodiment, a method for call security, the method comprises: agreeing, by a first party and a second party, about an acoustic fingerprint between the first party and the second party; performing a voice call, by the first party, calling the second party; applying, by the first party, the acoustic fingerprint to the voice call; and detecting, by the second party, the acoustic fingerprint in the voice call.
A computer implemented method for analyzing operation of cells of a communications network is provided. The method includes: obtaining data comprising performance indicators data from a first cell and a group of reference cells for a selected time period; —identifying, for the first cell, first change point of a first performance indicator, calculating magnitude of the change of the first performance indicators at the first change point, and defining the calculated magnitude as a first magnitude; identifying, for the group of reference cells, a group of reference change points of the first performance indicator, calculating magnitudes of the changes of the group of reference change points, and defining the calculated magnitudes as a group of reference magnitudes; comparing the first magnitude to the group of reference magnitudes to determine the relevance of the change point of the first cell; and providing output indicating the first change point of the first cell in response to detecting that said change point is determined relevant, or otherwise, providing output indicating that no relevant change points are identified.
A computer implemented method for analysing antenna directions in a communications network. The method includes at least obtaining network related data; calculating a characteristic user direction of a first cell of a first base station; calculating a difference between the characteristic user direction and the antenna azimuth direction of the first cell; and responsive to detecting that the calculated difference is greater than a pre-set threshold angle, indicating an anomaly in the first cell.
According to an embodiment, a computer-implemented method for detecting activity in an audio stream comprises: obtaining an audio stream; and detecting activity in the audio stream based on detection criteria, wherein the detection criteria comprise at least two of: an audio amplitude threshold, wherein sections of the audio stream with an audio amplitude less than the audio amplitude threshold are classified as inactive; a detection delay defining a time interval of the audio stream during which activity in the audio stream is ignored; a minimum activity duration defining a minimum duration for an active section in the audio stream; and/or a maximum inactivity duration defining a maximum duration of inactivity in the audio stream.
Managing a distributed energy storage, DES, arrangement to participate in electric grid balancing, wherein the DES arrangement comprises a pool of nodes. The method is performed by detecting (301) a balancing need for balancing the electric grid either in up direction or down direction; selecting (302) nodes for the balancing need; identifying (303) preferred balancing activity for a plurality of the selected nodes, wherein the preferred balancing activity is node specific, wherein first nodes, if any, have a preferred balancing activity in the same direction with the detected balancing need, and second nodes, if any, have a preferred balancing activity that is opposite to the detected balancing need; starting activation (304) of a balancing activity according to the balancing need for the first nodes, if any, upon detecting the balancing need; and delaying activation (305) of the balancing activity according to the balancing need for the second nodes, if any.
Disclosed is a method for securely managing a private wallet. The method comprises generating and storing a public key and a private key associated with a digital asset in the private wallet in a dedicated memory hardware of a primary user device, wherein the public key and the private key provide access to the digital asset; extracting a biometric input associated with a user and generating a biometric signature from the extracted biometric input; and linking the generated biometric signature to the private key for adding a security layer to access the private key.
G06Q 20/36 - Payment architectures, schemes or protocols characterised by the use of specific devices using electronic wallets or electronic money safes
G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
Disclosed is a method for recording operational condition of devices. The method comprises providing a set of rules for one or more operating conditions for the devices in a network, wherein each of the one or more operating conditions include acceptable ranges related to at least one of a usage data and an ambient data of the devices; assigning an operating condition, to a device, from the one or more operating conditions; receiving usage data and ambient data of the device; comparing the received usage data and the ambient data of the device with the provided usage data and ambient data based on the assigned operating condition; and verifying if the assigned operating condition is followed by the device or not based on the comparison of the usage data and the ambient data of the device. Disclosed also is a system (200) for recording operational condition of devices.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
G01R 31/36 - Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
Analyzing measurement results of a target system. The analysis is performed by receiving a first matrix including first measurement results of the target system; training a matrix decomposition model with the first matrix to obtain a third matrix of normal or stable measurement results and a fourth matrix of anomalous or unstable measurement results; receiving a second matrix including second measurement results of the target system, wherein the second measurement results are later measurement results compared to the first measurement results; selecting from the third matrix a subset that matches with the second matrix; subtracting the selected subset from the second matrix to obtain a fifth matrix; outputting the fifth matrix or information derived from the fifth matrix for the purpose of evaluating performance of the target system.
A computer implemented method for managing a distributed energy storage, DES, arrangement, wherein the DES arrangement comprises a pool of nodes. The method is performed by monitoring (301) energy levels of battery systems of the nodes of the DES arrangement; identifying (302), based on monitoring the energy levels, one or more target nodes for optimization; and enabling (303) node specific up or down regulation actions for the target nodes irrespective of grid balancing actions of the whole DES arrangement.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
H02J 3/24 - Arrangements for preventing or reducing oscillations of power in networks
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
H02J 3/48 - Controlling the sharing of the in-phase component
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the networkCircuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
60.
A COMPUTER IMPLEMENTED METHOD FOR ANALYZING OPERATION OF A CELL OF A COMMUNICATIONS NETWORK
A computer implemented method for analyzing operation of a cell of a communications network includes collecting data with measurement samples of signal level performance indicators from multiple cells of the communications network; calculating a characteristic value for a signal level performance indicator for a first cell type based on the collected data, wherein a part of the best measurement samples of the signal level performance indicator of the first cell type are taken into account in the calculation of the characteristic value; calculating a difference between the calculated characteristic value and a measurement sample of signal level performance indicator of a first cell of the first cell type; and providing output information indicating that an antenna system of the first cell is operating incorrectly in response to detecting that the calculated difference is greater than a preset threshold.
