7684 results about "Communication unit" patented technology

The invention relates to the technical field of the Internet of Things, and discloses a machine room equipment environment monitoring method and system based on the Internet of Things, and the method comprises the steps: constructing an edge calculation hardware system of the Internet of Things to obtain an integrated terminal which integrates a communication unit, an acquisition unit and a control unit; performing multi-channel parallel acquisition and edge calculation analysis on equipment and environment parameters in the machine room to obtain a standard data tuple and an analysis data packet; executing local hierarchical storage and logic control to obtain a control instruction and storage data; executing three-layer network communication interaction on the storage data to obtain a remotely accessible monitoring view; according to the method, intelligent alarm and system self-maintenance are achieved, graded and classified alarm information and a system state report are obtained, the data transmission amount is greatly reduced, meanwhile, the system response delay is reduced, the control decision accuracy is improved, and the misoperation risk is reduced.

A system for breakage early warning of high-voltage transmission lines based on acoustic prints, including a data acquisition unit, an edge processing unit, a cloud server, a warning execution unit, and a communication unit. The data acquisition unit is configured to collect environmental information of a high-voltage transmission tower in real time through a multimodal sensing device. The edge processing unit includes an adaptive filtering module configured to eliminate wind noise interference in the environmental information and compensate for frequency response deviation. The cloud server can generate a warning instruction based on the environmental information. The warning execution unit can perform warning and alarming actions based on the warning instruction. The communication unit is configured to enable data and information transmission among the units. A method implemented by such system is also provided.

The invention relates to the field of grain depot ventilation management, and discloses an automatic management system for ventilation in intelligent grain depot production, which comprises an environmental parameter monitoring module, a data processing and analysis module, an intelligent ventilation decision module, a ventilation equipment linkage control module and a dynamic feedback optimization module, the environmental parameter monitoring module is used for collecting temperature, humidity and gas concentration data in the bin in real time through the Internet of Things communication unit; the data processing and analyzing module is connected with the environment parameter monitoring module; the intelligent ventilation decision-making module receives the multi-dimensional data atlas, analyzes the temperature gradient, the humidity sensitivity index and the mildew risk value in the atlas through a dynamic classification algorithm, and fuses external meteorological data; the ventilation equipment linkage control module is used for receiving the instruction sequence of the intelligent ventilation decision module; the dynamic feedback optimization module is used for monitoring the efficiency coefficient and the grain pile environment change rate in the ventilation process; the system has the advantages that the ventilation precision and efficiency are improved, and granary environment management is optimized.

The invention relates to the technical field of power system management, in particular to a Beidou-based power grid emergency wireless command system, which comprises a Beidou positioning communication terminal, a multi-source data fusion terminal, an intelligent decision-making terminal, a heterogeneous communication terminal and a visual command terminal. The Beidou positioning communication module accurately obtains the position of the power equipment and transmits an encryption instruction; the multi-source data fusion module integrates power, weather and geographic information, and provides support for decision making through data cleaning and space-time correlation analysis; the intelligent decision-making module generates a multi-target optimization decision by applying an improved multi-target genetic algorithm based on a digital twinborn dynamic plan library and a deep reinforcement learning algorithm; the heterogeneous communication module integrates various communication units, realizes mode dynamic switching and bandwidth aggregation, and ensures stable communication. And the visual command terminal displays the power grid situation and efficiently issues an instruction by means of augmented reality and multi-level authority management. The power grid emergency response and command efficiency is greatly improved, and power supply stability is powerfully guaranteed.

The invention discloses an unmanned aerial vehicle cluster cooperative control system and method, and relates to the technical field of unmanned aerial vehicle cluster control, and the system comprises a multi-source sensing unit, an integrated laser radar, an RGB-D camera and a millimeter wave radar array, and is used for generating a centimeter-level precision three-dimensional map and tracking a dynamic obstacle in real time; the collaborative decision-making unit comprises an artificial intelligence prediction module which is used for predicting a collision point based on the movement state of the obstacle; the safety space construction module is used for generating a dynamic safety sphere according to the formation envelope size and the obstacle volume; the artificial intelligence correction module is used for constructing a safety section and generating an optimization path; and the dynamic communication unit is used for carrying out cluster data interaction by adopting hybrid networking of 5G and LoRa adaptive switching. The unmanned aerial vehicle cluster can be used as a whole to avoid obstacles, the original forms of the unmanned aerial vehicles are synchronously kept, and it is guaranteed that multiple unmanned aerial vehicles in the cluster do not collide.

