7026 results about "Wireless transmission" patented technology

A wireless transmit / receive unit, WTRU, receives a plurality of positioning reference signals from a plurality of terrestrial transmission points, the positioning reference signals including at least one positioning reference signal from a first terrestrial transmission point and at least one positioning signal from a second terrestrial transmission point, on condition that at least one value based on first measurements of the plurality of positioning reference signals satisfies a condition, transmits a request to initiate, at the WTRU, positioning using positioning reference signals received from satellites, received, in response to the request, information about a set of satellites, selects at least one satellite from the set of satellites, determines a second position estimate for the WTRU based on at least one positioning reference signal received from at least one selected satellite, and sends to a network node a message comprising information indicating the second position estimate for the WTRU.

There may be approaches for sidelink unlicensed (SL U) channel access in Mode 2. For example, a wireless transmit receive unit (WTRU) may perform SL U channel access and resource selection for channel occupancy time (COT) sharing and COT initiation within a resource selection window (RSW). The WTRU may detect COT and share based on control information, such as remaining duration, the number of scheduled transmission(s) within the COT, frequency resource assignment, priority, cast type, WTRU source and / or destination ID, COT / resource reservation, channel congestion, etc. The WTRU may determine SL COT initiation based on LBT and SCI sensing information including COT / resource reservation, priority, cast type, WTRU source and / or destination ID, channel congestion, etc. The WTRU may determine transmission resources within shared and initiated SL COT based on WTRU source and / or destination ID of a TB to transmit, RB interlace assignment indicated in decoded SCI associated with an overlapping reserved COT.

The invention discloses a mixed tower structure full-life damage intelligent sensing array early warning system, which relates to the field of mixed tower structure detection and comprises a multi-modal data collection module, an array topology optimization module, a self-adaptive signal processing module, a digital twin life prediction module, a grading early warning module and a visualization system. The multi-modal data collection module comprises a multi-modal sensor array, a self-powered module and a wireless transmission module. According to the invention, a full-scale sensing network is constructed, full-dimension damage perception from distributed monitoring to sudden damage capture and structural modal analysis is realized, wavelet transform and blind source separation are combined to eliminate environmental noise interference, a damage characteristic ultrasonic attenuation coefficient, an acoustic emission energy spectrum peak value, optical fiber strain gradient anomaly and vibration modal frequency deviation are extracted, and the detection accuracy is improved. And classification and positioning of damage types and intelligent diagnosis of severity levels are realized through a convolutional neural network and long and short memory neural network hybrid model, and a closed-loop processing flow from data acquisition to feature analysis is formed.

Methods, apparatus and systems are disclosed. In one embodiment, a method may be implemented by a first Wireless Transmit / Receive Unit (WTRU). The method may include receiving configuration information indicating a first set of RBs for performing a CSI-RS measurement, receiving an indication indicating a second set of RBs, and receiving an indication indicating that a first set of symbols or slots is not configured for a certain type of duplexing method and a second set of symbols or slots is configured for the certain type of duplexing method. The method may also include measuring a first CSI-RS in the first set of RBs in a symbol or slot in the first set of symbols or slots, measuring a second CSI-RS in a symbol or slot of the second set of symbols or slots in RBs that are in both the first set of RBs and the second set of RBs. determining a CSI based on the measurement of the first CSI-RS and the second CSI-RS, and reporting the CSI.

A wireless transmit / receive unit, WTRU, receives a positioning request message from another WTRU (1402). The positioning request message indicates a request associated with one or more of a sidelink positioning reference signals, SL-PRS, transmission or a SL-PRS reception and indicates a range of one or more parameters associated with the SL-PRS transmission or reception; these parameters comprise one or more of SL-RSRP, angle of departure AoD, angle of arrival AoA, and a line of sight LOS / NLOS metric. The WTRU measures the one or more parameters indicated in the positioning request message (1404) and performs the SL-PRS transmission (1410) or the SL-PRS reception (1410) on the condition that the measured parameters are within the range indicated in the positioning request message (1408).

