6652results about "Machine-to-machine/machine-type communication service" patented technology

The Internet can be configured to provide communications to a large number of Internet-of-Things (IoT) devices. An example non-transitory, machine readable medium comprises instructions that, when executed, direct a processor to: cause a device to connect to a network of a decentralized database, discover a namespace of a node of the decentralized database, create a shared database partition in response to being accepted by the node, advertise a service to the decentralized database; and route data of a service between a private database partition and the shared database partition

Methods, systems, and computer program products for managing Internet of Things (IoT) network-connected devices.

The invention discloses an intelligent water quality monitoring device based on Internet of Things, relates to the technical field of environmental monitoring, and aims to analyze a complex nonlinear relationship in water quality data, accurately predict a water quality change trend and identify potential water quality problems in advance through a deep learning model and a system. The dynamic weight calculation module can dynamically adjust the importance of water quality parameters according to real-time data and environmental changes, the monitoring precision and adaptability are improved, an intelligent feedback mechanism automatically adjusts the sampling frequency and the sensor position when an early warning signal is triggered, accurate monitoring of the water quality changes is ensured, and the monitoring accuracy is improved. The Internet of Things technology supports real-time transmission of water quality data and analysis results to the cloud, managers can check water quality states, historical trends and early warning records through a remote monitoring interface, the response capability and management efficiency of the system are improved, and the intelligent water quality monitoring device has the advantages of being high in precision, high in intelligence and high in adaptability.

Disclosed are methods, systems, and computer-readable medium to perform operations including: generating a registration request comprising a capability of the UE to serve as a gateway for a personal Internet-of-things network (PIN); sending the registration request to a base station serving the UE; receiving, from the base station, a registration accept message comprising a PIN gateway authorization; and initiating establishment of the PIN with at least one other device, wherein the UE serves as the gateway of the PIN to the base station.

The invention provides a real-time map route construction method and system. The method comprises the following steps: installing various sensors on an unmanned aerial vehicle to obtain multi-modal data of an environment; converting the multi-modal features into a high-dimensional embedding space, and constructing a real-time three-dimensional environment model based on a multi-modal point cloud reconstruction algorithm; deploying edge computing nodes, and distributing computing tasks to the edge computing nodes; planning a cooperative path among the multiple unmanned aerial vehicles; constructing a multi-unmanned aerial vehicle cooperative global adaptive adjustment mechanism to dynamically adjust the flight path of the unmanned aerial vehicle; and performing priority ranking on the tasks of the flight path of the unmanned aerial vehicle, constructing a path adjustment optimization mechanism according to the real-time flight condition to minimize the task failure risk, and updating the task priority and the scheduling strategy according to the feedback after each task is executed. According to the invention, a plurality of key problems in the prior art are effectively solved, and a technical guarantee is provided for successful application of the unmanned aerial vehicle in more complex application scenes.

Embodiments of the present disclosure relate to methods, devices and computer readable media for communication. A first network device receives a first paging message from a second network device in a RAN, the first paging message comprising information on a MT-SDT for a terminal device, and determines, based on the information, whether the MT-SDT is performed for the terminal device. If the MT-SDT is performed for the terminal device, the first network device transmits, to the terminal device, a second paging message comprising an indication indicating that the MT-SDT is performed for the terminal device. In this way, the MT-SDT procedure can be triggered.

In one aspect, a computer system for implementing asset tracker safety enhancements in an internet of things network comprising: a plurality of asset trackers, wherein each asset tracker tracks one or more IoT assets and obtains a set of IoT data; a server computing device configured to be in communication with the one or more networks, wherein the server computing device is further configured to implement the following logic: enhance the plurality of asset trackers with a plurality of sensors and a plurality of algorithms to detect and transmit an alert when a hazardous condition is detected, wherein the plurality of asset trackers monitor one or more IoT assets sensor data; and initiate a risk prevention or risk detection warning protocol when a specified probability of a hazardous material is detected by at least one asset tracker of the plurality of asset trackers.