A computer implemented method for controlling a communications network. The method includes obtaining, from the network, cell identifiers, remote electrical tilt, RET, equipment identifiers, link data comprising information about links between cells and RET equipment, and network configuration data, and, from a data storage, network planning data; finding a first cell, if any, missing a link to a RET equipment; searching based on comparing the network configuration data and the network planning data to which RET equipment, if any, the first cell should be linked, and responsive to detecting that the first cell and a first RET equipment should be linked, forming a link between the first cell and the first RET equipment; updating the link data with information comprising the formed link, if any; and using the updated link data in network control operations.
Disclosed is a method for performing predictive maintenance in a communication network, such as a decentralized communication network (200). The method comprises forming a training dataset using communication and anomaly data of communication nodes in communication network; building predictive maintenance client models and a predictive maintenance server model through machine learning using training dataset; deploying predictive maintenance client models and predictive maintenance server model in plurality of client nodes (202, 204, 206, 208, 210, 212, and 214) and server node (216), respectively; sensing an anomaly by a client node of plurality of client nodes; sending an aggregated information, by client node to server node; and performing a maintenance action by server node based on a decision made by server node on aggregated information. Disclosed also is a system for performing predictive maintenance in a communication network.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
A computer implemented method for optimizing directions of antennas of a base station of a communications network is provided. The method includes receiving antenna sector configuration data with sector information of each antenna and an azimuth angle of a main antenna direction of each antenna; receiving performance indicators of multiple subsectors of each antenna sector; calculating a cost function value indicating inter-sector impact between neighboring subsectors of adjacent sectors based on the performance indicators for the current antenna configuration and for at least one other possible antenna configuration; and identifying an antenna configuration yielding minimum cost function value of the calculated values as an optimized antenna configuration.
A computer implemented method for managing a distributed energy storage, DES, arrangement, wherein the DES arrangement comprises a pool of nodes (121-125). The method is performed by detecting a balancing need for frequency balancing of electric grid; selecting a plurality of nodes of the DES arrangement for fulfilling a capacity requirement associated with the balancing need; sending activation requests to the selected nodes, wherein sending of the activation requests is performed in parallel; detecting an activation confirmation situation or an error situation for the selected nodes; aggregating capacity of the nodes for which an activation confirmation situation is detected; and reserving the aggregated capacity for the balancing need.
Example embodiments may relate to detection of overshooting cells in a radio network. A computer- implemented method may comprise: estimating a dominance area of a cell of a communication network; identifying a plurality of devices transferring data via the cell, wherein the plurality of devices are substantially stationary outside the dominance area of the cell and primarily use at least one other cell of the communication network for data transfer; and determining that the cell is overshooting based on at least one of: a number of the plurality of devices, distances of the plurality of devices to an access node of the cell, or a number of intervening cells overlapping in frequency with the cell and being located between the access node of the cell and the plurality of devices.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
38 - Telecommunications services
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Application development software; application server
software; computer application software for wireless
devices, mobile phones, mobile devices, computers and
tablets; application software for cloud computing services;
application software for social networking services via
internet; collaboration management software platforms;
communication software; communication software for
connecting global computer networks; communication software
for connecting computer network users; computer application
software for streaming audio-visual media content via the
internet; computer programmes for use in telecommunications;
computer software to enable the provision of information via
communications networks; data communications software;
subscription management software for wireless devices,
mobile phones, mobile devices, computers and tablets; mail
software and mail server software for wireless devices,
mobile phones, mobile devices, computers and tablets;
entertainment software; software for online messaging;
supply chain management software; telecommunications
software; communications apparatus; software for planning,
integrating and optimizing data networks and workflows;
software for management of sales, customer service,
distribution, inventory, purchasing, order processing,
manufacturing, time and production; software for workflow
management; software providing business intelligence and
business predictive analytics; software for data analytics,
forecasting and reporting; computer software that includes
artificial intelligence for business data processing;
software for processing and managing information flows;
downloadable computer software and mobile applications for
use in database management, anomaly detection, business
process optimization, business management and artificial
intelligence; downloadable computer software and mobile
applications which are enhanced by data science approaches,
namely, artificial intelligence, machine learning, and data
mining, for use in computer networks, supply chains and
process analysis, optimization, anomaly detection, churn
prediction and predictive services; data recorded
electronically; computer programmes, systems and devices for
data processing; computer software development tools;
product engineering software; computer software platforms;
software for monitoring, analysing, controlling and running
technical data; data communications hardware; computer
software for use in monitoring and remote monitoring of
computer systems and electronic devices; downloadable
software for remotely accessing and controlling a computer;
computer programs for connecting remotely to computers or
computer networks; software for remote diagnostics; computer
software and systems to enable teleconferencing,
videoconferencing and videophone services; computer software
to maintain and operate computer systems; interactive
computer systems; recording platforms [optical];
optimisation software; computer programs for network
management; computer application software for use in
implementing the Internet of Things [IoT]; software for
product development; smart manufacturing software; software
for monitoring, analysing, controlling and running
industrial operations; computer and computer networking
hardware; databases; computer software for database
management; analytics software; machine learning software
for monitoring and analysis; artificial intelligence
software; cloud computing software; cloud network monitoring
software; software for the integration of artificial
intelligence and machine learning in the field of Big Data;
computer hardware modules for use in electronic devices
using the Internet of Things [IoT]; downloadable computer
programs using artificial intelligence and machine learning
for data analysis; downloadable computer programs using
artificial intelligence and machine learning for developing
predictive models and analysis; electronic control systems;
computer software to automate data warehousing; virtual
reality models; 3D animation software; 3D computer graphics
software; CAD-CAM software; downloadable software
applications for use with 3D printers; computer-aided
manufacturing [CAM] software; computer-aided design (CAD)
software; virtual assistant software; industrial software;
Internet of Things [IoT] gateways; 3D editing software;
graphical user interface software; data and image processing
software for making three dimensional models; software for
the planning, integration and optimization of 3D modelling;