The invention discloses a dredge pump control system and method for river regulation, and relates to the technical field of dredge pump control. The dredge pump control system comprises a sensing module, a centralized control module, an energy-saving execution module and a control parameter recording module; the sensing module is arranged on a multi-element sensor at a key part of a dredge pump for acquiring data, and the data is pre-processed by a microprocessor and then transmitted to the centralized control module at a high speed by a wireless transmission module, so that an accurate basis is provided for system control; according to the invention, by integrating multiple sensors and an advanced control algorithm, the dredging efficiency and accuracy of the dredge pump of the dredger are obviously improved; the sensing module can monitor key parameters of the dredge pump in real time, such as suction pressure, discharge flow, pump shaft temperature and sediment concentration, and it is ensured that the running state of the dredge pump is comprehensively known; and the centralized control module dynamically optimizes a control sequence by using a model predictive control and fuzzy logic control algorithm so as to adapt to variable working conditions.

The invention belongs to the technical field of aquaculture automation control, and particularly discloses an aquaculture environment intelligent disease early warning system and a storage medium, the system comprises a data acquisition layer, a data transmission layer, a processing platform layer and an application service layer; the data acquisition layer comprises an environment monitoring unit, a water quality sensor group, portable detection equipment and a data acquisition module; the data transmission layer comprises a wireless transmission module and an edge computing node; the processing platform layer comprises a machine learning prediction model and an environment factor correlation analysis model; the application service layer comprises an early warning information push module and a prevention and control scheme generation module. According to the intelligent disease early warning system for the aquaculture environment and the storage medium, a correlation model of environmental factors and disease occurrence is innovatively established, the early warning accuracy is 85% or above by adopting a machine learning technology, comprehensive monitoring and real-time early warning in the aquaculture process can be achieved, and accurate and efficient disease prevention and control are supported.

The invention discloses a bolt on-line monitoring method and system, and the method comprises the steps: generating a micro-motion feature matrix of a bolt according to a multi-dimensional vibration signal and a stress wave propagation characteristic of a bolt connection part; based on the micro-motion characteristic matrix, fusing local stress distribution data acquired by a bolt surface strain gauge, and outputting a health state quantitative index of the bolt; outputting a loosening risk level according to the health state quantitative index and historical loosening evolution data; and based on the looseness risk level and in combination with equipment operation state parameters, a self-adaptive decision tree model is adopted to dynamically adjust monitoring frequency and an alarm threshold value, a real-time monitoring strategy and a visual early warning report are generated, and a wireless transmission module is synchronously triggered to upload the real-time monitoring strategy and the visual early warning report to a cloud operation and maintenance platform. According to the embodiment of the invention, high-precision, self-adaptive and traceable bolt health state evaluation and early warning can be realized.

The invention discloses an AFIS intelligent fire-fighting monitoring system based on the Internet of Things technology, and relates to the technical field of fire-fighting safety, and the AFIS intelligent fire-fighting monitoring system comprises a front-end module, a central monitoring module, a data analysis module, an early warning module and a fault diagnosis module. The front-end module is used for monitoring fire-related environment data and fire-fighting equipment states through a plurality of sensor nodes; installing and deploying various types of sensor nodes in the key area; the collected original data is subjected to primary processing, including data cleaning, denoising, standardization and the like, so that the accuracy and reliability of the data are ensured; according to the invention, through integration of various sensor nodes, real-time monitoring of environment parameters of a key area and the state of fire-fighting equipment is realized, so that the fire prevention and response efficiency is obviously improved, the system can wirelessly transmit data by using the Internet of Things technology, the complexity of installation and maintenance is reduced, and the monitoring range is expanded.

The invention provides a seawater parameter calibration system, and belongs to the technical field of seawater parameter measurement. A thermohaline depth device is used for constructing a three-dimensional structure model to identify a spring layer position, a multi-parameter water quality sensing device is used for collecting data to establish a correlation model, and a dissolved oxygen analysis device is combined with thermohaline data to calculate a correction coefficient; and the spectral analysis device extracts feature recognition chemical components. The method comprises the key steps that a parameter interaction compensation function and an OceanParamNet model are adopted to construct a seawater comprehensive parameter calibration model, original data are corrected, and abnormal values are detected. The system realizes layered storage and wireless transmission of data, dynamically adjusts sampling frequency and power consumption, periodically executes a self-calibration program to compensate aging drift of a sensor, realizes high-precision self-adaptive calibration of seawater parameters, and solves the technical problems of low precision and poor environmental adaptability of seawater multi-parameter collaborative calibration in the prior art.

