62 results about "Border crossing" patented technology

The invention discloses a firmware-level security protection system and method for a hard disk of industrial automation equipment, particularly relates to the technical field of storage security protection, and is used for solving the problem of abnormal tampering of firmware. According to the method, instruction calling, interface access and interrupt timestamps are collected in a sliding window, a behavior sequence set containing an instruction sequence, calling frequency and sensitive marks is constructed and compared with a reference sequence library, firmware-level judgment on operation abnormity, access border crossing and tampering risks is triggered based on a transfer relation and an offset index, and the operation safety is improved. The method comprises the following steps of: dividing firmware into a control domain, a data domain and a configuration domain, realizing minimum permission and dynamic isolation by relying on state and permission mapping and permission register and interface shielding, forming a flow from detection to isolation to closed loop recovery by combining protected segment integrity verification and local copy hot switching, writing an exception into a protected loop log area for threshold updating, and performing protection on the protected loop log area. And the tamper-proof performance, the operation safety and the maintainability of the firmware are integrally improved.

The invention relates to the technical field of power distribution network power supply, and discloses a power distribution network power supply system based on time domain control, comprising a unified time service synchronization module used for establishing a unified time service link and keeping node time synchronization; the time domain acquisition and judgment module is used for acquiring a zero-crossover timestamp and voltage and current samples and determining candidate target moments and execution modes; the instruction generation and calculation module is used for calculating a zero-crossing time difference and an instantaneous voltage difference and generating a time domain action instruction set; the starting advance locking module is used for determining and locking starting advance; the instruction rechecking judgment module is used for rechecking the effectiveness of the instruction set; the action execution checking module is used for completing loop closing or loop opening at a candidate target moment and judging a border crossing state; and the time difference updating and correcting module is used for calculating a time deviation value and updating control parameters. According to the invention, high-precision time synchronization, dynamic self-calibration and action safety coordination control of the loop closing and opening process of the power distribution network are realized.

The invention relates to the technical field of chip packaging, in particular to a PCIe (peripheral component interface express) equipment function number border crossing prevention method supporting ARI (automatic repeat interface). The hardware layer protection process is as follows: S1-1, hot plugging; s1-2, if it is detected that the equipment declarates to support ARI, the PCIe controller hardware circuit immediately sets an equipment number register to zero; s1-3, only allowing the PCIe controller of the system to read the configuration space unidirectionally during the low level period of the reset signal PERST #; the interception process of the driving layer is as follows: S2-1, in an equipment enumeration stage, an operating system drives to dynamically read an ARI capability register; s2-2, if the equipment declarates to support ARI, forcing an equipment number register to be equal to 0, and releasing an original equipment number bit space for function number expansion; s2-3, border crossing access is blocked; and S2-4, synchronizing the state register. Compared with the prior art, correctness of device function numbers is guaranteed through two dimensions of hardware register state solidification and driver layer access truncation, and'perception-free 'fault tolerance of the PCIe device under ARI / traditional mode switching is achieved for the first time.

The invention relates to the technical field of building construction intellectualization, in particular to a building construction intelligent monitoring system based on multi-source sensor data fusion. Comprising a data acquisition and storage unit; a data fusion processing unit; the construction state analysis unit uses an improved anomaly detection algorithm; a risk assessment early warning unit; and a visualization and decision-making unit. Through the dynamic adaptation module, the structural displacement feature weight is adjusted based on the construction stage parameters to preferentially extract the construction key stage structural features, and the structural material elastic deformation limit is corrected in combination with the material linear expansion coefficient and the temperature difference value; meanwhile, the dynamic critical generation module generates a risk critical judgment basis changing along with the construction process in combination with structural bearing capacity parameters and equipment mechanical stress limits in the construction stage, so that the problem that abnormal detection and risk judgment are lack of dynamic adaptability is solved; and the accuracy of personnel border crossing, equipment abnormity and structure abnormity identification and the adaptability of risk assessment are effectively improved.