industrial automation software; software applications and
programs for industry; software applications and programs
for the medical field; software applications and programs
for the pharmaceuticals industry; software applications and
programs for the electronics industry; software applications
and programs for the semiconductors industry; software for
industrial applications; computer hardware and computer
networking hardware; hardware solutions for the industry,
namely, screens, computers, servers, modules; home
automation systems; media players; computer software,
namely, knowledge-based artificial intelligence platforms,
data analytics platforms and automation platforms that
leverage open source technology and optimize information
technology processes, monitor the entire information
technology infrastructure of an enterprise to detect
real-time anomalies and develop a fault diagnosis, analyze
information technology operations data and processes to
optimize and automate information technology service
management; Software for monitoring, analysing and managing
network and data using artificial intelligence and machine
learning; software for telecommunications and communications
on local or global communication networks; conference
systems comprised of telecommunications and computer
hardware and software for reservation-based or on-demand
conference sessions comprising audio, video and web-based
content and communications; digital signage, digital signage
display panels and digital signage monitors; virtual
communications and collaboration systems comprised of
telecommunications and computer hardware and software for
reservation-based or on-demand collaboration sessions
comprising audio, video and web-based content and
communications; SIM cards for mobile devices; digibox;
modems; modem cables; USB modems; mobile devices, mobile
phones, smart phones, wireless phones, laptops, tablets,
cameras, speakers, USB flash drives, headphones, smart
watches and peripherals therefor; television apparatus and
peripherals therefor; computer hardware and peripheral
devices; CDs and DVDs; digital video recorder; DVD and high
definition video disc players; home theater systems
comprised of audio and video receivers; broadband and mobile
broadband subscription software and devices; computer gaming
software; computer application software featuring games and
gaming; computer programmes for interactive television and
for interactive games and/or quizzes; computer software for
the administration of on-line games and gaming; audio books,
electronic books, audio recordings and podcasts; audio book
and electronic books (downloadable); electronic
publications, downloadable; computer software for the
collection, editing, organizing, modifying, book marking,
transmission, storage and sharing of data and information;
software in the field of text, image and sound transmission
and display; software for streaming audiovisual and
multimedia content via the internet and global
communications networks; software for streaming audiovisual
and multimedia content to mobile digital electronic devices;
software for searching, organizing, and recommending
multimedia content; downloadable motion pictures and
television shows provided via a video-on-demand service;
downloadable graphics featuring sets of digital images and
icons for use on computers, tablets, and mobile phones;
downloadable motion pictures and television shows; audio and
visual recordings; apparatus for recording, transmission or
reproduction of sound or images; encoded electronic chip
cards; digital media streaming devices; computer systems for
automated management of networks. Retail services in relation to computer software; providing
consumer product information and advice relating to
software; retail services and online retail services
connected with the sale of computer software, computer
hardware, computer systems, firmware, telecommunications
networking hardware, internet technology applications,
telecommunications networking apparatus, telecommunications
networking instruments for computer network operations
including accessories and parts and fittings therefor;
retail services and online retail services connected with
the sale of cloud technology hardware and software, virtual
technology hardware and software, communications apparatus
and telecommunications equipment including accessories and
parts and fittings therefor; arranging subscriptions of the
online publications of others; arranging subscriptions to
media packages, telephone services and internet services;
arranging subscriptions to telecommunication services for
others; subscriptions (arranging -) to telecommunication
services for others; retail of third-party pre-paid cards
for the purchase of telecommunication services,
entertainment services and multimedia content; retail
services in relation to domestic electronic and electric
equipment and smart devices; retail services in relation to
smartphones, computer hardware, tablets, wearable computers,
smart watches, mobile phones, cameras, games, game
controllers, headsets, memory cards, chargers, backup power
supply, virtual glasses, sim cards, loudspeakers, digiboxes,
modems, cables, and other audiovisual equipment and
peripherals therefor; retail services in relation to
broadband subscription software and devices and phone and
mobile broadband subscription software and devices;
compilation and systemization of information into computer
databases; compilation and systemization of information used
in electronic transmissions; computerized file management;
business management consulting services in the field of
information technology; automated and computerized data
processing;; business management services provided through
computer software; business management services provided
online from a global computer network or the internet;
marketing services provided by means of digital networks;
providing consumer product advice relating to wireless
devices, mobile phones, mobile devices, computers and
tablets and peripherals therefor; web site traffic
optimization; providing business information via global
computer networks; compilation and analysis of information
related to business, corporate administration and marketing;
business process management; data management services;
online data processing services; provision of computerised
data relating to business; business consultation services,
namely, business process improvement; business consulting
services in the field of knowledge-based artificial
intelligence platforms, data analytics platforms, and
automation platforms; business consulting services in the
field of knowledge management and business process
optimization; customer impact analysis; supply chain
advisory and consultancy services in relation to: commercial
industrial applications, infrastructure evaluation, process
management, process improvement, supply chain management and
forecasting, supply chain analysis, cost reduction, demand
and supply management and forecasting, customer relationship
management and data management; product marketing;
promotional marketing; internet marketing; retail services
and on-line retail services in relation to printed matter;
retail services in relation to audio books, electronic
books, magazines and audio recordings; arranging
subscriptions to services and arranging subscriptions to
electronic books and magazines, audio books, audio
recordings and podcasts; arranging subscriptions to online
publications for others namely arranging subscriptions to
digital services for the streaming of audio books and
electronic books and magazines on mobile phones, tablets and
computers; advertising, marketing and promotion services
relating to esports events; information, advisory and
consultancy services relating to all the aforesaid services. Providing user access to computer programmes in data
networks; transmission of interactive entertainment
software; advisory services relating to telecommunications;
arranging [provision] of electronic conferencing services;
broadcasting of audiovisual and multimedia content via the
internet; broadcasting of television programs using
video-on-demand and pay-per-view television services;
broadcasting programs via a global computer network;
communication by electronic means; communication services
for the electronic transmission of images; communication
services for the electronic transmission of data; computer
aided transmission of messages, information and images;
communications via a global computer network or the
internet; data streaming; data transmission and reception
services via telecommunication means; delivery of digital
audio and/or video by telecommunications; digital network
telecommunications services; electronic communications
services; interactive telecommunications services; internet