The invention discloses a fire-fighting early warning system and method based on artificial intelligence, and relates to the technical field of intelligent fire-fighting early warning, and the system comprises an environment sensing module which comprises a multispectral sensor, a temperature sensor, a smoke sensor and a high-definition camera, and is used for collecting fire characteristic spectral data and transmitting the data to a data analysis module; the data analysis module comprises an edge calculation unit and a data fusion unit, and is used for performing feature extraction and anomaly detection on the fire feature spectrum data through a deep learning model to generate a fire risk assessment result; the early warning decision module comprises a risk assessment unit, an early warning grading unit and a communication unit, and is used for determining an early warning grade according to a fire risk assessment result and triggering equipment of the execution feedback module; and the execution feedback module comprises a spraying system, an emergency lighting system and an alarm and is used for executing fire emergency measures according to the instruction of the early warning decision module. According to the invention, comprehensive improvement of fire prevention and control efficiency is realized through cooperative work of multiple modules.

The invention discloses a charging pile dynamic load balancing scheduling system based on reinforcement learning, and the system comprises a data collection module which comprises 5G communication units installed at the charging piles, and is used for obtaining the power of the charging piles, vehicle battery parameters and power grid load data in real time; the reinforcement learning decision module maps the data in the data acquisition module into a state vector through a feature extraction network, and generates a power distribution strategy by adopting a PPO + DQN hybrid algorithm; the communication protocol module realizes state synchronization and control instruction transmission between the charging piles based on an OCPP2.0 standard; the execution control module converts the control instruction into a PWM control signal, and adjusts the output power of each charging pile in real time; through the reinforcement learning decision module, the system can analyze the charging pile power, the vehicle battery parameters and the power grid load data in real time, generate an accurate power distribution strategy, ensure accurate matching of the charging pile power and the electric vehicle demand power, and thus significantly improve the charging efficiency.

The invention relates to the technical field of unmanned aerial vehicle cooperative hoisting, and provides a multi-unmanned aerial vehicle cooperative hoisting system and an unmanned aerial vehicle module, the unmanned aerial vehicle module is composed of two or more unmanned aerial vehicles, and each unmanned aerial vehicle is equipped with an airborne computer, a flight control assembly, a power assembly, a space positioning sensor, a tension sensor and a communication unit; the spatial positioning sensor is used for acquiring spatial position data of the unmanned aerial vehicle; the tension sensor is used for acquiring tension data of goods hoisted by the unmanned aerial vehicles, and the airborne computer is in data connection with a communication unit of the unmanned aerial vehicles and is used for calculating real-time lift force and attitude adjustment amount of the unmanned aerial vehicles based on the tension data and spatial data acquired by the unmanned aerial vehicles and controlling flight parameters of the multiple unmanned aerial vehicles according to the real-time lift force and attitude adjustment amount; according to the invention, through a multi-source fusion positioning and sliding mode adaptive hybrid control algorithm, cooperative positioning and dynamic load balancing of the unmanned aerial vehicle group are realized, and the overall stability and anti-interference capability of the hoisting system under complex disturbance are ensured.

The present invention relates to a computer implemented method for monitoring the blade (210) of a wind turbine (200), the method comprising fixing a sound acquisition device (110) to an outer surface of a tower (220) of the wind turbine (200), wherein the sound acquisition device (110) comprises a microphone, a sound encoder and a communication unit, acquiring a sound sample of sound emitted by the blade (210) during operation of the wind turbine (200), encoding the sound sample into a raw audio file, sending the raw audio file to a remote computing device (120), preprocessing the raw audio file, generating a spectrogram of the pre-processed audio file, detecting an anomaly by applying an image analysis machine learning model to the spectrogram, classifying the anomaly to a damage type by applying a damage type feature analysis machine learning model to frequency domain features of the audio file at the time and frequency of the anomaly, determining a damage location by applying a damage location feature analysis machine learning model to frequency domain features of the audio file at the time and frequency of the, and tracking of a damage severity by extracting audio features of the audio file at the time and frequency of the anomaly indicative of the damage severity depending on the damage type.