The invention belongs to the technical field of building progress management, and particularly discloses a multi-modal data-based identification and acquisition method and system, and the method comprises the steps: detecting the process progress deviation of a current working face in a building construction process in real time, and recognizing a cross risk through combining with the subsequent process plan time when the progress deviation exists, therefore, a multi-dimensional rule-driven necessity evaluation mechanism is constructed, quantitative, objective and traceable evaluation on the feasibility of the cross operation is realized, and a feasible time window and a space authorization boundary of the cross operation are defined on the current working face while the cross operation is judged to be necessary. And then, monitoring a motion track of a subsequent process in an authorized area, synchronously predicting completion feasibility of a previous process in a feasible window period, and carrying out space-time two-dimensional compliance judgment, so that real-time perception and risk identification of cross operation are realized by depending on multi-modal data fusion, and anomalies such as border crossing operation or progress lag can be actively discovered. And regulation intervention is triggered in time.

The invention discloses an intelligent low-altitude traffic unmanned aerial vehicle situation awareness method and system. The method comprises the steps of image acquisition, perception enhancement border crossing sample generation, boundary distance analysis feature extraction unit design, dynamic cross-specification air situation fusion, airspace anti-change loss calibration, unmanned aerial vehicle situation awareness model design and low-altitude traffic unmanned aerial vehicle situation awareness. The invention belongs to the field of image processing, and particularly relates to an intelligent low-altitude traffic unmanned aerial vehicle situation awareness method and system.According to the scheme, texture constraint loss is constructed, and situation misjudgment caused by detail loss is reduced; based on boundary distance analysis operation, separating low-altitude traffic noise and target features; based on height attitude self-adaptive pooling size design, feature mismatching is avoided; introducing a motion speed compensation factor to correct frame offset caused by high-speed flight of the low-altitude unmanned aerial vehicle; a dynamic noise suppression coefficient is introduced to suppress harmful gradient interference; and the low-altitude traffic unmanned aerial vehicle situation awareness effect is further improved.

The invention provides a dredger sensor health state diagnosis method and system, and belongs to the technical field of ship equipment health management.The dredger sensor health state diagnosis method comprises the following steps that N recent continuous sampling points are selected, a data mean value and a standard deviation in a sliding window are calculated, and a threshold confidence interval is defined; if the current sampling value continuously falls into the threshold confidence interval for M times; data such as mud pump power, mud density, pressure and flow velocity are collected in real time through the data collection unit, the mean value and the standard deviation are analyzed and calculated through the signal preprocessing unit, and then the fault type is judged in combination with the dynamic threshold value adaptation module, the soil texture classification strategy module and the redundancy check module. Alarm signals such as disconnection, water inflow and border crossing are triggered according to priorities through an alarm output unit, and the problems of mismatching of static thresholds, poor soil adaptability, high false alarm rate and the like in the prior art are solved by utilizing dynamic threshold adjustment, multi-dimensional data fusion and redundancy check mechanisms.

The invention discloses an automobile border crossing tolerance alarm method and system for a fixed operation line. The method comprises the following steps: generating a dynamic buffer area based on vehicle basic information, vehicle driving lane information and weather information; when the vehicle is driven into the dynamic buffer area of the lane, acquiring a drift point of a driving historical track of the vehicle on the lane; obtaining a vehicle course angle, and calculating an included angle deviation between a current driving track vector and a road segment vector; and determining an early warning level according to the drift point number and the included angle deviation. The real intention of the vehicle is deduced by analyzing the deviation between the vehicle course angle and the road direction and the historical track drift point, and the real risk is accurately captured.

