553 results about "Smart gateway" patented technology

The invention relates to the technical field of data processing, and discloses a multi-protocol fusion Internet of Things equipment intelligent gateway data conversion method and system. The method comprises the following steps: collecting a multi-protocol equipment data packet, and extracting protocol features to construct a vector library; protocol types are identified based on the vector library, data are analyzed, and a data object set containing semantic tags is constructed; semantic correlation is analyzed through an adaptive learning algorithm, and a dynamic protocol semantic mapping matrix is established; converting the data into a standard format according to the mapping matrix and recording a matching degree to form a target data pool; and extracting fusion data from the data pool, recoding according to a target protocol format, and outputting a data frame. The problem that an existing multi-protocol fusion data conversion method lacks protocol semantic understanding and self-adaptive learning ability is solved, and semantic consistency and conversion quality of data conversion among multi-protocol equipment are improved.

The invention discloses a converter station intelligent gateway image recognition system based on a YOLOv3 target detection algorithm, and the system employs a three-stage cooperative processing architecture design, and builds seamless connection of a multispectral image collection layer, an edge calculation gateway layer, and a cloud operation and maintenance management platform layer. The invention further provides an equipment defect detection method based on the system, bimodal image data are collected through the visible light camera and the thermal infrared imager, preprocessing operation is carried out, equipment positioning and defect classification are synchronously executed by utilizing the improved YOLOv3 network, a structured detection result is output, temperature field analysis is carried out on an infrared thermal image, and the equipment defect detection result is obtained. And an abnormal heating area is identified, when defects are detected, multi-level risk response early warning is generated, and a defect diagnosis report is pushed to the cloud operation and maintenance management platform layer. Real-time image analysis of converter station equipment can be realized, the method is suitable for automatic detection of typical fault defects of the equipment, and the operation and maintenance efficiency of a power grid is improved.

The invention relates to a method and a system for automatically updating an intelligent gateway and synchronizing a server. The method comprises the following steps: carrying out system self-inspection and network connection verification on the intelligent gateway to obtain network state information; obtaining version information of the intelligent gateway according to the network state information, and performing local storage management to obtain an update request data packet; establishing a secure communication connection with an OTA server based on the update request data packet to obtain a session credential; performing version comparison of multi-objective optimization by using the session voucher, and executing intelligent update decision making to obtain an update execution plan; downloading an update file from the OTA server according to the update execution plan and performing integrity verification to obtain a verified firmware image file; and deploying the verified firmware image file to the standby partition and executing update installation to complete state synchronous feedback. According to the method, the adaptability and accuracy of the update decision are improved, dynamic resource scheduling in the update process is realized, and the update is ensured to be carried out in the optimal system state.

The invention discloses an automatic protocol matching system for intelligent gateway sensor equipment of a power distribution station house. The automatic protocol matching system comprises a protocol feature deep analysis unit, a graph convolutional neural network topology construction unit, an equipment protocol suitability evaluation unit, a real-time data transmission monitoring unit, an abnormal protocol correction unit and a protocol matching result output unit. The system analyzes sensor protocol characteristics, combines power station house sensor deployment and transmission path construction graph models, evaluates protocol suitability, monitors transmission data, corrects abnormal protocols, and finally outputs a matching scheme. The graph convolutional neural network and the power station room data transmission detection model are utilized to realize automatic protocol matching, improve the fit degree of adaptation and an actual scene, form an exception handling closed loop, reduce interaction failures, improve the data transmission efficiency and stability of the power distribution station room, and meet the requirement of intelligent reconstruction.

