15771results about "Particular environment based services" patented technology

The invention provides a Beidou electric power data intelligent acquisition and dynamic communication scheduling method and system. The method comprises the steps that a master station constructs a database and trains a data priority classification model, a channel quality prediction model and an intelligent compression model; a substation collects power data through an edge calculation unit, constructs a skyline candidate set to perform data screening, and performs intelligent classification marking by using a data priority classification model; performing reliability evaluation on the data stream by using a Gaussian mixture model, selecting a compression strategy according to a reliability score, a data type and a priority, and packaging into a data frame; determining a transmission strategy in combination with a channel quality prediction result and a context-aware intelligent switching protocol, and sending a data frame; the master station receives the data frame, performs integrity verification, decompresses and reconstructs the data frame, and feeds back a communication state for model updating; and monitoring the operation state, performing early warning based on the anomaly detection model, and triggering a self-healing strategy. According to the invention, the Beidou communication resource utilization rate and the system reliability are improved.

The invention discloses a land-sea-air-space holographic sensing and collaborative decision-making system based on multi-mode edge intelligence. The system comprises a sensing layer which is used for carrying out three-dimensional monitoring on a ship driving process, the sea, the sky, a shore base and a space formed by the ship driving process, the sea, the sky, the shore base and the sea, the sky and the shore base; the network layer is used for constructing a global communication basis, preprocessing monitoring data, judging whether the ship has an abnormal condition or not, and realizing data transmission of the ocean, the sky, a shore base and a space formed by the ocean, the sky and the shore base; and the application layer is used for judging whether an abnormal condition exists in the ship driving process or not based on the data of the ocean, the sky, the shore base and the space formed by the ocean, the sky and the shore base transmitted by the network layer, performing collision early warning decision based on the abnormal condition, and performing dynamic channel capacity prediction. And navigation guidance and route tracking in extreme weather are carried out based on environmental risk early warning, underwater obstacle collision is avoided, and early warning information and decision information are fed back to a sensing layer.

The invention belongs to the technical field of traffic optimization, and particularly relates to a traffic optimization method based on a three-layer Stackelberg game, and the method comprises the steps: obtaining mixed traffic data; according to the mixed traffic data, constructing a three-layer Stackelberg game model; an equilibrium solution of the three-layer game model is solved through a deep reinforcement learning algorithm, an SAC algorithm is introduced into an upper layer to generate a global constraint strategy, and a DDPG algorithm is adopted in a lower layer to optimize cooperative driving and safe obstacle avoidance driving behaviors of the intelligent vehicle; according to the global constraint strategy and the intelligent vehicle driving behavior optimization result, the traffic efficiency, safety and energy consumption and carbon emission indexes of the mixed traffic flow are optimized, the traffic state is continuously updated through behavior feedback data of a middle layer and a lower layer, and strategy optimization is carried out in combination with SAC and DDPG models. Therefore, the problems of insufficient dynamic adaptability, low efficiency of main body interaction processing, limitation of a game model and the like in the prior art are solved.

The invention discloses an offshore platform anti-collision device and method based on multi-mode BEV perception, and the device comprises a three-dimensional fusion distance measurement module, a UWB distance measurement module, a ship navigation state monitoring module, a platform marine environment monitoring module, and a central processing unit. The three-dimensional fusion ranging module comprises a holder, a laser radar and a camera, and is used for performing 360-degree three-dimensional scanning on the periphery of the offshore platform; the UWB distance measuring modules are installed on the periphery of a ship and pile legs of an offshore platform. The ship navigation state monitoring module is used for acquiring ship position, navigational speed and course information in real time; the platform marine environment monitoring module collects wind wave data and weather data near the offshore platform and route information of passing ships through network communication. The invention discloses an offshore platform anti-collision device with real-time monitoring and collision risk assessment functions, the anti-collision safety of an offshore platform is improved, and the occurrence rate of collision accidents is reduced.