An operation mode from a plurality of operation modes can be determined (310) based on at least one traffic type originated from a UE. The plurality of operation modes can include at least one group operation mode and an individual operation mode. The at least one group operation mode can support a plurality of UEs grouped into a group of UEs. The at least one group operation mode can support at least one network entity communicating associated messages with the group of UEs including the UE. The associated messages can be associated with the group of UEs. A network entity can be informed (320) of the determined operation mode.

The invention provides a marine ecological environment influence tracking and monitoring method based on an offshore wind power project, and relates to the technical field of marine ecological environment, and the method comprises the steps: carrying out the ecological risk index calculation based on an obtained multi-modal feature vector, and obtaining ecological risk data, and configuring a space-time sequence based on the preprocessed comprehensive data source and the ecological risk data, and predicting a pollution diffusion path and migration blocking based on the preprocessed comprehensive data source. By introducing a dynamic evaluation model of an ecological risk index and combining time sequence modeling and spatial distribution modeling, dynamic analysis and future trend prediction of the ecological risk are realized, and by generating a risk thermodynamic diagram in real time, identifying a high-risk area and simulating a pollutant diffusion path and a biological migration blocking condition, the risk of the ecological risk can be predicted. According to the invention, the monitoring strategy can be dynamically adjusted according to the real-time monitoring data, a scientific basis is provided for construction optimization and ecological restoration, and the accuracy and timeliness of monitoring and evaluation are improved.

A system for data collection related to a fluid conveyance environment includes a data acquisition circuit comprising inputs and outputs; input sensors to provide sensor data values, coupled to a component in the fluid conveyance environment; and a processor comprising the data acquisition circuit. The processor is configured to determine a data storage profile; responsive to the data storage profile, configure the data acquisition circuit to selectively couple at least one of the inputs to at least one of the outputs; interpret the at least one of the sensor data values; store at least a portion of the at least one of the sensor data values in response to the data storage profile; analyze a set of the sensor data values and determine a data quality parameter; and adjust at least one of the data storage profile and a data collection routine in response to the data quality parameter.

A system can include a backend system and a sensor kit configured to monitor an industrial setting. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to the backend system via a public network. The backend system can include a processing system and a storage system, where the processing system performs backend operations on the sensor data and the storage systems stores the sensor data.

A system for data collection related to a fluid conveyance environment includes a data acquisition circuit comprising inputs and outputs; input sensors to provide sensor data values, coupled to a component in the fluid conveyance environment; and a processor comprising the data acquisition circuit. The processor is configured to determine a data storage profile; responsive to the data storage profile, configure the data acquisition circuit to selectively couple at least one of the inputs to at least one of the outputs; interpret the at least one of the sensor data values; store at least a portion of the at least one of the sensor data values in response to the data storage profile; analyze a set of the sensor data values and determine a data quality parameter; and adjust at least one of the data storage profile and a data collection routine in response to the data quality parameter.

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

Methods, systems, and devices for wireless communications are described. A UE may be configured with a machine learning model by a core network to perform analytics, training, or inferences. The UE may indicate capability information to a core network entity, including a list of machine learning models supported at the UE. A centralized core network entity may manage different machine learning models and may send information for a machine learning model to the UE, such as through another core network entity. The UE or the core network may initiate the configuration. For example, the UE may request to be configured with a machine learning model. The core network may send control signaling that indicates a configuration for the machine learning model to the UE. The UE may perform analytics based on the machine learning model.

A first radio terminal of a radio communications network. In one example, the first radio terminal includes an electronic processor, a communication module, and an antenna. The electronic processor is configured, together with the communication module, and the antenna, to cause the radio terminal to transmit, in a first transmission to a second radio terminal, data via a first subset of a set of SPS radio resources, reserve a second subset of the set of SPS radio resources for a subsequent data transmission, and in response to detecting a triggering event, skip the subsequent data transmission.