The invention provides an intelligent gateway data processing method for industrial multi-protocol adaptive conversion, which aims at the current situation that various heterogeneous communication protocols exist in an industrial site and is based on a complete process of protocol feature vector extraction, machine learning automatic identification, semantic level analysis and mapping, dynamic rule configuration and protocol frame reconstruction. By constructing a protocol feature model library, semantic contents of original data frames are automatically identified and analyzed, and accurate equivalent conversion of multi-protocol data is further realized in combination with a protocol conversion rule and a unified semantic model. The reconstruction function frame realizes frame structure assembly, data coding and check calculation, and ensures that an output frame completely conforms to a target protocol specification. The method has high compatibility, high expansibility and good real-time performance, and the industrial protocol intercommunication efficiency and the automation degree are remarkably improved.

The invention relates to an interface layout generation method based on an intelligent gateway and the intelligent gateway, and relates to the technical field of Internet of Things, and the interface layout generation method comprises the steps: obtaining and transmitting an instrument monitoring video to the intelligent gateway, and recognizing an instrument reading; according to an equipment fault dynamic judgment mechanism, combining with sensor data, fusing and analyzing instrument reading to obtain a data analysis result, and activating a corresponding operation trigger point; determining an interface function weight according to the operation trigger point in combination with a preset weight evaluation model, and constructing an interface layout template in combination with a dynamic layout generation algorithm; capturing and coding user operation behaviors, generating an interface operation event, and correcting the interface layout template in combination with event processing logic to obtain an optimal interface layout; an interface function weight is determined by constructing a weight evaluation model, a reasonable same-screen layout is automatically generated according to different business requirements and use scenes in combination with a dynamic layout generation algorithm and an interface layout template storage calling mechanism, and efficient and visual information display is obtained.

The invention discloses a communication method and system for realizing three-in-one network based on an intelligent CPE gateway, and relates to the technical field of network communication, and the method comprises the steps: connecting a telecommunication network, a broadcast television network and the Internet through the intelligent CPE gateway, collecting bandwidth, delay and packet loss rate data in real time, and storing the data in a time sequence database; analyzing historical and real-time data based on a flow prediction model of machine learning, generating a network demand prediction result of a future time period, and dynamically allocating multiple network resources by using a reinforcement learning algorithm; according to the priority of the service type, splitting the data flow to different network links by adopting a multi-path transmission protocol, and meanwhile, carrying out localization processing on the high-time-sensitivity service through an edge computing node; and providing a user-defined interface, setting the bandwidth priority of the service, and feeding back a user manual strategy to the resource allocation model. According to the invention, efficient interaction of three-network data is realized through multi-network access and protocol conversion of the intelligent CPE gateway.

The invention discloses an equipment health management and predictive maintenance method and system based on an industrial intelligent gateway, and relates to the technical field of industrial automation and predictive maintenance, and the method comprises the steps: collecting equipment data through a multi-source sensor, and carrying out the preprocessing of the equipment data through an intelligent gateway; mapping the high-quality data to a digital twinborn model for health state evaluation; based on an evaluation result, fault prediction is carried out by adopting knowledge-driven and data-driven fused intelligent diagnosis; generating and executing a personalized maintenance strategy; according to the system and the method, the problems of insufficient multi-source data fusion, insufficient health assessment accuracy and lack of individuation of a maintenance strategy are solved, and precision, self-adaption and resource optimization of equipment health management are realized.

The invention relates to the technical field of intelligent lighting control systems, in particular to an underground garage lighting control system and method based on artificial neural network PID and a storage medium. Comprising a brightness sensor, a traffic flow sensor, an illuminance sensor, a temperature and humidity sensor and a microwave speed measurement sensor which are arranged inside and outside a garage; the intelligent network connection lamp comprises an intelligent gateway unit, an LED dimming driving unit and an LED lamp, and the intelligent gateway unit is used for receiving the control instruction and communicating with the upper computer; and the upper computer is used for receiving the data of the detection unit, generating an optimal illumination control curve based on a garage comfort illumination model and a rendezvous zone fuzzy control model, and adjusting the illumination of lamps in each zone in real time through an RBF neural network PID (Proportion Integration Differentiation) algorithm. According to the method, self-learning optimization is achieved, PID parameters are adjusted online through the neural network RBF, the method adapts to long-term dynamic influences such as differences of different types of garages, seasonal changes and equipment aging, and optimal control is given.