The invention relates to the technical field of wind power generation, discloses an intelligent safety early warning method for wind power hoisting operation, and aims to solve the technical problems of insufficient perception and lack of data fusion and intelligent analysis decision in existing operation safety management. The method is characterized by comprising the following steps: constructing an intelligent terminal integrated with a UWB / IMU / safety belt / environment sensor; deploying a positioning base station network and a signal relay system; a multi-source data fusion intelligent analysis platform is established, and high-precision positioning, behavior recognition and deep learning risk prediction are achieved; and a closed-loop intelligent decision-making and execution system is constructed, and graded early warning, electronic fence, environment linkage and one-key help calling are realized. According to the method, a traditional experience driving mode is innovated into a data driving mode, the safety level and the operation efficiency of wind power hoisting operation are remarkably improved, and the defects of insufficient perception, information isolation and the like are overcome.

The invention discloses a building facility detection data intelligent analysis and report system and method, and relates to the technical field of building structure health monitoring, and the method comprises the steps: achieving the high-precision data capture in a strong light dust raising environment through a laser radar and a dual-spectrum camera of a multi-mode anti-interference collection module; a millimeter wave radar array and an IMU inertial unit of the high-risk area strengthening module penetrate through severe working conditions to monitor key structure displacement; the credibility management engine is provided with an NFC timestamp chip and a double-chain block chain, and data judicial-level credibility and operation traceability are ensured; through humidity response gel packaging and Peltier semiconductor refrigeration of the self-maintenance sensing network, node environment self-adaption and drift suppression are achieved; and the multi-stage analysis center fuses edge-cloud computing power based on federal learning, generates a dynamic risk map and automatically outputs a compliance report. Accurate and timely reference is provided for operation and maintenance decisions, and the safety management level of building facilities is effectively improved.

The invention discloses an Internet of Vehicles network selection and switching decision system supporting access of multiple operators. According to the method and the device, the timeliness and the continuity of network switching are remarkably improved through prediction and planning in advance. The module depends on a trajectory-network matching prediction sub-module, combines a vehicle navigation trajectory and a global digital twinborn model, identifies a base station coverage area in a future driving path and the network service quality of each operator in advance, and avoids the lag problem that switching is triggered only after signals are weakened in traditional passive switching. The pre-switching resource reservation sub-module further sends a resource request to a target operator base station and confirms reservation before the vehicle enters a new road section, ensures that resources such as bandwidth and time slot required during switching are in place, reduces switching failure or interruption caused by resource competition, avoids common communication interruption after signal sudden drop in traditional switching, and improves the switching efficiency. And continuous transmission of key businesses such as automatic driving control instructions and real-time road conditions is ensured.

The invention discloses a dynamic beam adaptive optimization method for the Internet of Vehicles, and the method comprises the steps: firstly obtaining the current position, speed and driving direction of a vehicle, and carrying out the prediction of a future trajectory through combining historical trajectory information and employing a Kalman filtering technology and the like; and selecting a candidate beam direction from the predefined beam codebook. The system receives channel quality feedback information of a communication link in real time, and dynamically updates a beam forming weight based on an improved recursive least square algorithm. According to the algorithm, a composite adaptive adjustment mechanism of an error size and an error change trend is introduced, a multi-objective optimization function is constructed, and performance indexes such as link quality maximization, interference power minimization and beam switching frequency minimization are effectively balanced in a dynamic environment, so that an optimal beam direction is obtained. Finally, the real-time switching of the antenna array beams is realized through a low-overhead and low-delay control protocol. According to the method, track perception and a self-adaptive feedback mechanism are fused, and good real-time performance, stability and expandability are achieved.