The invention relates to the technical field of intelligent power supplies, in particular to an intelligent power supply for an unattended station. Comprising a multi-source power supply scheduling unit; an intelligent energy storage management unit; a double-link communication unit; the double-link communication unit is used for constructing a multi-redundancy communication link of wired, wireless and power line carriers, and the double-link communication unit is based on link quality data, adopts an automatic switching strategy to guarantee data transmission continuity, preprocesses monitoring data by using an edge side data clustering algorithm, and realizes offline data caching and transmission flow optimization. Through a multi-source energy dynamic scheduling strategy, according to photovoltaic real-time output, commercial power time-of-use electricity price and load electricity demand, power supply paths of photovoltaic, commercial power and a storage battery can be dynamically optimized, the consumption proportion of clean energy is improved, the dependency degree of high-cost commercial power is reduced, a complex energy structure of photovoltaic, commercial power and storage battery multi-energy complementation is effectively adapted, and the energy utilization rate is improved. And power supply flexibility is enhanced.

The invention relates to the technical field of solar panel maintenance, in particular to a photovoltaic power station solar cell panel intelligent flushing system, which comprises an image analysis module, an intelligent control module, an image processing module, a data processing module, a data processing module, a data processing module, a data processing module and a data processing module, and is characterized in that the image analysis module is used for monitoring smudginess data of the surface of a solar cell panel and transmitting the smudginess data to the intelligent control module in real time; the multispectral camera collects surface images of a current cell panel and a next cell panel, the surface images comprise cell panel surface images collected under different spectral bands or angles, and smudginess distribution and smudginess degree of the next cell panel are obtained; a cleaning strategy is generated according to the cleaning requirement through a preset intelligent algorithm, a control instruction is output and sent to the intelligent control module through the communication unit, and the intelligent control module adjusts the working state of the flushing device. According to the system, the precise recognition capability of the system on the dirty area is improved, it is ensured that water flow can effectively cover the part needing to be cleaned in the cleaning process, and waste of the non-dirty area is avoided.

The invention discloses an air-ground cooperation system and an air-ground cooperation method based on intelligence, and relates to the field of intelligent unmanned system control. The system comprises an intelligent unit, a multi-element sensing unit, a communication unit and a task execution unit. Based on a Vision-Language-Action (VLA) framework, an intelligent unit with a body realizes end-to-end analysis of a natural language instruction and a visual instruction, fuses sensing data of an unmanned aerial vehicle and an unmanned vehicle, generates a joint feature code with time-space alignment, and dynamically allocates a cooperative task. The communication unit supports low-delay end-to-end communication and real-time data synchronization between clusters, and ensures efficient interaction between agents. The multi-element sensing unit is integrated with a visual camera, a laser radar and high-precision positioning equipment, and air-ground environment multi-mode sensing is achieved. And the task execution unit supports the unmanned aerial vehicle to complete coordination actions in a complex scene. According to the scheme, the problems of insufficient multi-mode perception, limited natural language interaction and low dynamic cooperation efficiency of the existing system are solved, and the cooperation capability and system robustness of the unmanned aerial vehicle and the unmanned aerial vehicle in a complex environment are remarkably improved.

A communications system for a restaurant includes multiple field communications units, a portable communications device, and processing circuitry. The field communications units include a speaker and a microphone. The portable communications device is transportable by an order taker of the restaurant. The processing circuitry obtains a user input to transition the portable communications device between multiple different channels. The multiple different channels correspond to one of the multiple field communications units. The processing circuitry transitions the portable communications device to one of the multiple different channels according to the user input. The processing circuitry facilitates end-to-end bi-directional audio communication between the order taker and a customer by operating the portable communications device and the one of the multiple field communications units to exchange audio data over the one of the multiple different channels.

The invention relates to the technical field of intelligent power grids, and provides an intelligent terminal supporting multi-parameter fusion perception, which comprises a data acquisition module for acquiring parameters of a transformer body and parameters of a far-end intelligent electric meter through multiple types of sensors; the data processing module is used for executing a dynamic window cleaning algorithm on the collected data, and the data fusion module is used for outputting power grid state characteristics by adopting a fixed weight and dynamic weight dual-mode fusion mechanism; a multi-mode wireless communication unit is arranged in the communication module, and the communication module uploads the fused data and the early warning information to a cloud master station platform; according to the method, the defects in the prior art are overcome, a sliding window self-adaptive adjustment mechanism is established, and the window length is automatically adjusted and calculated by analyzing data distribution characteristics in real time; when abnormal fluctuation is detected, the window is contracted to improve the sensitivity, and the window is expanded to enhance the immunity under a steady-state working condition.