The invention discloses a real-time state synchronization method and system, electronic equipment and a storage medium, and belongs to the technical field of network communication.The method comprises the steps that in response to a connection request from a client side, persistent connection with the client side is established, and a state subscription relation is recorded; performing semantic analysis on the state change event from the business service layer to determine a push priority; a corresponding target intelligent gateway is found according to the target object identifier of the state change event, a pushing strategy is executed by fusing the client network condition maintained by the target intelligent gateway and the pushing priority, and the state is updated and synchronized to the related client; and monitoring the health state of the persistent connection, and when the connection is abnormal and recovered, performing state synchronization with the client by the intelligent gateway based on the stored incremental state information. According to the invention, the problems of unreliable connection, redundant pushing and poor expansibility of a traditional SSE scheme are solved, and high-reliability, high-efficiency and horizontally-expandable real-time state synchronization is realized.

The invention discloses a smart park alarm method and system based on an intelligent gateway, and the method comprises the following steps: accessing a heterogeneous terminal through a multi-protocol southbound interface, generating a standardized event set, and building a spatial topology table; performing quality evaluation on the standardized event set to form a sequential cleaning event stream; target detection is carried out based on the sequential cleaning event flow, and a semantic event flow is output; performing space-time matching on the semantic event flow to obtain a fusion event set; according to a preset grading standard, a grading warning set is generated, and a linkage instruction set is generated; scheduling and executing the execution end according to the linkage instruction set to form a processing state feedback; integrating the grading warning set and the processing state feedback into an evidence packet, and reporting the evidence packet in parallel through the main and standby reporting links; and archiving and indexing the evidence packet and the reported result, generating an auditable record, and finishing synchronous updating with an upper platform. According to the invention, the smart park alarm method and system are realized.

The invention relates to the technical field of power grid monitoring, and discloses a power grid power equipment anomaly prediction method, system and device, and a storage medium, which are used for solving the problem that the existing single data source and threshold alarm prediction mode cannot adapt to advanced prevention and high-precision state detection. The method comprises the following steps: acquiring real-time electrical quantity time sequence data, image data and a monitoring report of each piece of power equipment in an equipment abnormal area in a power grid through an edge intelligent gateway; respectively carrying out feature extraction on the real-time electric quantity time sequence data, the image data and the monitoring report to obtain an electric quantity feature vector, a visual feature vector and a semantic feature vector; and carrying out weight fusion on the electrical quantity feature vector, the visual feature vector and the semantic feature vector, and carrying out abnormal state prediction based on the fused feature vector and a historical feature sequence.

The invention relates to the technical field of gateway equipment data processing, and provides an intelligent alarm method, device and equipment of a multifunctional gateway and a storage medium, and the method comprises the steps: obtaining smoke concentration data and door magnetic state data of the intelligent gateway equipment to generate a corresponding alarm signal, carrying out the noise filtering and time window analysis of the alarm signal, and obtaining the smoke concentration data and the door magnetic state data of the intelligent gateway equipment. The alarm intensity index and the alarm duration index are obtained, the alarm intensity index and the alarm duration index are utilized to sort the alarm priorities, an alarm scheme is obtained, and a fire-fighting response instruction is generated based on the alarm scheme. Smoke concentration data and door magnetic state data are collected for real-time analysis and association processing, a fire-fighting response instruction is generated, the alarm accuracy and response efficiency are improved, potential safety hazards caused by false alarm and leakage alarm are reduced, and the problems that in practical application, a current alarm system is poor in adaptability in complex scenes, and fire-fighting performance is poor are solved. The processing of a plurality of alarm signals is not accurate enough, and false alarm or missing alarm occurs.