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

The invention relates to the technical field of warehouse-in and warehouse-out management, in particular to a second-hand car warehouse-in and warehouse-out management system and method. The system comprises a vehicle RFID tag module, an intelligent electronic price tag module, a warehouse-in management module, a warehouse-out management module, an inventory monitoring and alarming module, a multi-point RFID positioning network module and an inventory map visualization module, and a unique encrypted RFID tag can be configured for each second-hand vehicle; binding an intelligent electronic price tag for each second-hand vehicle, and receiving verification to generate a verification result; collecting label information when the vehicle enters the parking lot; the label information is verified when the vehicle leaves; receiving the verification result of the intelligent electronic price tag and the vehicle in-library data of the database to lock the position of the abnormal vehicle; dense RFID reader nodes are arranged in the market to collect and output positioning data; and receiving the positioning data and the vehicle state information, generating a real-time inventory distribution map, and providing a scheduling and site planning decision basis for a manager. The scheduling and planning efficiency of managers can be improved.

The invention relates to the technical field of wireless communication, in particular to a production line wireless communication system and method. The system comprises a multi-dimensional feature sensing module, an interference intelligent cognition and decision-making module, a communication opportunity decision-making module and a channel resource arrangement module. An expected action sequence, transient current features and spatial position topology of an interference source are collected through a multi-dimensional feature sensing module, and an interference source multi-dimensional feature set is generated through fusion; the interference intelligent cognition and decision-making module performs space-time spectrum joint modeling of an interference field based on the feature set, generates a workshop electromagnetic environment situation map, constructs a whole network link toughness map in parallel, and generates a conflict-free communication scheduling table through fusion analysis and multi-dimensional cost optimization; the communication opportunity decision module converts the dispatch table into an executable instruction; and the channel resource arrangement module executes the instruction and realizes closed-loop feedback. According to the method, the problem of communication uncertainty caused by industrial electromagnetic interference is solved, and reliable transmission of key services such as automatic guided vehicle scheduling and man-machine interaction is ensured.

The invention discloses a bus and station interactive scheduling method and system based on V2X and deep reinforcement learning decision, a medium and equipment, and the method comprises the steps: collecting bus operation dynamic data, station passenger flow and environment data in real time, and combining V2X network interaction information to construct a full-dimension perception system; a deep reinforcement learning model is adopted for dynamic decision making, intelligent closed-loop control of vehicle scheduling, station service and traffic signal cooperation is achieved, the bus punctuality rate is remarkably increased, the waiting time of passengers is shortened, operation safety is guaranteed through active early warning of abnormal conditions, and intelligent upgrading of a bus system from passive response to active prevention is achieved.

The invention discloses a method and system for cooperatively positioning a vehicle through a door lock, and the method comprises the steps: obtaining and dynamically updating a neighbor door lock list through the detected door lock of the vehicle according to the broadcast and scanning data of a Bluetooth tag on a moving vehicle; according to the periodic detection report of the door locks on the vehicle and the global analysis of the management system, the cooperative timers of the related door locks are synchronized, and timing management for preventing repeated triggering is implemented; according to the response of the obtained neighbor door lock which initiates multicast query after the collaborative timer expires, the door lock which initiates the query verifies whether all responders are in the neighbor list, so as to judge whether the vehicle is stably parked; and according to the vehicle parking information confirmed by the door lock, the management system updates the global state and sends a parking position notification to the owner. According to the embodiment of the invention, accurate and low-misjudgment judgment of the parking state of the vehicle can be realized, and the reliability and real-time performance of vehicle positioning management are improved by means of global state synchronization.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A system for self-executing enhanced interaction with a node-based logistics receptacle. The system includes a wireless accessory sensor node disposed on the node-based logistics receptacle to monitor storage receptacle components of the node-based logistics receptacle to generate sensor data. The system includes a bridge node disposed on the node-based logistics receptacle that uploads information related the sensor data, detects an external device separate from the node-based logistics receptacle, communicates with the external device to establish a smart contract based connection that provides an interaction privilege, interfaces with the external device according to the interaction privilege, and transmits an update message to the backend server that corresponds to at least a portion of the uploaded information related to the sensor data and information related to interfacing with the external device.