A method of channel access adjustment for sidelink (SL) communication in a shared / unlicensed spectrum by a user equipment (UE) includes transmitting, by the UE, at least one physical sidelink shared channel (PSSCH) transmission in a reference duration for a latest channel occupancy initiated using Type 1 channel access procedures and performing, by the UE, a contention window adjustment operation based on at least one hybrid automatic repeat request-acknowledgement (HARQ-ACK) feedback corresponding to the at least one PSSCH transmission.

The invention provides a crop planting environment data acquisition and real-time optimization device integrated with the Internet of Things technology, which comprises a data acquisition module, a data cleaning and feature extraction module, an environment optimization strategy generation module, a decision support and execution module, an intelligent learning and optimization module and a monitoring and data visualization module, relates to the field of communication and data processing. The environment data is collected in real time through the distributed Internet of Things equipment, the planting area is fully covered, the problem of insufficient data acquisition in the prior art is solved, and a reliable data source is provided for subsequent optimization. The real-time performance and comprehensiveness of data acquisition are improved, and the accuracy of basic data optimization is ensured. An adaptive signal enhancement model is introduced, complex interference is effectively identified and eliminated, the intensity of weak signals is enhanced, and the problem that the optimization effect is reduced due to data noise in the prior art is solved. The precision and efficiency of data processing are improved, and high-quality input is provided for an optimization model.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

A wireless adapter for a standalone medical device can include a socket housing at a first end of the wireless adapter along a longitudinal axis of the wireless adapter, the socket housing configured to receive and electrically connect with a wireless dongle. The adapter can further include a medical device connector at a second end of the wireless adapter opposite the first end. The medical device connector can electrically connect with a standalone medical device; receive patient data from the standalone medical device; and pass the patient data to the wireless dongle to enable the wireless dongle to wirelessly transmit the patient data to a medical network interface coupled to a patient monitoring hub.

An access network device receives first information from an access and mobility management function network element. The first information carries a data size of downlink data of a terminal device buffered in a user plane function network element or a session management function network element, the terminal device is in an inactive state, and an extended discontinuous reception cycle is configured by the access network device for the terminal device. The access network device determines, based on the data size of the downlink data, that the downlink data is small data. The access network device sends a first indication to the terminal device, to indicate the terminal device to perform small data transmission, and a second indication to the user plane function network element, to indicate the user plane function network element to send the small data to the access network device.

A drive unit adapted for use in farm equipment includes a first transceiver and a processing module. The processing module is configured to receive first data from the farm equipment, including sensor data and / or controller data, and integrate the received first data with additional second data indicating an agricultural prescription for a geographic region to form agricultural data. The processing module is also configured to apply one or more spatial filter constraints and temporal filter constraints to the agricultural data and then compute, from the filtered agricultural data, a difference between actual execution of one or more parameters of the agricultural prescription and expected execution of the one or more parameters. The processing module is further configured to, when the difference exceeds a predefined stored threshold, autonomously generate and transmit to a remote computing device, a settings alert to thereby trigger generation of an updated agricultural prescription.

A WTRU may receive a first message comprising one or more criteria associated with an application server. If one or more local application servers satisfy the one or more criteria, the WTRU may send a second message to the local client device. The second message may comprise information for accessing the one or more local application servers in the local network. If no local application servers in the local network satisfy the one or more criteria, the WTRU may send a third message comprising the one or more criteria to a central application management server. The WTRU may receive a fourth message from the central application management server indicating one or more non-local application servers that satisfy the one or more criteria. The WTRU may send a fifth message to the local client device with information for accessing the one or more non-local application servers.