The invention discloses a mobile intelligent safety supervision device based on multi-mode perception and edge calculation, and the device comprises a camera which is a high-performance dual-camera with adjustable height and visual angle, is fixed on a telescopic aluminum alloy support, integrates a loudspeaker and a voice communication function, and supports the autonomous network and 4G bidirectional communication; the edge intelligent gateway is used as a core computing unit, supports a neural network algorithm to analyze audio and video data, and realizes real-time identification of security behaviors; the Beidou positioning module is integrated on the edge intelligent gateway and provides centimeter-level high-precision positioning; the data storage module is used for large-capacity data storage and supporting storage and retrieval of audio and video streams and analysis data; the network transmission module is a multi-protocol network transmission module and supports WiFi, 4G and wired network transmission; and the power supply module is high in capacity and adopts a pluggable battery design. Omnibearing high-definition video monitoring can be realized, and the requirements of real-time communication and real-time early warning between project responsible personnel and on-site construction personnel are met.

The invention relates to the technical field of intelligent gateways, in particular to an unmanned mine car multi-group radar external parameter calibration method and calibration system. The unmanned mine car multi-group radar external parameter calibration method comprises the following steps that a foam rectangular calibration plate serves as a core, a novel calibration plate frame is designed in cooperation with a corner reflector, and meanwhile a small calibration field capable of meeting unmanned mine car multi-laser radar and millimeter wave radar external parameter calibration tasks is designed based on the calibration plate frame; and performing laser radar data recording on the miniaturized calibration field to obtain laser radar point cloud data in the calibration field, and realizing calibration target extraction and constraint extraction according to the point cloud data of the calibration field. The method is suitable for unmanned mine car multi-laser radar and millimeter wave calibration, the efficiency is improved, and therefore the problems that in the prior art, the unmanned mine car is poor in calibration process precision, insufficient in global optimization and expansibility and the like in the outdoor rugged environment are solved.

The embodiment of the invention provides a trusted IoT (Internet of Things) access method and equipment based on a block chain. The method is applied to the technical field of communication, and comprises the following steps: firstly, generating a key for the Internet of Things in a TEE environment of an intelligent gateway, encrypting a resource address of an Internet of Things device, preventing the key from being acquired by malicious software, preventing the key from being counterfeited, and ensuring the security of the Internet of Things device accessing a block chain network, and a block chain stores a key index instead of the key, so that the security of the Internet of Things device accessing a block chain network is ensured. The risk of key leakage is further reduced; by setting a device management contract and a policy authority contract, the authority of a user for accessing the Internet of Things device is inquired and managed, fine control of the access authority is realized, and only the user having the authority can obtain a corresponding secret key from an intelligent gateway to decrypt an encrypted resource address provided in a block chain. According to the arrangement, leakage of the resource address is effectively prevented, and sensitive information is prevented from being leaked.

The present invention discloses a 5G-TSN industrial heterogeneous virtual network architecture and a fine-grained scheduling method for virtual resources, and relates to the field of industrial communications. NFV technology is used to virtualize the TSN intelligent gateway of the edge computing layer into a virtual machine with TSN functions; the SDN controller centrally controls the TSN intelligent gateway supporting SDN technology deployed at the edge computing layer, and combines with NFV technology to perform virtualized network modeling of the 5G-TSN industrial heterogeneous network from the perspective of resource scheduling, and schedules and manages network slices with different QoS belonging to different industrial applications. The present invention is oriented to the upper-layer dynamic application requirements of flexible manufacturing, takes into account the heterogeneous QoS requirements of on-site communication resources and data streams, introduces the age of information (AoI) as an indicator at the virtual level to characterize the information timeliness of 5G access network data transmission, and proposes a 5G-TSN industrial heterogeneous virtual network architecture and heterogeneous QoS mapping mechanism in combination with the characteristics of 5G data, which can realize fine-grained on-demand delivery of industrial multi-priority heterogeneous data streams.