The invention relates to the technical field of agricultural intelligent irrigation, in particular to an intelligent irrigation control system and method based on meteorological environment acquisition, and the system comprises a sensing layer, a transmission layer, a control layer, a cloud layer and an execution layer. Then meteorological environment data collected by the sensing layer is transmitted to the control layer through a wireless transmitting module and a wireless receiving module, and a controller of the control layer is integrated with an edge computing unit, a communication unit and a decision-making unit; the problems that an existing agricultural meteorological monitoring and irrigation control system is high in network transmission load coefficient, and the edge computing capability of sensor nodes cannot be effectively utilized; the problem that an irrigation control algorithm based on a static threshold mechanism or a single statistical model lacks adaptive processing of rainfall time sequence prediction and dynamic response ability of specific requirements of crop growth stages is solved.

The invention relates to the technical field of street lamps, and provides a solar street lamp fault self-inspection and cloud alarm system, which comprises a cloud control platform and a local module, and is characterized in that the local module comprises a wireless communication unit, a data processing unit with a built-in dynamic decision algorithm, a data acquisition unit and an execution unit; the method comprises the following steps: periodically collecting real-time operation data and real-time environment data of the solar street lamp; outputting a fault type code and an emergency disposal instruction through the fault classification decision tree model; sending alarm information to the cloud control platform; the execution unit executes the emergency disposal instruction. According to the method, the dynamic threshold value interval is generated through the dynamic threshold value adjustment algorithm, the influence of dynamic environment parameters such as illumination intensity and temperature on the running state of the solar street lamp is fully considered, misjudgment caused by fixed threshold value judgment is avoided, the system false alarm rate is greatly reduced, and unnecessary manual troubleshooting cost is reduced.

The invention relates to the technical field of underwater communication and positioning, in particular to a multi-mode underwater wireless communication system based on dynamic link calibration, which integrates underwater acoustic positioning guide, attitude adaptive tracking control, optical link enhancement and an error code correction mechanism. Comprising a central control core, an acoustic communication unit, an optical communication transmitting unit, an optical signal receiving unit, an optical control unit, a multi-axis attitude adjusting unit, a data fusion and verification processing unit and a high-speed modulation-demodulation and error code correction unit. And by using a double-shaft servo motor and automatic gain control, real-time target tracking and accurate alignment of optical signals are realized, FPGA and OFDM modulation are combined to optimize data throughput, and a data cross validation mechanism is introduced to correct error codes, so that the data integrity is improved.

The invention relates to the field of forestry pest prevention and control, and discloses a juglans sigillata forest intelligent pest prevention and control system and method.The juglans sigillata forest intelligent pest prevention and control system comprises a data acquisition module used for collecting basic information of a juglans sigillata forest, and the basic information comprises meteorological environment parameters, soil physical and chemical properties and in-forest visual image data; the identification and analysis module is used for deeply analyzing data characteristics of the basic information, discriminating types and severity of diseases and pests, predicting potential occurrence risks of the diseases and pests and forming an evaluation result; and the early warning response module is used for presetting a risk level threshold value and rule logic and generating an early warning signal of a corresponding level according to an evaluation result. A data acquisition module integrating multiple types of monitoring units and communication units is constructed, so that the juglans sigillata forest can be sensed in all directions, the limitation of manual inspection is eliminated, and the problems of inaccurate monitoring and difficulty in data backtracking are solved; and the identification analysis module comprises sample management, model training and data analysis and prediction.

The invention relates to a pressure sensor (1) for detecting a leakage in a first separating membrane (8), with - a process adapter (6) with a membrane system (7) comprising the first separation membrane (8) and a second separation membrane (9), which are arranged such that the first separation membrane (8) faces the medium (24) and the second separation membrane (9) faces away from the medium (24) and a first intermediate space (10) is enclosed between the first separation membrane (8) and the second separation membrane (9), which has a vacuum, - a sensor unit (14) with a carrier (15), a second pressure sensor (16) and a communication unit (17), wherein the sensor unit (14) is attached to the pressure sensor (1) in a pressure-tight manner by means of the carrier (15) and is arranged such that the second pressure sensor (16) monitors the vacuum in the first space (10), wherein the second pressure sensor (16) and the communication unit (17) are electrically connected to each other and are arranged on a surface of the carrier (15) facing the vacuum.