provider services; on-line communication services; operation
of a telecommunications network; operation of
telecommunications systems; providing access to a global
computer network for the transfer and dissemination of
information; providing access to online computer databases;
providing access to multimedia content online; providing
access to telecommunication networks; providing facilities
and equipment for video conferencing; providing
telecommunications connections to a global communication
network or databases; providing video conferencing services;
provision of telecommunication access to films and
television programs provided via a video-on-demand service;
provision of telecommunication access to video and audio
content provided via an online video-on-demand service;
remote transmission of data by means of telecommunications;
streaming audio and video material on the internet;
streaming of audio, visual and audiovisual material via a
global computer network; video, audio and television
streaming services; audiovisual communication services;
automated operator services of the telecommunications
network; telecommunication services provided via internet
platforms and portals; electronic transmission of documents;
communication of data by means of telecommunications;
transmission of data, messages and information; digital
transmission of data; transmission of information by
electronic communications networks; communication of
information by electronic means; transmission of electronic
messages, information and documents; electronic data
interchange services; transfer of electronic information and
data via computer networks and the internet; transfer of
information and data via online services and the internet;
electronic file transfer; providing access to information
via the internet; computer aided transmission of information
and images; providing users with secure remote access via
the internet to private computer networks; provision of
access to data or documents stored electronically in central
files for remote consultation; providing teleconferencing
and videoconferencing services; communication services for
video conferencing purposes; data transmission services
between networked computer systems; providing access to
platforms and portals on the internet; audio, video and
multimedia broadcasting via the internet and other
communications networks; communication services over
computer networks; data transmission services over
telecommunications networks; providing multiple use access
to global computer information networks for the transfer and
dissemination of a wide range of information; providing
wireless telecommunications via electronic communications
networks; providing access to data in computer networks;
providing access to a platform for 3d model delivery and
data transfer; information transmission services via digital
networks; providing videoconferencing facilities; mobile
telecommunication network services; provision of electronic
sound links; streaming of audio material on the internet;
broadcasting of multimedia entertainment content, films,
television shows, and special events; providing an online
forum where users can post ratings, reviews, and
recommendations of movies and television shows and on events
and activities in the field of entertainment and education;
streaming, broadcasting and transmission of audio and visual
content via the internet; video-on-demand transmission
services; broadcasting of esports events; streaming of
esports events; computer communication and internet access
relating to esports events; broadcasting services related to
electronic sports events; rental of tv and radio equipment
and digiboxes for broadcasting; rental of message sending
and telecommunication equipment; providing access to
internet platforms for the purpose of streaming and
downloading audio books and electronic books on mobile
phones, tablets and computers; providing access to a website
for users where they can post reviews and recommendations
about books and magazine; information, advisory and
consultancy services relating to all the aforesaid services. Multimedia entertainment software publishing services;
multimedia publishing of books; on-line publication of
electronic books and journals and audio books; on-line
publishing services; providing electronic, non-downloadable
publications online; publication of audio books and audio
recordings; provision of multimedia entertainment programs
by television, broadband, wireless and on-line services;
entertainment services provided by on-line streams; distance
learning services provided online; educational services
relating to computer systems; training in the operation of
software systems; instruction in the use of data processing
devices, systems and programs; provision of instruction
relating to data processing; training services related to
the maintenance and repair of computer-controlled testing
systems; production of video and sound recordings;
production of entertainment in the form of television
programs and films; audio, film, video and television
recording services; production of audiovisual presentations
and recordings; provision of automated video recording
services; film production services; film production for
entertainment purposes; providing multi-media entertainment
via a website; television programme and film preparation and
production; showing of television programmes and films;
entertainment services relating to sport; rental services
for videos, films, television programs and books; providing
electronic publications; publication, publishing, loan and
rental of books, including audio books and magazines,
including electronic; rental of audio-visual apparatus;
rental of motion pictures; rental services for audio and
video equipment; information, consultancy and reviews
relating to books and magazines; publishing services;
translation services; library services for audio recordings,
provided online through a computer or telecommunications
network; providing non-downloadable films and television
shows via video-on-demand transmission services;
entertainment services in the nature of ongoing television
series and movies; entertainment services in the nature of
development, creation, production, distribution, and
post-production of motion picture films, television shows,
special events, and multimedia entertainment content;
entertainment services in the nature of a live theatrical,
musical or comedic performance; providing online
non-downloadable video clips and other multimedia digital
content containing audio, video, artwork, and/or text from
or related to an ongoing television series; providing
entertainment information via a website; entertainment
services, namely, providing on-line computer, electronic and
video games; providing temporary use of non-downloadable
interactive games; providing information, reviews, and
recommendations regarding movies and television shows via a
website and video-on-demand transmission services;
interactive entertainment services; online interactive
entertainment; educational and entertainment services,
namely, providing interactive online non-downloadable
multimedia entertainment content; entertainment and
educational services, namely, providing movies, television
shows, and information, reviews, and recommendations
regarding movies and television shows; entertainment
services in the nature of providing television shows,
movies, and multimedia content and information, reviews, and
recommendations regarding television shows, movies, and
multimedia content via a website; organization of events for
entertainment and cultural purposes; conducting of live
esports events; entertainment services relating to esports;
esports coaching and officiating; organisation and
production of esports events and activities; production of
esports events for television; providing esports facilities;
provision of information relating to esports; ticket
reservation and booking services for esports events;
e-sports services; arranging and conducting e-sports
competitions; entertainment in the nature of e-sports
competitions; games equipment and game console rental;
information, advisory and consultancy services relating to
all the aforesaid services. Advisory services in the field of product development and
quality improvement of software; design and development of
software in the field of mobile applications; design and
development of operating software for computer networks and
servers; design and development of computer software for
supply chain management; maintenance of software for
communication systems; providing online non-downloadable
software for use in communication; providing temporary use
of non-downloadable interactive entertainment software;