The invention discloses a foundation pit monitoring self-adaptive regulation and control method based on reinforcement learning, and aims to solve the problems that safety constraints are difficult to meet continuously under complex working conditions and disturbances, and'controllability and no boundary crossing 'are difficult to guarantee. The foundation pit monitoring self-adaptive regulation and control method comprises the following steps: constructing a monitoring-prediction-check-projection-execution-learning closed loop taking safety embedding as a unified drive; according to the method, multi-source data and partition state estimation are fused, and distributed risk actor-commentator, physical constraint nerve prediction and adaptive confidence calibration, model prediction safety filtering and micro quadratic programming projection are adopted; the technical effects of real-time self-adaptive regulation and control within the standard limit value and the dynamic safety margin, reduction of the border crossing risk and improvement of the stability and the reliability are achieved.

The invention discloses a pipe-jacking construction safety risk intelligent assessment method based on multi-source data fusion, and relates to the technical field of pipe-jacking construction, and the method comprises the steps: obtaining historical monitoring data of pipe-jacking construction, including geological radar images, engineering operation parameters and structural deformation parameters; establishing a construction topology network based on the historical monitoring data, identifying risk driving factors in combination with a preset GAM model, and automatically adjusting the monitoring data acquisition frequency; a machine learning model is introduced, iterative training is performed on each batch of monitoring data, and abnormal fluctuation of structural deformation parameters is evaluated so as to identify the risk degree of geological mutation; wherein the risk degree comprises a valid risk and an invalid risk; based on the construction topology network, in combination with the effective risk, executing an operation safety strategy, and judging a border crossing behavior; according to the method, accurate association of node links is realized, monitoring pertinence is improved, multi-source data fusion is refined to a certain extent, and judgment of risk core sources and timely early warning are facilitated.

The invention discloses an unmanned aerial vehicle self-destruction measure ground verification method and system. The method comprises the following steps: configuring an instruction self-destruction measure and an autonomous self-destruction measure on the unmanned aerial vehicle; setting a safe airspace for testing on the ground; injecting boundary information of the safe airspace into a flight control system of the unmanned aerial vehicle; a GNSS transponder is used for providing simulated satellite positioning signals for the unmanned aerial vehicle, and the GNSS transponder comprises an outdoor antenna, an indoor antenna and a host; dynamically simulating the position change of the unmanned aerial vehicle relative to the safe airspace by moving the outdoor antenna so as to construct a test scene in which the unmanned aerial vehicle crosses the safe airspace; and based on the test scene, respectively carrying out ground verification on the function validity of the instruction self-destruction measure and the autonomous self-destruction measure. According to the invention, an airplane border crossing scene is dynamically simulated through the movable GNSS transponder, comprehensive, convenient and safe ground verification of instruction self-destruction and autonomous self-destruction measures under multiple working conditions is realized, and the self-destruction reliability is guaranteed.

The invention discloses a personnel activity control and regional safety prevention and control system and method based on a fusion positioning technology, and relates to the technical field of personnel monitoring. A positioning sensing module is fused with the positioning technology to obtain positioning data and preprocess the positioning data; the GIS fusion module dynamically divides an early warning area and maps positioning data to an electronic map; the intelligent analysis module monitors the spatial relationship between the personnel and the early warning area, and when an early warning condition is met, early warning is triggered and a border crossing event list is generated; the linkage execution module receives the early warning signal and is linked with a camera, an entrance guard and an alarm device in a corresponding early warning area; and the visual echo module is used for displaying the electronic map, the early warning area, the personnel track, the event list and the video information. The method improves the positioning precision, flexibly and dynamically divides and manages areas, carries out border crossing detection and exemption rules in combination with a plurality of judgment mechanisms to realize precise prevention and control, is linked with security equipment, enhances the cooperative prevention and control capability, and reduces the cost.