The invention relates to the technical field of power systems, and discloses a voltage regulation system of reactive power compensation equipment, which is characterized in that harmonic interference is filtered and eliminated through a voltage reactive power sensing unit, and accurate power grid parameters are acquired; a load trend pre-judgment unit analyzes the historical load curve and the real-time change trend to generate a future pre-judgment signal; the dynamic compensation calculation unit combines the current power grid state with the prediction to calculate the optimal compensation capacity and generate a switching instruction, after the hybrid switching actuator receives the instruction, a thyristor is triggered firstly to realize inrush current-free conduction, a contactor is switched to maintain low power consumption after the current is stable, and meanwhile, the compensation state monitoring unit performs closed-loop adjustment on parameter deviation, so that the optimal compensation capacity is obtained. The multi-dimensional protection unit prevents overvoltage, overcurrent and overheating, the double-path power supply guarantees continuous operation when the main power supply is abnormal, the intelligent communication unit realizes data uploading and remote cooperation, quick response switching of reactive compensation equipment and guarantee of safety of a large-scale power grid are realized, and inrush current impact in the switching process is effectively inhibited.

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.

The invention relates to the technical field of construction intelligent monitoring, in particular to a building construction remote intelligent monitoring system based on 5G telephone communication and edge computing. Comprising an on-site sensing unit; the edge processing unit is used for realizing accurate integration of heterogeneous data through an improved self-adaptive weighted fusion algorithm and generating a real-time control strategy in combination with a working condition dynamic model; the 5G communication unit is combined with predictive slice scheduling and a multi-mode anti-interference protocol; and a remote monitoring unit. The industrial-grade sensor array is adopted to collect related data, a monitoring data stream with a timestamp and marked with an abnormal identifier is generated, meanwhile, an edge processing unit complements abnormal data through a data preprocessing module, heterogeneous data integration is achieved through an improved self-adaptive weighted fusion algorithm, and the data processing efficiency is improved. According to the method, the problems that the data processing architecture and the construction multi-source data characteristics are insufficient in adaptation and data validity tracing is missing are effectively solved, and effective tracing and accurate integration of the construction scene multi-dimensional monitoring data are achieved.

The invention relates to the technical field of geotechnical engineering and intelligent monitoring, and discloses an assembly type anti-slide pile service safety digital twinborn early warning system which comprises a sensing module used for collecting physical parameters of an anti-slide pile in real time and comprising a sensor array and a distributed optical fiber temperature measuring device; the transmission module is connected with the sensing module, is used for receiving and preprocessing the sensor data, and comprises a wireless communication unit and an edge computing unit; the digital twin module is connected with the transmission module, is used for constructing a pile-soil coupling dynamic model and updating the pile-soil coupling dynamic model in real time, and comprises a cloud numerical simulation engine and a three-dimensional visualization unit; and the early warning decision module is connected with the digital twinning module, is used for outputting and triggering a grading response mechanism according to the model, and comprises a risk judgment unit and a processing strategy library. According to the invention, the real-time monitoring and intelligent early warning of the health state of the slide-resistant pile in the whole life cycle are realized by combining the Internet of Things sensor, edge calculation, three-dimensional modeling and big data analysis technologies.

The invention relates to a crawler-type magnetic adsorption wall-climbing robot, and belongs to the field of wall-climbing robots. The wall-climbing robot comprises a main body bracket, a control module, a driving module, an adsorption module and a mechanical arm module, the main body support is a frame of a hollow structure and comprises a bottom plate, side plates arranged on the two sides of a chassis and a cover plate connected with the tops of the side plates, and a power source is arranged in the main body support. The control module is arranged in the main body bracket and is electrically connected with a power supply, and the control module comprises a wireless communication unit. The robot is simple in structure and high in obstacle crossing capacity, permanent magnet magnetic poles are arranged in a Halbach array, the upper sides and the lower sides of the magnetic poles are in an upper strong magnetic state and a lower weak magnetic state, and the magnetic adsorption force to the wall face is greatly improved.

The invention relates to medical instruments, in particular to a peritoneal dialysis device which comprises a dialysate management unit, a sensor unit, a processor, a storage device, a peritoneal transfer model, an intelligent alarm management unit and a communication unit, and the dialysate management unit is configured to be used for perfusion of dialysate into the abdominal cavity of a patient and drainage of the dialysate from the abdominal cavity of the patient; the sensor unit is configured to be used for monitoring physiological parameters of a patient and dialysate characteristic parameters and receiving symptom information and comfort level scores input by the patient, the storage stores instructions executed by the processor, and the instructions enable the processor to be capable of dynamically adjusting treatment parameters of the dialysate management unit in real time in combination with a pre-trained peritoneal transfer model. The perfusion speed, the drainage speed or the dialysate temperature of the dialysate management unit are dynamically adjusted, so that the comfort level score of the patient is maintained to be above a preset threshold value, treatment parameters can be dynamically adjusted in real time to optimize the treatment effect, peritonitis risks are early warned, and the comfort level of the patient is improved.