providing temporary use of on-line non-downloadable software
for the management and transmission of information; software
as a service [SAAS] services; software development for
automated communication network operation; development of
computer programs recorded on data media (software) designed
for use in construction and automated manufacturing
(cad/cam); provision of technical support in the operation
of computing networks; providing quality assurance services;
research relating to the computerised automation of
industrial processes; software as a Service [SaaS] for
management of sales, customer service, distribution,
inventory, purchasing, order processing, manufacturing,
workflow and production management; Software as a Service
[SaaS] for provision and automation of business intelligence
and business predictive analytics and for digitising
business processes; Software as a service [SaaS] featuring
computer software platforms for artificial intelligence;
Software as a service [SaaS] featuring software for machine
learning; Software as a Service [SaaS] for cloud network
monitoring; providing temporary use of on-line
non-downloadable software featuring software for
communication; providing temporary use of on-line
non-downloadable software for network management; cloud
computing featuring software with machine learning model
functionalities for data processing and for analyzing,
compiling, organizing and monitoring data; platform as a
service (PaaS) featuring software for use in centralizing
management of machine learning models; Platform as a service
(PaaS) featuring knowledge-based artificial intelligence
computer software platforms, data analytics software
platforms and automation software platforms that combine
machine learning and automation to optimize and analyze
information technology processes, to detect real-time
anomalies and develop a fault diagnosis; design and
development of automation platforms; management of computer
systems and consulting services in the field of automated
workflows driven by rules and artificial intelligence;
hosting of telecommunication networking web sites to users
featuring automated and artificial intelligence-driven
automated workflow services and document, business process
and customer relationships management; providing temporary
use of a non-downloadable computer interface for the
development of data transmission networks; data migration
services; providing information about the design and
development of computer software, systems and networks;
design and development of engineering products; product
development for others; design and development of systems
for data input, processing, display and storage; providing
temporary use of on-line non-downloadable software for
importing and managing data; monitoring services and remote
monitoring of computer systems and network systems; design
and development of control, regulation and monitoring
software for computer systems and electronic devices;
monitoring of computer systems to detect breakdowns;
testing, analysis and monitoring of telecommunication
signals; remote computer backup services; remote server
administration; testing the functionality of apparatus and
instruments; computer system analysis; computer programming
for data processing and communication systems; design and
development of data processing systems, operating system
software and data storage systems; configuration of computer
systems and networks; installation, maintenance and repair
of software for computer systems and electronic devices;
hosting web portals; technical support services relating to
computer software and applications; development of online
electronic systems for data transfer; computer aided product
development; industrial and technical analysis, development
and research services; testing, analysis and monitoring of
system algorithms for generating and processing
telecommunications and navigation data; design and
development of wireless computer networks; providing
temporary use of on-line non-downloadable operating software
for accessing and using a cloud computing network; providing
artificial intelligence computer programs on data networks;
cloud storage services using artificial intelligence for
processing and analysing data; Software as a service [SaaS]
services featuring software for machine learning, deep
learning and deep neural networks; platforms for artificial
intelligence as software as a service [SaaS]; diagnosis of
faults in computer software; technical data analysis
services; creation of control programs for automated
measurement, assembly, adjustment and related visualization;
development of software solutions for internet providers and
internet users; cloud computing; cloud hosting provider
services; cloud storage services for electronic data; design
and development of operating software for accessing and
using a cloud computing network; electronic data storage;
energy saving management for communication networks; energy
usage monitoring services, namely recording and monitoring
data relating to energy consumption and energy saving;
design and development of industrial processes, industrial
products and industrial machinery; computer aided design for
manufacturing operations; industrial process research;
development of software solutions for industry; development
of software solutions for the medical field; development of
software solutions for the pharmaceuticals industry;
development of software solutions for the electronics
industry; development of software solutions for the
semiconductors industry; analysis of computer and
telecommunication systems and networks; computer systems
monitoring; cloud-based data processing; data security
services; design of digital signage monitors; design and
development of computer game software; rental of computer
game software; rental of entertainment software;
information, advisory and consultancy services relating to
all the aforesaid services.
67.
COMPUTER-IMPLEMENTED METHOD FOR AUTOMATED CALL PROCESSING
According to an embodiment, a computer-implemented method for automated call processing comprises: receiving a call from a user; identifying an environment of the user during the call using acoustic scene classification; configuring at least one property of an automated call processing system according to the identified environment; and processing the call at least partially using the automated call processing system.
G10L 15/32 - Multiple recognisers used in sequence or in parallelScore combination systems therefor, e.g. voting systems
H04M 3/42 - Systems providing special services or facilities to subscribers
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G10L 13/033 - Voice editing, e.g. manipulating the voice of the synthesiser
68.
METHOD AND SYSTEM FOR PROVIDING MEASUREMENT-BASED NEW RADIO COVERAGE MAP
Disclosed is a method for providing measurement-based new radio (NR) coverage map (200, 300). Moreover, the method comprises obtaining, from a radio network, a user equipment data; obtaining a first information corresponding to a Long-Term Evolution (LTE) minimization 5 of driving test (MDT); obtaining a second information corresponding to an LTE-NR event; combining the first information and the second information to provide a network performance information; and determining, based on the user equipment data and the network performance information, a location information corresponding to the NR 10 coverage. Disclosed also is a system for providing measurement-based new radio (NR) coverage map.
According to an embodiment, a computer-implemented method for call security comprises: receiving a call from a user; identifying an environment of the user during the call using acoustic scene classification; comparing the identified environment to a preconfigured environment whitelist; and in response to at least the preconfigured environment whitelist not comprising the identified environment, performing at least one security policy action.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
H04M 3/493 - Interactive information services, e.g. directory enquiries
A computer implemented method for controlling a communications network. The method is performed by obtaining first meteorological data comprising information about weather conditions at different locations; obtaining first performance data from the communications network (101) at different network locations; mapping the first meteorological data and the first performance data to each other based on location information to obtain a plurality of data points of performance data and respective weather condition; creating a model of impact of the weather conditions on performance data based on the plurality of data points; and providing the model for the purpose of controlling the communications network (101).