The invention relates to the technical field of fire early warning, and discloses a tunnel fire early warning method and system based on deep learning, and the method comprises the steps: deploying a sensor, constructing a wireless transmission network, and obtaining multi-modal data; carrying out preprocessing, feature extraction and feature fusion on the multi-modal data; constructing a tunnel fire early warning model adapted to the construction environment and designing a dynamic threshold mechanism; and designing a multi-level early warning response mechanism and carrying out early warning. According to the invention, the dust-proof smoke sensor is arranged to overcome the problem of susceptibility to dust interference; sampling frequency and communication frequency are automatically adjusted according to monitoring requirements during data transmission, so that the monitoring effect is ensured and the service life of a battery is prolonged; a tunnel fire early warning model based on TCNN is constructed, and a large-scale fire data set is constructed through FDS digital simulation to train the model; a dynamic threshold value capable of being automatically adjusted according to the environment is designed, and the problem that a fixed threshold value system does not adapt to the changing environment is solved.

The invention discloses a plant disease and insect pest early warning method and system based on plant monitoring, and belongs to the field of plant disease and insect pest early warning, and the method comprises the steps: extracting the contour of a lesion region through an edge detection algorithm, carrying out the smoothing of the contour through the combination of morphological operation, and obtaining a more precise lesion region boundary; according to an image segmentation result and a disease type identification result, a plant health condition evaluation model is established, and the plant damage degree is quantified; environmental data and image data are acquired from a plurality of sensor nodes distributed in a field, and the data are gathered to a regional gateway through wireless transmission; carrying out preprocessing and feature extraction on the converged heterogeneous data in a regional gateway, removing noise data and redundant information, and extracting key features; and carrying out pest detection and counting on the preprocessed image by using a deep learning model, carrying out modeling on a pest number change trend, predicting population density change in a period of time in the future in combination with environmental factors, and generating a detection result.

The invention provides a medical material distribution method and system based on an offshore medical rescue unmanned aerial vehicle. Wherein a marine environment model is generated; according to the marine environment model, an AI scheduling algorithm is applied to analyze the specific demand, priority and emergency degree of a marine receiving point, and an optimized task sequence and a material loading scheme are obtained; establishing a cooperative communication mechanism between offshore medical rescue unmanned aerial vehicle formations through an AI-driven distributed consensus algorithm, and dynamically adjusting a flight path and generating a distribution path by using an AI path planning technology in combination with real-time situation awareness and obstacle detection analysis; and after arriving at a specified receiving point, automatically calibrating the landing coordinates, and synchronizing the material state, handover information and environmental data to a medical team and a central scheduling system through a low-delay wireless transmission mode according to the distribution path. According to the technical scheme provided by the invention, the efficiency and reliability of offshore material distribution are greatly improved.

A localization system comprises: a device; a master unit which wirelessly transmits a first localization signal; a plurality of lateration units distributed about the area within which the device is being localized, wherein each lateration unit of the plurality independently starts its own timer upon its receipt of the first localization signal; and a localization unit. The device receives the first localization signal and responsively wirelessly transmits a second localization signal. Each of the lateration units: independently receives the second localization signal; stops its respective timer responsive to receipt of the second localization signal; and wirelessly transmits a timer count signal to a localization unit. The timer count signal identifies the transmitting lateration unit and a count of its respective timer. The localization unit utilizes the plurality of timer along with respective distances between the master unit and the lateration units to localize the first device via time-of-flight lateration.