The invention relates to the field of network equipment test, discloses a test method and a test management system for intelligent PON gateway test, and solves the problems of insufficient test coverage, difficulty in equipment compatibility verification, low test efficiency, inaccurate test result analysis and the like in the existing intelligent PON gateway test process. High-quality and high-efficiency testing of the intelligent PON gateway is realized by establishing a testing historical database, dynamically generating a testing strategy, intelligently scheduling testing resources, accurately calculating a testing balance index and pointedly solving the problem of testing imbalance.

The invention discloses a method and a system for realizing remote operation and maintenance of equipment through cooperation of an industrial intelligent gateway and a cloud platform, and relates to the technical field of remote operation and maintenance of industrial Internet of Things, and the method comprises the following steps: the gateway collects multi-modal data of the equipment and locally preprocesses the multi-modal data to generate a structured data packet; lightweight Transform model forward propagation is executed, and an encrypted feature vector is extracted and uploaded to a cloud platform; the cloud platform adopts federated learning to update model parameters based on the feature vectors, issues the model parameters to the gateway, and synchronously constructs equipment digital twin bodies; analyzing the natural language operation and maintenance instruction through the digital twin to generate a control command; an equipment association graph is constructed, a fault propagation path is analyzed by using a graph convolutional network (GCN), and an early warning is generated; and after executing the control instruction, the gateway feeds back state data to the cloud platform, updates the digital twin and model input, and forms closed-loop control. According to the invention, collaborative optimization of data privacy protection, cross-device fault prediction and intelligent decision is realized, and the operation and maintenance efficiency and security are improved.

The invention relates to the technical field of artificial intelligence, intelligent gateways and finance, and provides a flow scheduling method, device and equipment for an intelligent gateway and a medium, and the method comprises the steps: obtaining resource monitoring data and API call chain data of each node in the intelligent gateway through a distributed service cluster grid; determining resource use trend prediction information and dynamic threshold information according to the resource monitoring data and a trained time sequence prediction model; in response to the fact that the resource use trend prediction information is abnormal, determining a fault propagation path according to the API call chain data and a pre-trained causal reasoning model; and determining a dynamic flow scheduling strategy through a multi-factor weight formula, and determining an adaptive fusing strategy according to the dynamic threshold information. Through the technical scheme, the problems of difficult fault positioning and scheduling lagging in a traditional distributed system are solved, and the stability, the anti-risk capability and the resource utilization efficiency of the intelligent gateway in a complex load scene are remarkably improved.

The invention discloses an unattended hydropower station intelligent safety prevention and control system and method, and the system comprises a sensing layer, a network layer, a platform layer and an application layer, the sensing layer is provided with multiple types of sensors, and collects equipment operation parameters, a dam structure state, a reservoir area hydrological environment and perimeter image data in real time; the underwater sonar, the unmanned aerial vehicle and the camera are included to realize omnibearing monitoring; the network layer adopts 5G + LoRa dynamic fusion networking, and a deep Q network routing algorithm is integrated through an intelligent gateway. According to the intelligent safety prevention and control system and method for the hydropower station based on unattended operation, the structure is reasonable, a three-dimensional monitoring network is constructed through vibration / temperature / pressure sensors, underwater sonar, an unmanned aerial vehicle, an AI camera and the like, and equipment operation parameters, the dam structure state, the reservoir area hydrological environment and perimeter image data are collected in real time; all-around dead-corner-free monitoring of equipment, structure and environment of the hydropower station is achieved, and the system is worthy of popularization.