Provided is a system and method for de-personalized security data file sharing using passenger list information messages, the method including: obtaining from an electronic passenger list information message, passenger data for passengers, the passenger data including a unique passenger identifier (UPID) assigned by a Departure Control System (DCS) of an originating airline for each of the plurality of passengers; and, for each of the passengers: depersonalizing the passenger data; retrieving a security screening image (SSI) representative of contents of the luggage item; converting the SSI and the UPID into SSI file sharing data for a security screening tool; transmitting the SSI file sharing data to a secure system associated with a border crossing airport to be used in a security screening process on the checked-in luggage item using the security screening tool; receiving a first screening message with a result of the screening process; and causing the result to be displayed, wherein the result includes one of: a first result representative of cleared security screening; or a second result representative of failed security screening, wherein one or more of the passenger or the checked-in luggage item that failed the security screening are flagged for further security inspection.

The invention relates to the technical field of AI-based central air-conditioning system energy-saving optimization, and discloses an AI-based central air-conditioning system energy-saving optimization simulation platform. Setting a unified sampling period, reading rated temperature difference, temperature and heat exchange amount sensor resolution and maximum heat exchange amount from a specification, initializing thermal resistance and thermal capacity double-exponential smoothing parameters, and setting non-zero protection; the condenser temperature, the evaporator temperature and the heat exchange amount are collected in real time, and abnormity is eliminated through border crossing and lower limit verification; calculating a temperature difference and a first-order change rate thereof, and estimating instantaneous thermal resistance and thermal capacity according to the temperature difference and the first-order change rate; a smoothing coefficient is adaptively generated based on the continuous period parameter difference value, and double-exponential smoothing iteration updating is adopted; performing physical correction on the smoothed parameters and storing history in a rolling manner to ensure that the result is reliable; and finally, recommended heat exchange amount is calculated and subjected to range correction on the basis of the newest smooth thermal resistance and serves as closed-loop control reference of refrigerant flow or compressor load in the next period.

The invention relates to the technical field of vehicle monitoring and scheduling, in particular to a vehicle dynamic scheduling and compliance monitoring system and method based on an electronic fence, and the system comprises a dynamic scheduling information access module, a dynamic electronic fence engine, a judgment early warning module, a visual output terminal and a data storage and learning module. The method is characterized in that a temporary task electronic fence with a life cycle and reasonable path authorization is dynamically generated for a controlled vehicle by acquiring scheduling information in real time, and the temporary task electronic fence and a basic static fence form a multi-layer fence logic. And the judgment and early warning module combines the real-time position of the vehicle and the scheduling context to carry out scenario research and judgment, so that reasonable border crossing and illegal behaviors are effectively distinguished, and the false alarm rate is greatly reduced. Meanwhile, the system continuously optimizes fence parameters and rules through learning. According to the invention, the problems of poor applicability and high false alarm rate of a fixed electronic fence in a dynamic scheduling scene are solved, the balance between supervision rigidity and business elasticity is realized, and the intelligent and precise level of vehicle monitoring is improved.

This application provides a method, apparatus, and equipment for the collaborative control of mixed-load truck platoons, applicable to business scenarios such as ports, border crossings, road freight, urban delivery, mining, and airports. The method includes: acquiring the real-time load mass of each vehicle in the platoon and constructing a vehicle energy consumption model incorporating kinetic energy recovery; dynamically determining the optimal lead vehicle based on this energy consumption model and forward-looking road gradient information, with the goal of minimizing the overall energy consumption of the platoon; and finally, generating and executing an energy-saving control strategy before the platoon reaches the slope, instructing the platoon to complete the collaborative driving configuration switch. This invention achieves refined and adaptive energy-saving control of truck platoons under real-world complex road conditions by integrating load, gradient, and kinetic energy recovery factors.

The invention discloses a production quality management and control method and system for automobile parts, and relates to the technical field of automation control, and the method comprises the steps: binding a unique identifier of a part, collecting multi-source process data, screening a reference sample set, and obtaining a reference parameter set; the method comprises the following steps: collecting actual measurement data of a current part, calculating a joint border crossing index, judging the quality state of the part, identifying an abnormal cluster, executing targeted fine tuning, and generating a statistical tetrad and a candidate process parameter set; obtaining a standardized statistical index set, and preferentially determining an optimal control instruction through a lexicographical order; and receiving an optimal control instruction, arranging the optimal control instruction to take effect, performing feed-forward robust judgment, performing computer execution and online monitoring, generating a disposal decision, solidifying an effective control instruction, and updating a reference parameter set. And the adaptability of the control strategy is enhanced, and continuous optimization and accurate control of the production process are realized.