A dynamic learning server-based logistics system includes a node-based logistics receptacle operative to receive a delivery item as part of a logistics transaction and also includes a backend server maintaining a management profile related to operation of the node-based logistics receptacle. The node-based logistics receptacle includes a plurality of monitored receptacle components, a wireless accessory sensor node having a plurality of sensors, and a bridge node operative to retrieve event information from the wireless accessory sensor node. The backend server receives the retrieved event information, compares the retrieved event information with the management profile, identifies a threshold change condition from the comparison, dynamically revises the management profile when the threshold change condition is identified, and transmits an adjustment message to the bridge node. The adjustment message is based upon the revised management profile, and the adjustment message initiates a timing change to operation of the bridge node.

The invention discloses a door lock assisted vehicle positioning method and system, and the method comprises the steps: enabling a home door lock to join in a first multicast group used for receiving a final position notice according to the pre-configured vehicle Bluetooth tag ID and multicast group setting, and enabling a unit door lock gateway to join in a second multicast group used for cooperative communication between gateways; according to vehicle Bluetooth signals periodically detected by a unit door lock, a unit door lock gateway connected with the unit door lock carries out local recording and statistics; distinguishing a single-gateway scene from a multi-gateway scene according to an accumulation and time comparison result of the collaborative notification information among the unit door lock gateways, and carrying out final parking position judgment; according to a query request of the owner, unit door lock position information corresponding to the vehicle is read from a home door lock local storage in a near field communication mode. According to the embodiment of the invention, accurate judgment and active notification of the final parking position of the vehicle in the community can be realized, and the problem of vehicle searching by the vehicle owner is effectively solved.

The invention provides a dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, and belongs to the technical field of wireless communication and unmanned aerial vehicle cooperative control. The system is composed of two unmanned aerial vehicles, serves as a mobile base station to provide relay communication for users, and cooperatively perceives an aerial target. The method comprises the following steps: establishing an integrated model integrating tracks, NOMA signals and layered continuous interference cancellation; calculating communication and sensing key indexes; constructing an optimization problem which takes maximization of the minimum average interaction rate between the unmanned aerial vehicles as a target and takes power, QoS, perception and security constraints into consideration; a distributed architecture is adopted to decompose problems, and a Dual-TD3 algorithm is proposed to collaboratively optimize beam forming and a flight path. According to the dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, dynamic intelligent distribution of communication and sensing resources is realized, and the interaction rate, the robustness and the resource utilization rate of the system in a dynamic scene are remarkably improved.

Disclosed in the present invention is a three-dimensional roadside sensor deployment method for collaborative sensing in the Internet of Vehicles. The method comprises: modeling an RSN model of a three-dimensional road environment; on the basis of the RSN model, constructing sensing detection functions for single sensors, and when there are a plurality of sensors providing coverage, constructing a global sensor detection function for each deployable area on the basis of the sensing detection functions for the single sensors; taking the maximization of the proportion of deployable areas that meets or exceeds a minimum detection probability as a first objective optimization problem function, which maximization is based on the global sensor detection function, taking the minimization of the total number of sensors in each deployable area as a second objective optimization problem function, and constructing a deployment optimization reward function consisting of the first objective optimization problem function and the second objective optimization problem function; and constructing a decision sequence, and on the basis of a decision transformer, solving the decision sequence to obtain a deployment policy, wherein a cumulative reward value is obtained by performing reward reallocation on the deployment optimization reward function by means of a two-layer optimization method. The present invention implements sensor deployment in a three-dimensional road environment.

A wireless communication method. An initiating user equipment (UE) performs channel occupancy time (COT) initiating for a COT based on a channel access scheme and transmits sidelink data and sidelink control information within the COT. A responding UE receives the sidelink data and sidelink control information within the COT and performs a channel access scheme to use the shared COT. The responding UE transmits a sidelink hybrid automatic repeat request (HARQ) feedback in response to the sidelink data. The initiating receives the sidelink HARQ feedback.