The invention relates to the technical field of intelligent gateways, in particular to a method and system for automatically expanding intelligent router plug-ins through LLM. The method comprises the steps that a user describes a plug-in function requirement of the intelligent router in a natural language through voice or text input equipment; and the cloud preprocessing service carries out character conversion processing on the voice data, carries out contradiction check and invalid information filtering on natural language requirements, extracts structured requirement information and inputs the structured requirement information to the cloud big language model. According to the intelligent router plug-in development method and system, the problems that in traditional intelligent router plug-in development, the manual intervention degree is high, the process is long and compatibility is insufficient are effectively solved by constructing an automatic system with the cloud large language model and the multi-service module cooperating. Through cooperation of multiple technical modules, a full-automatic process covering demand input, code generation, engineering integration, test verification and terminal deployment is constructed, and the intelligent router plug-in development efficiency and quality are remarkably improved.

The invention relates to the technical field of industrial intelligent gateways, in particular to an aviation plug waterproof wet plug type connector for an intelligent gateway. Comprising a connecting shell, a conductive module is arranged in the middle of the interior of the connecting shell, the conductive module is used for protecting two cable ends after butt joint is completed, symmetrically-distributed sliding rings and symmetrically-distributed limiting rings are slidably connected into the connecting shell, and the sides, close to the conductive module, of the limiting rings are in threaded connection with threaded sleeves. And wedge-shaped blocks which are distributed at equal intervals in the circumferential direction are fixedly connected to the sides, close to the conductive modules, of the limiting rings, the threaded sleeves are used for extruding the adjacent wedge-shaped blocks so as to clamp the adjacent cable ends, and springs are fixedly connected between the sliding rings and the adjacent limiting rings. According to the invention, the springs and the limiting rings drive the wedge-shaped blocks which are distributed at equal intervals in the circumferential direction, so that the two separated cable ends are close to each other, and normal transmission of current can still be ensured after the cable ends are interfered by external force.

The utility model discloses a structural settlement diagnostor which comprises an intelligent gateway, a liquid storage tank, a static level gauge a, a static level gauge b and a static level gauge c which are respectively connected in series through an air pipe, a liquid pipe and a communication bus. When the static force level gauge a, the static force level gauge b and the static force level gauge c are replaced and maintained, the connecting nut is rotated, the connector a and the connector b are separated, no pressure exists between the ejector rod and the conical round head b, under the action of resilience force of the elastic piece a and the elastic piece b, the inner taper hole round plate a makes contact with the conical round head a, the connector a is sealed, and the static force level gauge c is maintained. And an inner taper hole circular plate b is in contact with a conical round head b to seal a connector b, so that the condition of liquid leakage is avoided after the liquid pipe is detached, and the maintenance difficulty is reduced.

The invention discloses an equipment logic interlocking control method supporting edge collaboration and an intelligent gateway, and belongs to the field of industrial control and industrial Internet of Things. Reading a configuration center rule and generating a verification entry list; reading a local key value cache, sending a remote state query request and analyzing a state response message; obtaining an interlocking judgment result based on aging screening, numerical value comparison and Boolean operation of the collection timestamps; and executing physical bus message issuing or failure response output according to an interlocking judgment result. According to the method, a data access mode of combining configuration center rule management and local cache is adopted, so that the state of the dependent object can be uniformly verified, and the interlocking judgment traceability is improved.

The invention discloses a method and system for adapting an industrial intelligent gateway to multiple industrial protocols, and relates to the technical field of industrial Internet of Things edge computing, and the method comprises the steps: monitoring industrial network traffic self-learning, and constructing a protocol fingerprint database; dynamically constructing a virtual equipment twinborn body based on the fingerprint database to form a simulation environment; automatically verifying protocol configuration in a simulation environment; the application verification configuration is connected with the entity device to collect data; performing in-stream calculation processing on the data stream in real time to generate an advanced event and feature data; according to the method, automatic identification and compatibility of unknown protocols are realized, production accidents are avoided through virtual simulation verification, data value extraction is synchronously completed in the data acquisition process, and the security, reliability and data processing efficiency of protocol adaptation are effectively improved.