The invention provides a bastion host operation instruction border crossing behavior identification and control method, which comprises the following steps of: extracting an input value of a current operation instruction and a security boundary value preset by a system through a bastion host operation log, and synchronously acquiring a CPU occupancy rate, a memory usage amount and a running task number of a target host; analyzing the incidence relation among the CPU occupancy rate, the memory usage amount and the number of running tasks according to the host resource state data and the task load data, and identifying whether the host is in a light-load running state or a heavy-load running state currently to obtain a host load level; and according to the operation instruction input value, the security boundary value and the host load level, calculating the deviation degree of the operation instruction input value and the security boundary by adopting a dynamic risk quantification algorithm, and adjusting a risk weight coefficient in combination with the host load level to obtain a boundary crossing risk level.

The invention belongs to the technical field of monitoring, and particularly relates to a solar power supply edge calculation monitoring device for highway equipment, which comprises a solar cell panel, a power management module and a storage battery, and is characterized in that the solar cell panel supplies power to the storage battery and an edge calculation load through the power management module; the high-definition camera is used for collecting a monitoring picture of a highway construction area; the edge calculation unit is configured to perform image preprocessing on the monitoring picture and generate border crossing event elements and illegal parking event elements based on a multi-exit Anchor-free target detection network; the 4G or 5G wireless communication module is used for sending comprehensive alarm data obtained by packaging the border crossing event elements and the illegal parking event elements to the management center platform; and the local alarm unit is connected with the edge calculation unit and is used for carrying out audible and visual alarm based on the comprehensive alarm data. According to the invention, through an edge calculation mechanism capable of adaptively selecting a reasoning outlet, the detection speed and the recognition stability in a complex environment can be improved.

The invention discloses a passenger unsafe behavior recognition device and method for a special equipment scene, and relates to the technical field of special equipment safety monitoring. The device comprises a sensing unit, a data transmission unit, a data processing unit and a man-machine interaction unit. Passenger videos and equipment data are collected through the sensing unit, key points of passengers are extracted through a YOLOv11 posture estimation model in the data processing unit, and five unsafe behaviors including falling, squatting, backward walking, border crossing and overcrowding are accurately recognized in combination with behavior judgment logic customized for special equipment scenes. An identification result is displayed in real time through the man-machine interaction unit and is fed back to the special equipment control system through the data transmission unit, and closed-loop safety control of perception-analysis-decision-execution is formed. According to the invention, the problems of low identification precision, poor scene adaptability and lack of real-time linkage capability in the prior art are solved, and the safety and intelligent level of operation of the special equipment are remarkably improved.

The invention belongs to the technical field of grazing, and particularly discloses a real-time grazing livestock behavior monitoring device based on Beidou navigation positioning, which comprises an arc-shaped strip, a positioner and a contraction band, one end of the arc-shaped strip is connected with a positioner, a GPS positioning unit is arranged in the positioner and used for transmitting position data to the cloud end, the other end of the arc-shaped strip is inserted into the positioner through an insertion part, a round block is arranged on the surface of the arc-shaped strip, and a through groove is formed between the round block and the arc-shaped strip. According to the invention, through cooperation of the plug-in component and the slot, the ferrule can be conveniently sleeved on the neck of the livestock, position data is transmitted in real time through the positioner, the device cooperates with a cloud platform, functions of electronic fence triggering, border crossing and retention alarm, track playback and afterward tracing, zoned rotational grazing scheduling, livestock capacity accounting and the like can be realized, the manual inspection cost is reduced, and the working efficiency is improved. And the real-time performance, the reliability and the refinement level of grazing management are improved.