Example embodiments may relate to determining root sequence indices (RSI) for a cell. A computer- implemented method may comprise: obtaining a first set of N1 RSIs allocated to a first cell; obtaining a plurality of RSI sets allocated to a plurality of second cells; determining an RSI conflict; determining a conflict rank for the plurality of second cells, wherein the conflict rank is indicative of a level of expected interference with the first cell; determining a plurality of RSI lists associated with the plurality of second cells; selecting an RSI list, which is indicative of a set of N1 RSIs not allocated to any of the plurality of second cells, and which is associated with a cell having a conflict rank indicative of a lowest level of expected interference; and allocating the set of N1 RSIs not allocated to any of the plurality of second cells to the first cell.
A method, apparatus and computer program are disclosed for fixed communication line malfunction detection and recovery, including: monitoring states of a plurality of fixed communication lines; extrapolating future states of the plurality of fixed communication lines; determining a recovery group having as members any of the plurality of fixed communication lines having future states extrapolated to decline below a predetermined minimum quality threshold; and causing initiation of recovery action for each member of the recovery group before the extrapolated decline below the predetermined minimum quality threshold.
According to an embodiment, a computer-implemented method for obtaining at least one number based on a word buffer comprises: obtaining a word buffer; filling a number word buffer based on the word buffer by repeatedly obtaining a word from the word buffer, checking whether the word is a number word, and, in response to the word being a number word, adding the word to the number word buffer; in response to at least one preconfigured condition being met, converting the number word buffer into at least one number; and adding the at least one number to a result buffer.
According to an embodiment, a computer- implemented method for punctuation of text from an audio comprises: obtaining an audio input comprising speech data; identifying a plurality of silent sections in the audio input; grouping the plurality of silent sections into a plurality of groups, wherein each group in the plurality of groups corresponds to a punctuation mark or a space without a punctuation mark; and associating each silent section in the plurality of silent sections with a punctuation mark or a space according to the group of the silent section, thus obtaining punctuation information.
Disclosed is a system (100) and a method (200) for detecting anomaly in a radio access network (RAN (102, 300)). The method comprises receiving quality parameters data for a wide communication network (308) established by plurality of base stations (110, 302) associated with the RAN; defining a first radio fingerprint based on the quality parameters data for the wide communication network; monitoring, by one of the base stations installed in a geological area (306), quality parameters data for a local communication network (310); defining a second radio fingerprint based on the quality parameters data for the local communication network; comparing the first radio fingerprint and the second radio fingerprint to determine variation in the quality parameters data therebetween; and generating an alert signal indicative of presence of a possible fake base station (304) in the geological area based on the determined variation in the quality parameters data.
Example embodiments relate to counteractions for remedying anomalies within a communication network. A computer-implemented method may comprise detecting an anomaly associated with at least a first cell; determining a counteraction for the first cell; identifying at least one second cell impacted by the counteraction; obtaining first performance indicator(s) the first cell and/or the at least one second cell, wherein the first performance indicator(s) are associated with a first time period before performance of the counteraction; causing performance of the counteraction at the first cell or providing an indication of the counteraction for performance of the counteraction at the first cell by a user; obtaining second performance indicator(s) associated with the first cell and/or the at least one second cell, wherein the second performance indicator(s) are associated with a second time period after performance of the counteraction; and verifying the counteraction based on first performance indicator(s) and the second performance indicator(s).
A computer implemented method for speech recognition from an audio signal includes: obtaining initial values for silence detection parameters including: a lead period; a threshold amplitude; and a terminal period. Detect an amplitude of the audio signal at a first time T1 of the audio signal. Optionally adjusting the threshold amplitude based on the detected amplitude. Starting the speech recognition from a second time T2 of the audio signal. Starting silence detection from the audio signal when the lead period has elapsed after the second time T2 including: responsive to detecting an amplitude below the threshold amplitude for a duration of the terminal period, terminating the speech recognition and the silence detection at a third time T3 of the audio signal and adjusting the silence detection parameters based on the detected amplitude changes of the audio signal between the first time T1 and the third time T3.
Disclosed is computer-implemented method for automatically detecting cross-connected cells in communication network. The method comprises obtaining first cell data of source cell (304, 404, 508) within communication network; determining effective area (302, 506) of source cell using first cell data; classifying each neighbouring cell of source cell into one of: a first group, a second group, based on location of neighbouring cell; calculating share of handover events from source cell to neighbouring cells in first group using first cell data; and when share of handover events from source cell to neighbouring cells in first group lies below first threshold, filtering out neighbouring cell(s) from amongst second group with which handover events of source cell lies above second threshold and determining source cell to be cross-connected cell when: direction of filtered cell(s) (402, 502) is opposite to direction of the source cell; and/or effective area (504) of filtered cell(s) does not overlap with effective area of source cell.
A computer implemented method for controlling a virtual power plant, VPP, comprising a plurality of spatially distributed energy storage, DES, devices. The method is performed by operating the virtual power plant according to a first plan, wherein the first plan provides a pre-planned schedule for charging or discharging the DES devices over a first time period to fulfil a power reserve obligation; analysing the first plan in real time during the first time period, wherein the analysis is performed in view of predefined acceptance criteria and real time operating context data; and identifying a need to adjust the first plan on the basis of the analysis and accordingly adjusting the first plan in real time during the first time period.
A computer implemented method for controlling a virtual power plant, VPP, comprising a plurality of spatially distributed energy storage, DES, devices. The method is performed by obtaining historical reference data and DES infrastructure data; identifying an operating objective for the virtual power plant; simulating operation of the virtual power plant over a first time period based on the historical reference data and the DES infrastructure data; selecting an operating plan for the first time period based on the simulation in view of the operating objective, wherein the operating plan concerns utilization of the virtual power plant for grid balancing; using the selected operating plan and responsively monitoring operation of the virtual power plant over the first time period; and using results from the monitoring to adjust future simulations.