Methods and apparatuses are described herein to address issues at the MAC layer resulting from potential Listen-Before-Talk (LBT) failures and delayed transmission. For example, a wireless transmit / receive unit (WTRU) may monitor a plurality of TX resource pools within a sidelink bandwidth part (BWP) for LBT events. The WTRU may cause, based on determining that an LBT failure has occurred, a corrective action associated with a sidelink MAC procedure. The WTRU may determine, based on the LBT failure, that a total number or consecutive number of detected LBT failures for one of the monitored TX resource pools exceeds a threshold, indicating a consistent LBT failure. The WTRU may, based on the consistent LBT failure, send an indication of the consistent LBT failure for the TX resource pool to peer WTRUs. and an indication of the consistent LBT failure for the TX resource pool to a serving cell.

A localization system comprises: a device; a master unit which wirelessly transmits a first localization signal; a plurality of lateration units distributed about the area within which the device is being localized, wherein each lateration unit of the plurality independently starts its own timer upon its receipt of the first localization signal; and a localization unit. The device receives the first localization signal and responsively wirelessly transmits a second localization signal. Each of the lateration units: independently receives the second localization signal; stops its respective timer responsive to receipt of the second localization signal; and wirelessly transmits a timer count signal to a localization unit. The timer count signal identifies the transmitting lateration unit and a count of its respective timer. The localization unit utilizes the plurality of timer along with respective distances between the master unit and the lateration units to localize the first device via time-of-flight lateration.

A wireless transmit / receive unit (WTRU) may be configured to implement layer 1 / layer 2 (L1 / L2) based inter-cell mobility procedures with reduced latency during handover or other mobility operations. The WTRU may be configured to receive configuration information associated with a plurality of candidate cells. The configuration information may be associated with a physical layer measurement for each candidate cell. The configuration information may include a measurement criteria. The WTRU may be configured to determine a subset of the plurality of candidate cells, with each candidate cell in the subset determined based on the measurement criteria. The WTRU may be configured to send a report indicating the subset. perform a physical layer measurement on the subset, and receive an indication to perform layer handover to a candidate cell of the subset.

The invention belongs to the technical field of intelligent weighing, and more particularly relates to an intelligent self-adaptive electronic scale system based on machine learning and a data processing method, and the system comprises a composite sensor module which is used for collecting gravity, volume and shape information; the automatic calibration module is connected with the composite sensor module and is used for carrying out regular calibration and calibration according to the data of the composite sensor module; the wireless networking module is connected with the automatic calibration module and is used for wirelessly transmitting and interacting the calibrated data; the intelligent operation and maintenance module is connected with the wireless networking module and is used for receiving the transmitted data and realizing equipment state monitoring and anomaly detection; the environment adaptation module is connected with the intelligent operation and maintenance module and is used for realizing adaptive compensation in a severe environment according to a detection result; and the man-machine interaction module is connected with the environment adaptation module and is used for displaying a compensated result and realizing a user-friendly operation interface, so that high-precision and all-around weighing perception is realized.

The present invention provides an unmanned aerial vehicle-based electric power patrol inspection control method and system. The method comprises: creating a flight path on the basis of an electric power patrol inspection area, and collecting images and position information of electric power devices by means of various types of devices carried by an unmanned aerial vehicle, the images and the position information being transmitted to a receiving terminal at a ground station in a wireless transmission mode; the ground station receiving the images and the position information that are collected in real time, processing and analyzing the images to obtain analytic status, such as defects, damage and corrosion, of the electric power devices; and, on the basis of the analytic status from the ground station, using the position information as distinguishing features to generate an electronic patrol inspection report, providing service lives, maintenance costs and maintenance measures of the electric power devices on the basis of the electronic patrol inspection report, and notifying maintenance staff of the position information of the electric power devices. The system comprises an unmanned aerial vehicle control module, an image processing and analysis module and an electronic patrol inspection report generation module. The present invention is of great significance to maintenance and management of electric power devices.

The invention discloses an information encryption method for wireless electronic countermeasure, and relates to the technical field of wireless transmission. According to the method, the wireless channel state is monitored in real time, the channel quality evaluation model is established, and the adaptive frequency adjustment algorithm and the cognitive radio technology are combined, so that whether the channel meets the communication quality requirement or not can be accurately judged, the influence of interference and attack on communication is effectively avoided, the continuity and stability of the communication process are ensured, and the communication quality is improved. The adaptability and the reliability of a communication system in a complex electromagnetic environment are remarkably improved, the quantum key is generated based on an encryption communication protocol of quantum key distribution, extremely high security of the key is ensured, communication data are difficult to crack in the encryption transmission process, security threats such as eavesdropping and tampering are effectively resisted, and the security of the communication system is improved. And through a secret key pre-distribution mechanism and a secret key updating process, the insufficient secret key distribution rate and the potential security risk are dealt with, the security of communication is further enhanced, and the confidentiality and integrity of information transmission are ensured.