The invention belongs to the technical field of intelligent electric power internet of things, and particularly relates to an unmanned aerial vehicle heterogeneous terminal self-adaptive security access method for electric power edge computing, which comprises the following specific steps: terminal registration and credible anchoring: binding a hardware-level identity, collecting a multi-mode fingerprint and constructing a security behavior portrait; self-adaptive access authentication is carried out; dynamic behavior monitoring and baseline adjustment: establishing an identity authentication and management system, synchronously carrying out multi-dimensional real-time monitoring, carrying out linkage treatment on abnormal behaviors, and adopting a baseline evolution mechanism to avoid misjudgment; the multi-dimensional real-time monitoring comprises terminal service trend monitoring and flow situation analysis; and performing safe closed loop and cooperative response. According to the invention, unified risk detection of the unmanned aerial vehicle can be realized, real-time monitoring of vulnerabilities, access authority and operation states of the unmanned aerial vehicle is carried out, a dynamic behavior monitoring model is constructed in combination with unmanned aerial vehicle terminal information, business data, environment data and the like, and real-time monitoring and early warning of the unmanned aerial vehicle terminal are realized.

The invention provides a virtual power plant dynamic response scheduling method and system based on a cognitive spectrum network, which can improve the reliability, self-adaptive capability calculation efficiency and risk management and control capability of a virtual power plant communication system, and relates to the technical field of virtual power plants, the method comprises the following steps: establishing a cognitive spectrum self-organizing network; collecting current operation state data of each power resource under the virtual power plant and historical operation state data under different working conditions; obtaining a resource response characteristic of each power resource; outputting a preliminary optimization result; converting the preliminary optimization result into a credible optimization result; generating a system risk partition topology report; a market risk hedging strategy capable of being automatically executed is generated; and generating a final scheduling instruction containing the power set value, the execution time, the hedging operation and the risk constraint condition of each resource. According to the method, a feasible technical path is provided for large-scale efficient utilization of distributed resources under the background of the energy internet.

An operating method of a first device (100) in a wireless communication system is presented. The method may comprise the steps of: determining that a first device (100) interrupts walking of a pedestrian; and determining, on the basis of the determination that the first device (100) interrupts walking of the pedestrian, whether to perform a first operation for preventing the interruption.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention relates to a vehicle and unmanned aerial vehicle combined scheduling method for wide-range low-cost inspection. The method comprises the following steps: acquiring prior information; modeling the unmanned aerial vehicle inspection problem of each target area according to the prior information to obtain a mixed integer non-convex optimization problem with the goal of minimizing the weighted sum of the total execution time and the energy consumption of all the inspection unmanned aerial vehicles; performing linearization on a non-convex bilinear term in the mixed integer non-convex optimization problem, and performing discretization processing on a nonlinear function by adopting piecewise linear approximation; an approximate mixed integer linear programming problem is obtained and solved, and an unmanned aerial vehicle scheduling strategy is obtained; modeling according to the unmanned aerial vehicle scheduling strategy and the prior information to obtain an inspection vehicle path planning problem taking the comprehensive driving cost as a target; the routing inspection vehicle path planning problem is converted and modeled into a Markov decision process, a routing inspection vehicle is used as an intelligent agent, a state, an action and a reward function are defined, and a routing inspection vehicle scheduling strategy is obtained. Therefore, combined inspection of the inspection vehicle and the unmanned aerial vehicle is realized, and the inspection range is expanded.

The invention discloses an Internet of Vehicles intrusion detection method based on hierarchical feature enhancement and a dynamic sparse attention mechanism, and the method comprises the steps: firstly obtaining an original CAN bus message data stream, and carrying out the multi-modal data preprocessing and hierarchical feature construction; secondly, for hierarchical features, performing message-level depth feature compression and space-time statistical feature enhancement by adopting a dual-channel feature compression mechanism to form an enhanced mixed feature vector, and then constructing a neural network model of a dynamic sparse attention mechanism based on content awareness to perform feature extraction; and inputting a sparse attention calculation result into a hierarchical classifier, and predicting and outputting a detection result. And training the network model, and deploying the trained network model in a vehicle-mounted embedded device to realize real-time message monitoring and intrusion detection. According to the method, the calculation complexity and parameter quantity of the model are greatly reduced, the real-time performance in a vehicle-mounted environment is remarkably improved, and the detection capability on complex hidden attacks is effectively improved.