Disclosed is a method for remotely monitoring sub-systems (204, 206, 208, 308, 310). The method is implemented by first software application executing on client device(s) (202, 414, 702) communicably coupled to sub-systems. The method comprising: polling data from sub-systems, wherein a sub-system comprises at least one of: computing device, server, operating system, second software application, and wherein data from the sub-system is polled at a polling frequency; classifying data into a category from amongst categories; analyzing classified data, based on pre-stored data at centralized server (210), to determine data points of classified data that have changed; and transmitting data points to centralized server at a upload frequency, for storage thereat.
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Disclosed is a method (200) and a system (100) for detecting an anomaly in sensor time series data of a sensing arrangement (110). The method comprises implementing a neural network (120) trained on training data comprising prior sensor time series data; re-constructing a sample sensor time series data for a target time period using the trained neural network (120); determining an anomaly score variable based on a re-construction error in the re-constructed sample sensor time series data; determining a confidence interval for the target time period based on a distribution of the determined anomaly score variable; mapping a target sensor time series data, generated by the sensing arrangement (110) corresponding to the target time period, to the determined confidence interval; and indicating an anomaly in the target sensor time series data if the target sensor time series data is not substantially within the determined confidence interval.
A computer-implemented method for automatically detecting a fraud call. A call request is received from a caller device to initiate a voice call with a called device at a local Public Land Mobile Network (PLMN). The call request is identified originating from a foreign Public Land Mobile Network (PLMN). In response to detecting that a caller ID of the caller device is associated to a local Public Land Mobile Network (PLMN), current location information is requested from a database of the local Public Land Mobile Network (PLMN). If the location information indicates the caller device is attached to the foreign Public Land Mobile Network (PLMN), determining the call request as authentic; and if the location information indicates the caller device is attached to the local Public Land Mobile Network (PLMN), determining the call request as fraud.
A computer implemented method for energy savings management for cells of a sector or a base station of a communication network. The sector or base station has co-located cells that operate on different frequency bands. The method is performed by obtaining a default energy savings plan that calls for fully shutting down at least one of the cells for a first time period and provides a first amount of energy savings; evaluating energy savings achievable by using partial shutdown in cells and determining a second time period of partial shutdown that is needed for achieving the first amount of energy savings; obtaining a third time period that is usable for energy savings actions; and choosing to use partial shutdown in the cells, if the second time period is shorter than the third time period, and else choosing to use the default energy saving plan.
A computer implemented method for evaluating effect of a change made in a communication network. The method is performed by comparing values of the performance indicator in a cell of interest before and after the change to obtain a first comparison result; comparing values of the performance indicator in a set of reference cells before and after the change to obtain a second comparison result; and evaluating the effect of the change made in the communication network based on difference between the first comparison result and the second comparison result.
A computer implemented method of monitoring and controlling a target system, such as a communication network or an industrial process. The method includes receiving information about anomalies in operation of the target system detected by an automated anomaly detection mechanism; automatically determining certainty characteristics of the detected anomalies; submitting detected anomalies to expert evaluation in priority order determined based on the certainty characteristics; and adjusting the determination of certainty characteristics of the detected anomalies and/or the automated anomaly detection mechanism based on results of the expert evaluation.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
87.
METHOD AND SYSTEM OF IMPROVING FAULT TOLERANCE OF NETWORK
Disclosed is a method of improving fault tolerance of network, network comprising plurality of relay nodes, internet access node and plurality of customer nodes. The method comprising identifying first set of relay nodes connecting one of customer nodes to internet access node,5 selecting a first relay node from first set of relay nodes, to be simulated as a first faulty node in the network, detecting, based on the simulation, number of customer nodes without at least one corresponding network path connecting to the internet access node due to the selection of the first relay node as the first faulty node, determining impact score of the 10 first relay node based on the detected number of customer nodes without at least one corresponding network path connecting to the internet access node, and triggering one or more changes in topology of network according to the impact score to improve fault tolerance of network.
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
H04L 41/147 - Network analysis or design for predicting network behaviour
H04L 41/0668 - Management of faults, events, alarms or notifications using network fault recovery by dynamic selection of recovery network elements, e.g. replacement by the most appropriate element after failure
88.
SYSTEM AND METHOD FOR OPTIMIZING FAULT DETECTION IN INTERNET OF THINGS NETWORK
Disclosed is a method for optimizing fault detection in an Internet of Things (IoT) network (204). The method comprises determining a fault activity associated with an IoT device in IoT network (204); identifying a location information of IoT device (202); determining whether fault activity is associated with a mobile network corresponding to the location information; performing one of an automation activity of generating a service ticket for fault correction of mobile network, when fault activity is associated with mobile network, or generating a field service ticket for fault correction of the IoT device (202), when fault activity is not associated with mobile network. Disclosed also is a system for optimizing fault detection in an IoT network, system comprising a processor configured to perform the steps of the aforementioned method.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04W 4/70 - Services for machine-to-machine communication [M2M] or machine type communication [MTC]
H04W 24/00 - Supervisory, monitoring or testing arrangements
A computer implemented method for uplink power control in a mobile network. The method is performed by obtaining (301) signal to interference and noise ratio, SINR, of a first cell of the mobile network; comparing (302) the SINR to current uplink power parameter of the first cell; determining (303) a new value for the uplink power parameter based on the comparison so that, if the SINR is higher than the current uplink power parameter, the current uplink power parameter is increased to obtain the new value for the uplink power parameter, and if the SINR is lower than the current uplink power parameter, the current uplink power parameter is decreased to obtain the new value for the uplink power parameter; and providing (304) the determined new value of the uplink power parameter for use in uplink power control of the first cell.