The application belongs to the field of industrial safety monitoring, and discloses a foreign matter border crossing detection method, computer equipment and a storage medium. The method comprises the following steps: acquiring a current video frame; inputting the current video frame into a warning line segmentation model and a foreign matter detection model respectively to determine a binary mask of the current video frame and a dynamic detection frame for foreign matter; determining at least one warning boundary point set of the current video frame based on the binary mask; performing linear regression fitting on each warning boundary point set to obtain a corresponding candidate fitting warning line, and generating a corresponding candidate warning area based on each candidate fitting warning line; selecting a target warning area with the highest overlap degree with a current calibration warning area from each candidate warning area; if the overlap degree is less than a preset threshold, regarding the target warning area as a new calibration warning area; and determining whether there is foreign matter border crossing in the current video frame based on the dynamic detection frame and the new calibration warning area. The application can improve the accuracy of foreign matter border crossing detection.

The invention discloses an industrial big data processing system based on an artificial intelligence algorithm, relates to the technical field of industrial big data and intelligent control, and is used for solving the problems of source aliasing, time sequence gap and unstable judgment in multi-source heterogeneous industrial data containing pseudo-random watermarks and noise. Bit plane chromatography and evidence curved surface imaging are introduced, a watermark effective window is judged in combination with anti-fact replay, a specific vector group is obtained by using coherent weighted robust subspace projection, candidate bit width convergence, boundary persistent window coverage and orthogonal vanishing are completed, and a signal plane and a watermark plane are output in a source separation manner. A historical side establishes an interval according to environment aggregation and a robust extreme value and carries out gray loading, and an online side executes border crossing judgment and alarm suppression; the abnormal identification adopts tolerance consistency and historical similarity to screen and output risk levels and disposal priorities; adjusting and generating, matching and issuing an adjusting quantity according to a change rate, applying a triple safety guardrail and rollback, and writing back a historical closed link according to a result.

The invention belongs to the technical field of natural resource inspection, and particularly relates to a natural resource multi-sensing integrated monitoring method and platform. According to the method, through fusion correction of time synchronization, coordinate unification and historical tracks, the influence of time and coordinate abnormity and accidental positioning deviation on border crossing judgment can be effectively eliminated, so that misinformation and misscheduling are reduced, the self-learning responsibility range is automatically expanded and shrunk according to the space density and the inspection frequency, inspection resources can be concentrated in a high-demand or high-risk area, and the inspection efficiency is improved. Unnecessary repeated inspection on a low-risk area is avoided, manpower and operation cost is reduced, time-space matching and continuity inspection of events and tracks can restore inspection behavior paths and trends before and after the events occur, managers are assisted in judging event properties and responsibility ownership, the treatment pertinence and efficiency are improved, and the management cost is reduced. Through fusion evaluation of three types of risk indexes of space, border crossing and events, grading early warning of the natural resource state is realized.

The invention particularly relates to a frontier defense perception alarm decision-making system based on a multi-mode visual model, which relates to the technical field of frontier defense security, and comprises the following steps: receiving video slices and disposal principle txt data sent by a background processing module, identifying and analyzing target behavior actions in the video slices, judging the alarm type and level in combination with the disposal principle, and sending the alarm type and level to the background processing module; and processing suggestions are generated and fed back to the background processing module. According to the method, the cross-modal understanding capability of the multi-modal visual large model is combined with frontier defense specific scene optimization and thinking chain reasoning mechanisms, so that the accuracy of frontier defense target behavior recognition and alarm judgment is greatly improved; the video is segmented through an adaptive slicing algorithm, the behavior action integrity is ensured, and model input interference is further reduced through format standardization processing; on the basis of fine adjustment of open source models such as qwenVL, a frontier defense scene exclusive data set is fused, and the recognition capability of professional behaviors such as illegal border crossing and suspicious article carrying is enhanced.