The invention discloses a face recognition and encryption verification multi-grid article distribution control method and a distribution vehicle, and relates to the technical field of recognition and verification safety, and the method comprises the steps: fusing three-dimensional environment information through employing a vehicle-mounted edge calculation terminal and a navigation positioning terminal, and constructing a dynamic safety response strategy; the warehouse is analyzed through the vehicle-mounted warehouse control unified management terminal and the dynamic safety response strategy, and an edge intelligent control mechanism is obtained; processing based on a vehicle control and monitoring terminal and an edge intelligent control mechanism to obtain a real-time state; a vehicle interaction terminal and an intelligent operation terminal are utilized to obtain a face image and a visual dynamic feature, and a multi-modal detection strategy is utilized to analyze the face image and the visual dynamic feature to obtain a final authorized face image and a final authorized visual dynamic feature; and a dual-mode intelligent redundant unlocking technology is constructed, and face recognition and encryption verification are performed on the distribution vehicle based on the dual-mode intelligent redundant unlocking technology. According to the invention, compliance, high-efficiency and safe distribution of high-value materials is realized in an unmanned environment.

The invention relates to the technical field of precision agriculture monitoring, and discloses a precision agriculture monitoring system based on adaptive wireless communication. The system comprises a multi-source environment acquisition module, a communication protocol adaptation module and a crop state evaluation module. The multi-source environment acquisition module acquires soil humidity data, illumination intensity data and meteorological parameter data through wireless sensor nodes deployed in a farmland area, and performs timestamp synchronization on the data to ensure the consistency of the data in time dimension. And the communication protocol adaptation module dynamically selects a wireless transmission frequency band according to the synchronous data volume, allocates communication time slots based on the data priority, and generates adaptive transmission channel parameters so as to cope with the communication requirements in the data volume fluctuation and complex environment. The crop state evaluation module receives the transmission channel parameters, analyzes the real-time environment data flow, and divides the current crop growth state into a growth standard state, a growth lag state or a growth fluctuation state. The system provides support for fine management of agricultural production.

The invention provides a vehicle-mounted network security threat sensing system and method based on edge and cloud collaboration, and belongs to the technical field of vehicle network security. Comprising the following steps: S1, collecting vehicle multi-modal data through an edge layer; s2, preprocessing the multi-modal data of the vehicle; s3, performing feature extraction on the preprocessed vehicle multi-modal data to obtain a high-dimensional feature vector; s4, calculating a threat confidence score based on the high-dimensional feature vector; s5, performing hierarchical response decision based on the threat confidence score and a predefined response strategy library, and generating hierarchical response data; s6, extracting threat metadata based on the hierarchical response data; s7, performing global association analysis based on the threat metadata, and upgrading a defense system; and S8, based on the global threat intelligence and the upgraded defense system, carrying out edge layer updating, and then skipping to S1. The method is beneficial to eliminating response delay, relieving network bandwidth pressure and optimizing cloud computing resource load.

The invention discloses a complex environment information acquisition method based on a sensor network, and relates to the technical field of sensor networks, and the method comprises the steps: building a complex environment portrait and a service level, and generating a scene configuration comprising an information freshness budget, a risk heat map and an alarm threshold; based on scene configuration, configuring mesh wireless networking, time synchronization parameters and candidate relays, and constructing observation configuration and quality rules; and generating a data stream and a real-time queue state according to a self-adaptive sampling strategy and an event mark, calculating an emergency degree and distributing a forwarding probability according to an information freshness budget by combining a candidate relay and a risk heat map, outputting uploaded data and a quality record, completing convergence and grading alarm according to an alarm threshold, and generating a disposal feedback and audit index. The state set, the uncertainty set, the link idle degree and the energy sufficiency are linked under the constraint of the information freshness budget, so that hot spot encryption, low-risk sparseness, reduction of energy consumption and conflict rate and standard observation time efficiency are realized.