H04W 52/14 - Separate analysis of uplink or downlink
H04W 52/24 - TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
H04W 52/36 - Transmission power control [TPC] using constraints in the total amount of available transmission power with a discrete range or set of values, e.g. step size, ramping or offsets
A method for managing a distributed battery arrangement, wherein the arrangement comprises a pool of battery assets. The arrangement allows capacity limits to be set for the battery assets. The capacity limits are a first capacity limit (C1) defining minimum charge that is to be maintained in the battery asset; and a second capacity limit (C2) defining maximum charge; wherein capacity falling between the first capacity limit (C1) and the second capacity limit (C2) is a usable capacity range (C3). Usage of the usable capacity range (C3) of the battery assets is controlled for balancing and/or optimization tasks.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the networkCircuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
A computer implemented method for controlling a pool of energy storages. The energy storages of the pool have capacity limits defining how the energy storages are intended to be used. The method is performed by detecting (403) an exception event; selecting (404) one or more energy storages associated with the detected exception event; and temporarily adjusting (405) at least one capacity limit of the selected energy storages in accordance with the detected exception event.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H02J 9/06 - Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over
92.
Automated evaluation of effects of changes in communications networks
A method for evaluating effect of a change in a communications network includes receiving a first set of performance indicator values. measured over a first period of time before the change in the communications network; receiving a second set of performance indicator values with performance indicator values measured over a second period of time after the change in the communications network; comparing the first set and the second set to evaluate the effect of the change; determining a performance threshold based on the performance indicator values of the first set; determining a first performance ratio value based on the performance indicator values of the first set and the performance threshold; determining a second performance ratio value based on the performance indicator values of the second set and the performance threshold and providing output based on the first performance ratio value and the second performance ratio value.
A computer implemented method for controlling a pool of energy storages. The energy storages of the pool have capacity limits defining how the energy storages are intended to be used. The method is performed by detecting (403) an exception event; selecting (404) one or more energy storages associated with the detected exception event; and temporarily adjusting (405) at least one capacity limit of the selected energy storages in accordance with the detected exception event.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H02J 9/06 - Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over
A computer implemented method for managing a distributed battery arrangement, wherein the arrangement comprises a pool of battery assets (121-125), wherein the battery assets of the pool are individually owned. The method is performed by obtaining real time data relating to current state of the battery assets of the pool, wherein the current state of the battery assets of the pool comprises at least information about capacity and wear profile of the battery assets of the pool; and selecting one or more battery assets from the pool based on the obtained real time data to fulfil a capacity requirement for frequency balancing of electric grid (151).
Disclosed is a method and a system (200, 302) for modifying a state of a device (206, 304) using detected anomalous behaviour in a self-exciting point process. The method comprises receiving time series data for a time period of the self-exciting point process, selecting a first portion, corresponding to a first time period, from the received time-series data, characterizing a normal behaviour for at least the first time period of the self-exciting point process, defining a baseline range for the self-exciting point process based, at least in part, on bounds of first point values in the selected first portion, processing a second portion based on the defined baseline range to detect one or more second point values exceeding the defined baseline range being characterized as the one or more anomalous events for at least the second time period of the self-exciting point process and modifying the state of the device based on the characterized one or more anomalous events.
H04L 43/0817 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
H04L 41/147 - Network analysis or design for predicting network behaviour
H04L 41/08 - Configuration management of networks or network elements
H04L 41/5009 - Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
H04L 43/0805 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
A method for managing a distributed battery arrangement, wherein the arrangement comprises a pool of battery assets. The arrangement allows capacity limits to be set for the battery assets. The capacity limits are a first capacity limit (C1) defining minimum charge that is to be maintained in the battery asset; and a second capacity limit (C2) defining maximum charge; wherein capacity falling between the first capacity limit (C1) and the second capacity limit (C2) is a usable capacity range (C3). Usage of the usable capacity range (C3) of the battery assets is controlled for balancing and/or optimization tasks.
H02J 3/32 - Arrangements for balancing the load in a network by storage of energy using batteries with converting means
H02J 3/38 - Arrangements for parallelly feeding a single network by two or more generators, converters or transformers
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the networkCircuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
97.
Network monitoring related to remote electrical tilt
A computer implemented method of monitoring a communication network. The method includes obtaining first information related to remote electrical tilt configurations deployed in the communication network; obtaining second information related to cell documentation; comparing the first and second information to identify mismatches between the first and second information, if any; and outputting an alarm concerning mismatches identified as a result of the comparison.
A computer implemented method for automated operation of a communication network (110). The method comprises determining (301) a fault activity in the network (110), selecting (302) an automation algorithm based on a root of the fault activity, determining (303) quarantine rules, and selecting (304) an automated action for solving the fault activity based on the quarantine rules.
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
H04L 41/0654 - Management of faults, events, alarms or notifications using network fault recovery
H04L 41/5074 - Handling of user complaints or trouble tickets
99.
OBTAINING AN AUTOENCODER MODEL FOR THE PURPOSE OF PROCESSING METRICS OF A TARGET SYSTEM
A computer implemented method for obtaining an autoencoder model for the purpose of processing metrics of a target system. The method includes obtaining a data set including metrics associated with the target system, the data set being intended for training the autoencoder for processing further metrics of the target system; masking the data set with a predefined mask configured to exclude certain parts of the data set; using the unmasked parts of the data set for training the autoencoder; masking reconstructed data from the autoencoder with the same predefined mask; using reconstruction error of the unmasked parts of the reconstructed data to update parameters of the autoencoder to obtain autoencoder model; using the masked parts of the data set for testing the autoencoder model; and providing the autoencoder model for processing further metrics of the target system.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
A computer implemented method for analyzing a target system for the purpose of controlling the target system. The method is performed by obtaining (301) a dataset comprising observations related to the target system; computing (302) alignment score for the dataset using a linear kernel to obtain a linear alignment score; computing (302) alignment score for the dataset using a non-linear kernel to obtain a non-linear alignment score; comparing (303) the linear alignment score and the non-linear alignment score; and if linear alignment score > non-linear alignment score, selecting (304) anomaly detection that uses Euclidean space measures, and else selecting anomaly detection that uses non-Euclidean space measures.