A device configured for wirelessly transmitting a signal via a sidelink of a wireless communication network, e.g., 5G New Radio, includes a control unit configured for evaluating an availability of resources of the sidelink using an evaluation parameter. The control unit is configured to adapt the evaluation parameter.

The invention discloses a mine tunnel operation period deformation monitoring method and system, and relates to the technical field of mine tunnel monitoring, and the method comprises the following steps: carrying out the real-time monitoring of the deformation condition in a mine tunnel through a sensor device, and transmitting the collected monitoring data to a data processing center through a wireless transmission module. Real-time monitoring of mine tunnel deformation is achieved through the multiple sensors and the wireless transmission technology, the problem of data lag is solved, and monitoring accuracy and timeliness are improved. And in combination with a multi-objective optimization algorithm, the system automatically adjusts key parameters such as a supporting structure and a mining sequence according to real-time data, so that an optimal safety control scheme is ensured. According to the system, the operation efficiency and safety are improved, manual misjudgment is reduced, and the control strategy can be continuously optimized according to the operation stage.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for bistatic sensing. In certain representative embodiments, a wireless transmit / receive unit (WTRU) may receive information indicating reference signal (RS) configurations; first and second time thresholds; and transmission / reception point (TRP) locations. The WTRU may select a first set of TRPs. The WTRU may send an uplink bistatic sensing request including information indicating the first set, the obstacle location, and / or the WTRU location. The WTRU may receive an uplink bistatic sensing acknowledgment including information indicating a second set of TRPs. The WTRU may select one or more of the RS configurations based on the first and second time thresholds, and TRP locations of the second set. The WTRU may transmit one or more RSs using the one or more RSs configurations. The second set of TRPs may receive the transmitted RSs and perform bistatic sensing of the obstacle.

The embodiment of the invention provides a pressure sensing device and a pressure sensing system based on an implantable medical device, and relates to the field of implantable medical devices. The device comprises a pressure sensor and a sensor support. The pressure sensor is arranged on the sensor support and fixed to the interior of the body through the sensor support. The pressure sensor comprises a sensor body, a pressure sensing diaphragm and a flow velocity detection module. The flow velocity detection module comprises a support ring, a human-shaped elastic sheet, a second rectangular groove and a strain resistor; the pressure sensing diaphragm senses fluid pressure and converts the fluid pressure into resistance change, and when fluid acts on the human-shaped elastic piece, fluid speed information is converted into the resistance change. The pressure sensing system adopts a wireless transmission module to establish signal connection with a pressure sensing device, collects and analyzes in-vivo information, and obtains data through an external terminal device. The size of the detection device is reduced, the system integration degree is improved, and the device can be conveniently implanted into a body.

Procedures, methods, apparatuses, devices, and computer program products for determining sidelink transmission power. A first Wireless Transmit / Receive Unit, WTRU senses for at least one signal, using: a first receive beam in a first direction associated with an upcoming sidelink unicast transmission to a target WTRU and (2) a second receive beam for in an opposite direction, determines, from the sensed signal(s), scheduled transmissions that will interfere with the upcoming sidelink unicast transmission based on the scheduled transmissions overlapping in time and frequency with the upcoming sidelink unicast transmission, determines a transmission power to compensate for: (1) pathloss and (2) estimated interference at the target WTRU of scheduled transmissions interfering with and that have a lower priority than the upcoming sidelink unicast transmission, the estimated interference based on respective sensed signal received signal strengths, and sends to the target WTRU data in the sidelink unicast transmission using the determined transmission power.