The invention provides a method and a system for measuring and calculating a cargo communication volume. The method comprises the following steps: acquiring total freight data of a target area; the total freight data comprises highway freight data and common highway freight data; based on the total freight data, determining the expressway inter-region freight volume ratio of the expressway freight volume in the total expressway freight volume; based on the expressway freight volume and the expressway inter-region freight volume ratio, calculating an initial cargo exchange volume between the target region and other regions; based on the historical transportation data, determining a correction coefficient corresponding to the cargo exchange volume; the correction coefficient is used for representing the transportation characteristics of the transit vehicle in the target area; and according to the correction coefficient, correcting the initial cargo exchange volume to obtain a corrected cargo exchange volume. In the mode, the total cargo exchange amount corresponding to the regional road reflecting the real cargo interaction condition between the regions can be calculated, and the accuracy and reliability of a statistical result are improved.

The invention relates to an online detection method, equipment and system for polyethylene fiber yarns, and belongs to the technical field of intelligent manufacturing of high-performance fibers. The equipment comprises a yarn color detection module, a surface defect detection module, an optical coherence tomography (OCT) module and an ultrasonic diameter detection module, and can perform multi-dimensional detection on appearance and internal structure defects of yarns in the production process. By constructing a process parameter optimization model based on defect indexes and diameter errors, the system can dynamically adjust key process parameters such as the melting temperature, the high shear rate and the cooling rate according to real-time detection data, and closed-loop control is achieved. Process parameter updating adopts joint optimization of a sensitivity matrix and a weight matrix, and a parameter constraint mechanism is arranged to prevent border crossing and system oscillation. The whole system can improve the quality consistency and manufacturing stability of polyethylene fiber yarns, and is suitable for continuous and intelligent production scenes.

The invention relates to a memory border crossing detection method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a first processor, and comprises the following steps: performing instruction analysis on a first heterogeneous program to obtain a reference memory address corresponding to a read-write instruction in the first heterogeneous program; acquiring an actual memory address corresponding to the read-write instruction in a process that a second processor runs the first heterogeneous program; and according to the reference memory address and the actual memory address, determining whether memory crossing exists in the first heterogeneous program. By adopting the method, the memory crossing of the heterogeneous program running on the heterogeneous chip can be effectively detected.

The application discloses an AI human body sensor integrating security, care and linkage functions, comprising: a radar module for emitting radar signals and receiving reflected signals to obtain signal collection information; a security module for configuring a security strategy, wherein the security strategy is used for detecting illegal intrusion and border crossing behavior based on the signal collection information and triggering a first alarm mechanism; a care module for configuring a care strategy, wherein the care strategy is used for detecting the activity state of a person under care based on the signal collection information and triggering a second alarm mechanism; a linkage module for constructing a monitoring scene based on security information transmitted by the security module and care information transmitted by the care module, determining a linkage strategy based on the monitoring scene, and sending the linkage strategy to corresponding execution equipment; and a power module. The AI human body sensor realizes high-precision human body detection under the premise of protecting privacy, integrates security and care functions, reduces false positives and false negatives, constructs a multi-scene linkage mechanism, and realizes device collaborative response.

The utility model relates to the technical field of monitoring alarm, in particular to a power van alarm device, which is used for displaying the running condition of a power van and comprises a main body, an adjusting module, an alarm module, a fence module and a control module, the adjusting module is arranged at the bottom of the body and used for supporting the body and adjusting the angle or direction of the body. The alarm module is arranged on the top of the body. The fence modules are arranged on two sides of the body; the control module is arranged in the main body and is electrically connected with the alarm module, the fence module and the power supply vehicle; the fence module monitors object border crossing information through infrared rays. The alarm module and the fence module are adopted, light rays of different colors are matched with buzzing, the running state of the power van and the invasion situation of surrounding objects are monitored and displayed, and it is guaranteed that an operator can receive signals at a distance or a near position. And an adjusting module is arranged, so that the power van alarm device can adapt to emergencies and can be used in different environments.