The invention relates to the technical field of terminal monitoring, in particular to an intelligent security terminal collaborative monitoring system with edge computing capability. Comprising a multi-mode sensing unit; the edge calculation processing unit is used for distributing CPU and FPGA operation tasks by using a dynamic characteristic distillation technology and a hardware load feedback technology on the basis of multi-mode perception data; a distributed cooperative communication unit; and an intelligent decision-making unit. Visual, voiceprint and environmental physical signals of a security area are collected through the multi-modal sensing unit, unified time stamps and spatial coordinate association are added for multi-dimensional signals by means of the data synchronization module, and cooperation of the feature distillation module and the model optimization module in the edge calculation processing unit is combined. According to the method, multi-modal features are mapped to a unified feature space, high-value features are screened, and redundant convolution kernels are identified and removed, so that effective cooperative processing of multi-modal security and protection data can be realized, and the processing efficiency of edge-side sensing data is improved.

Analytics dashboards for critical event management systems that include artificial-intelligence (AI) functionalities, and related software. AI functionalities disclosed include pattern recognition and predictive modelling. One or more pattern-recognition algorithms can be used, for example, to identified patterns or other groupings within stored critical events, which can then be used to improve response performance and / or to inform the generation of predictive models. One or more predictive-modeling algorithms can be used to generate one or more predictive models that can then be used, for example, to make predictions about newly arriving critical events that can then be used, among other things, to provide optimal response performance and allow users to efficiently and effectively manage responses critical events. These and other features are described in detail.

A system includes a distributed ledger storing one or more smart contracts; one or more 5G small cells, each having one or more antennas mounted on a housing, each small cell sending packets of data trackable with the distributed ledger; and a processor to control a directionality of the antennas in communication with a predetermined target using 5G protocols.

Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points operationally coupled to at least one industrial component in at least one of an industrial boiler system or industrial pipeline system; a data storage structured to store a library of stored noise patterns associated with operation of the at least one industrial component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data; and a data analysis circuit structured to: analyze the collected data, determine a measured noise pattern for the at least one industrial component, and compare the measured noise pattern to the library of stored noise patterns to identify a changed condition of the at least one industrial component.

The invention provides a communication method and a communication device, which are used for providing a relay service for an AIOT (environmental Internet of Things) terminal through a relay device so as to improve the signal coverage of the terminal in an AIOT scene. According to the method, a relay device sends first information to a core network device, the first information being used for requesting to provide a relay service for an AIOT terminal, and / or being used for instructing the relay device to support providing the relay service for the AIOT terminal. The access network device may receive third information from the core network device to instruct the relay device to provide a relay service for the AIOT terminal. The relay device may also receive configuration information of a relay service from the access network device. Based on the method, the relay device can obtain the configuration information required for providing the relay service for the AIOT terminal from the access network device so as to support the relay device to provide the relay service for the AIOT terminal.

Some embodiments of this disclosure include systems, apparatuses, methods, and computer-readable media for use in a wireless network for communicating data over control plane in a 5G system. For example, some embodiments are directed to a user equipment (UE). The UE includes processor circuitry and radio front end circuitry. The processor circuitry can be configured to transmit, using the radio front end circuitry, a first message for connecting to a 5G network and indicating a capability of the UE relating to Cellular Internet of Things (CIOT). The processor circuitry can be further configured to transmit, using the radio front end circuitry and via a control plane to the 5G network, a second message comprising mobile originated data. The processor circuitry can be further configured to receive, using the radio front end circuitry, a third message from the 5G network.

The present application provides an electronic device and a control method for the electronic device. A control device, after discovering a first device, based on receiving an adding command for a network configuration for the first device input from a user, can send a network configuration request to the first device to establish a first encrypted session with the first device. The control device, under this first encrypted session, verifies legitimacy of the first device and, after the first device passes verification, can send network configuration information to the first device.

Embodiments of the disclosure provides to a method and device for provisioning PIN subscription data in a wireless communication system supporting a personal IoT network (PIN). The method performed by a user equipment (UE) in a wireless communication system supporting the PIN, the method comprises transmitting, to a mobility management function (AMF), a registration request message including PIN input information, and receiving, from the AMF, a registration accept message including PIN subscription data based on the PIN input information, wherein the UE in the PIN acts as at least one of a PIN element with gateway capability (PEGC) device and a PIN element with management capability (PEMC) device.