The invention belongs to the technical field of environment monitoring equipment, and relates to an environment monitor for a chemical plant, which comprises a stand column, a monitoring box and a sampling box, a multi-sensor fusion unit is mounted at the bottom of the monitoring box, and an edge intelligent gateway is arranged in the multi-sensor fusion unit; a detachable sampling container is arranged in the sampling box, a gas inlet joint and a gas outlet joint are arranged on the sampling container, a sampling joint is mounted at the bottom of the monitoring box, one end of the sampling joint extends out of the monitoring box, and the other end of the sampling joint is connected with the gas inlet joint through a gas conveying pipeline; an air extracting pump is installed in the sampling box, an air inlet of the air extracting pump is detachably connected with the air outlet connector, and the multi-sensor fusion unit and the air extracting pump are electrically connected with the edge intelligent gateway. The environment monitor can be arranged at a certain point position of a chemical plant and used for monitoring pollutants in ambient air, continuous real-time on-line monitoring can be carried out on the pollutants in the ambient air by using the multi-sensor fusion unit and the edge intelligent gateway, and gas samples can be automatically and manually collected.

The invention relates to the technical field of Internet of Things communication, and discloses a self-adaptive wireless communication intelligent gateway optimization method, which comprises the following steps: collecting wireless communication environment information; analyzing the wireless communication environment; if the node meets the reporting condition, triggering an active reporting mechanism, and if the node does not meet the reporting condition, not triggering; performing corresponding optimization based on the reported data content in the active reporting mechanism; by arranging the step 2 and the step 3, back-and-forth control is facilitated by adopting a dynamic polling interval adjustment mechanism, node data is acquired in real time, communication power is adjusted according to the node distance to reduce energy consumption, and compared with a fixed polling mechanism, the node energy consumption is reduced; and meanwhile, an active reporting mechanism is adopted to timely discover a node communication problem and judge whether the node meets a reporting condition or not, and if so, the node is timely reported and the active reporting mechanism is triggered, so that node abnormity and data abnormity can be timely discovered, event reporting time delay is reduced, and corresponding optimization is timely performed to improve communication stability.

The present invention discloses an intelligent lighting control system for a parking lot, which belongs to the field of intelligent lighting technology and includes: an acquisition and processing module for collecting real-time data of the parking lot environment and performing preprocessing; an automatic control module for intelligently controlling parking lot lighting, which enables local sensing and linkage between AI lamps through Bluetooth Mesh networking technology, so that the group can respond synchronously; a remote control module for adding an intelligent gateway to access the Internet to remotely control the parking lot. The present invention solves the existing problems of being unable to automatically adjust the brightness and lighting range of parking lot lighting according to factors such as ambient light and human activities, and being unable to remotely control the parking lot, resulting in low parking lot management efficiency and energy conservation and environmental protection levels. The present invention can automatically adjust the brightness and lighting range of parking lot lighting according to factors such as ambient light and human activities, achieve a two-way balance between energy conservation and user experience, and can remotely control the parking lot, which can improve management efficiency and energy conservation and environmental protection levels.

The invention discloses a high-low voltage power distribution cabinet operation monitoring management method and system based on big data analysis and electronic equipment, and relates to the technical field of intelligent operation and maintenance of high-low voltage power distribution cabinets. The method comprises the following steps: acquiring various parameters based on deployed various types of sensors, and performing protocol conversion on acquired data through an intelligent gateway; carrying out local preprocessing on the data, and generating a standardized data message; uploading the data to a cloud platform, performing association analysis on multi-source data through a big data fusion algorithm, establishing multi-baseline monitoring of an equipment operation state, performing fault mode identification on abnormal data deviating from baselines, and generating fault early warning information; and automatically generating an operation and maintenance strategy according to the fault early warning information in combination with a preset operation and maintenance rule base. According to the technical scheme, comprehensive and real-time monitoring of the operation state of the high-low voltage power distribution cabinet is achieved, multiple parameters are collected through multiple types of sensors, the big data analysis technology is combined, and the abnormal situation in the equipment operation process can be accurately captured.