The invention discloses an ultrasonic water meter detection device and method, and relates to the technical field of ultrasonic flow metering, the device comprises an ultrasonic detection unit, a block chain evidence storage unit, a zero-knowledge proof module, a master control MCU and a low-power-consumption communication unit, the ultrasonic detection unit collects downstream and countercurrent ultrasonic propagation time difference delta t through symmetrically installed transducers, a time difference measurement module (precision + / -1ns) is combined with water temperature data to calibrate a delta t value, the block chain evidence storage unit constructs a Merkel tree for a delta t sequence according to a time window, and root hash is written into a private chain by improving a PBFT consensus mechanism (threshold 4 / 5 node confirmation). The method covers the whole process of data collection, evidence storage, verification and auditing, solves the problems that traditional water meter data is easy to tamper, privacy is leaked and installation is limited through a hash chain and zero-knowledge proof technology, and is suitable for an intelligent water affair scene.

A position determination device, which determines a position of a portable device relative to a vehicle, includes a first communication unit performing Bluetooth (registered trademark) communication with the portable device and a computer executing a process for determining the position of the portable device. The first communication unit transmits and receives (i) a modulation signal for data communication and (ii) continuous wave signals for distance measurement purpose. The first communication unit maintains a communicable state with the portable device even while the computer operates in a power saving mode. The first communication unit executes a process of calculating a distance from the first communication unit to the portable device using data related to reception phases of the continuous wave signals transmitted from the portable device, compares the calculated distance with a predetermined value, and switches from the power saving mode to a normal mode based on comparison result.

The invention relates to the technical field of automatic monitoring, in particular to a multi-sensor fusion automatic monitoring system and method based on Beidou positioning, and the system comprises an anti-interference and environment adaptation module which comprises a Beidou positioning module, a multi-sensor fusion unit and a data processing and communication unit, the Beidou positioning module is connected with the data processing and communication unit, and the multi-sensor fusion unit is connected with the anti-interference and environment adaptation module; the multi-sensor fusion unit is connected with the data processing and communication unit and used for collecting positioning signals, the multi-sensor fusion unit is connected with the data processing and communication unit and used for providing auxiliary monitoring data, and the control center analysis unit receives real-time data through the data processing and communication unit and is used for monitoring analysis and early warning. Therefore, the problems of easy signal shielding, precision fluctuation and data interruption of single Beidou positioning in a complex environment, insufficient three-dimensional monitoring precision and poor anti-interference and wide-temperature stability caused by lack of hard-soft cooperation in multi-sensor fusion, and high false and missing report rate caused by fixed early warning threshold are solved.

A wireless relay device includes: a communication unit that receives signaling including control information related to a relay function from a base station; a control unit that controls the relay function based on the control information; and a relay unit that executes the relay function of receiving a first signal from the base station, transmitting the first signal to a terminal, receiving a second signal from the terminal, and transmitting the second signal to the base station, in which the control unit enables or disables transmission and reception of the first signal and transmission and reception of the second signal based on the control information.

The invention provides a parallel optimization method and system for a GPGPU (General Purpose Graphics Processing Unit) instruction execution stage, and the method comprises the steps: splitting an input instruction into a plurality of sub-instructions which can be independently scheduled based on an instruction type, operand dependency analysis and a hardware resource real-time state, and generating a dependency table to record the input and output association of the sub-instructions; acquiring real-time load data of the calculation unit, the storage unit and the communication unit, and distributing the sub-instructions to the calculation unit, the storage unit or the communication unit by adopting a priority dynamic adjustment algorithm and combining instruction key path analysis; according to the dependency relationship of the sub-instructions and the availability of hardware resources, the execution sequence of the sub-instructions is adjusted to maximize the degree of parallelism; and analyzing the dependency relationship among the sub-instructions in real time to maximize the degree of parallelism to dynamically adjust a parallel execution strategy so as to realize serial execution of dependent instructions and parallel execution of non-dependent instructions. According to the method, the complexity of instruction compiling is reduced, the efficiency of instruction compiling is improved, and meanwhile extra consumed time is reduced.