The invention discloses a reservoir dam safety monitoring abnormity early warning method and system, and belongs to the technical field of safety monitoring, and the method specifically comprises the steps: installing a sensor array at a spillway, a dam body, a dam foundation and a dam shoulder part of a reservoir dam, collecting dam physical parameter data in real time, and transmitting the data to a monitoring center in a wireless manner; after receiving the data, the monitoring center preprocesses and analyzes the data, calculates parameters such as deformation, settlement and displacement of the dam, and compares the parameters with preset safety thresholds; if the dam is in an unsafe state, the system automatically sends out an early warning signal, and a worker acts according to an emergency plan; the method further comprises the steps of field inspection, treatment measure implementation and result recording and feedback, safe operation of the dam is ensured, and the early warning and emergency response efficiency is improved.

The invention discloses a wireless high-density electroencephalogram and myoelectricity hybrid synchronous acquisition and monitoring system, and belongs to the field of human-computer interaction. The wireless high-density electroencephalogram and myoelectricity mixed synchronous collecting and monitoring system is composed of three parts, namely a high-density electroencephalogram and surface myoelectricity signal collecting system, a base station system and an upper computer system. The high-density electroencephalogram and surface electromyogram signal acquisition system is responsible for acquisition and primary processing of signals, and the base station system performs data interaction with the high-density electroencephalogram and surface electromyogram signal acquisition system in a wireless transmission mode and transmits the processed signals to the upper computer system for further analysis and display. According to the invention, a wireless and distributed architecture and a high-channel-number data acquisition scheme are integrated, the problems of efficient acquisition and synchronous processing of electroencephalogram and myoelectricity mixed signals are emphatically solved, and the application range in the fields of brain-computer interfaces, virtual reality, neural rehabilitation, cognitive training and the like is widened.

An automated urinary output monitoring system includes a urine collection assembly, a scale, and a pump. The urine collection assembly includes a urinary catheter coupled to a first drainage tube. The interim container coupled to the first drainage tube and a second drainage coupled to a final container. The scale measures the weight of urine collected in the final container and a display can depict the volume of urine collected in the final container. A vacuum pump can be coupled with the final container to draw urine from the interim container into the final container, and an air vent can isolate the patient from the vacuum within the final container. The system can be configured to wirelessly transmit urine volume data to an external computing device. A gyroscope can be coupled with the scale to determine the orientation of the scale.

The invention relates to a brain-computer interface system and a brain-computer interface device.The brain-computer interface system comprises an implant host and a probe connected to the implant host, the probe is used for being implanted into the intracranial position of the human body to obtain electroencephalogram signals, and the implant host is used for being implanted into the non-intracranial position of the human body and processing the electroencephalogram signals; the implant host comprises a wireless charging module and a wireless communication module, the wireless charging module is used for wirelessly charging the implant host, and the wireless communication module is used for wirelessly transmitting the electroencephalogram signals processed by the implant host. According to the brain-computer interface system, the brain-computer interface system is designed into a split type, the probe used for acquiring the electroencephalogram signals is implanted into the brain of the human body, the implant host used for processing the electroencephalogram signals is implanted into the non-brain of the human body, the implant body with the power supply part can be far away from the brain, and brain tissue damage caused by fever is avoided.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent dynamic pilot frequency networking system and method for an image transmission module MESH ad hoc network. The method is based on spectrum fingerprint features, combines a real-time interference topological graph constructed by interaction of neighborhood nodes, identifies a conflict frequency set needing to be evaded through multi-dimensional weighted evaluation, and dynamically generates a pilot frequency strategy table containing main and standby frequencies and a switching threshold value by using a frequency hopping decision engine according to the conflict frequency set and a preset legal frequency pool. Synchronizing the pilot frequency strategy table to an associated relay node, generating a link stability evaluation matrix and feeding back the link stability evaluation matrix to a frequency hopping decision engine; and correcting a frequency switching threshold value and an alternative frequency weight in the pilot frequency strategy table based on the link stability evaluation matrix. According to the invention, the spectrum utilization efficiency of the unmanned aerial vehicle image transmission system can be improved, the stability and reliability of a multi-hop link are ensured, the networking time delay is reduced through a distributed decision-making mechanism, and an effective solution is provided for high-quality wireless transmission in a dynamic topology environment.