1388results about How to "Realize management" patented technology

The invention discloses a trackless rubber-tyred vehicle multi-terminal data fusion system, relates to the technical field of data fusion, and is used for solving the problem of poor trackless rubber-tyred vehicle multi-terminal data fusion. Comprising a path quantification module, an equipment health classification module, an alternative optimization module and a consistency verification module. According to the method, multi-terminal data fusion is carried out on a trackless rubber-tyred vehicle, a sensor dependency graph is dynamically constructed, dependency weights are calculated, a critical path is optimized, health indexes are defined according to a signal-to-noise ratio, output fluctuation and response delay, multi-dimensional abnormity is detected in combination with a sliding window and a mahalanobis distance, and a health score is generated to monitor the state of the sensor. A fault sensor is isolated, substitute data is generated through a redundant data source, the substitute data is incorporated into a fusion process after verification, a dependency graph is adjusted, a path is optimized, global consistency verification analysis is performed, different strategy management modules are triggered, a data fusion rule and task allocation are optimized, and the data fusion reliability of the trackless rubber-tyred vehicle in a complex operation environment is improved.

The invention relates to the technical field of data processing, in particular to an intelligent logistics platform management system and method based on multi-source data. The method comprises the following steps: acquiring cold-chain logistics order data; performing multi-type cargo temperature control demand processing on the cold-chain logistics order data to generate cargo temperature control demand data; performing multi-node temperature control task decomposition on the cold-chain logistics order data through the cargo temperature control demand data to generate multi-node fine temperature control task data; performing cold chain abnormal feature analysis according to the multi-node fine temperature control task data to generate abnormal temperature control processing scheme data; and carrying out transportation-junction point temperature control correction according to the abnormal temperature control processing scheme data, and carrying out cold chain quality weighted scoring to generate logistics quality scoring data. According to the invention, through cold chain task decomposition and cooperation of multiple transportation nodes, intelligent cold chain logistics management is realized, and the temperature control management efficiency and cargo quality guarantee of cold chain logistics are improved.

The invention provides a self-adaptive power supply energy-saving configuration method and system based on energy gradient utilization, and relates to the technical field of power supply management, and the method comprises the steps: collecting the operation parameters of electric equipment, building a power utilization model, and carrying out the self-adaptive correction; constructing a multi-stage energy distribution matrix according to the corrected power utilization model, and performing energy efficiency grading on the power utilization equipment; performing spatial-temporal feature extraction by adopting a bidirectional attention mechanism, generating an electric equipment priority strategy in combination with a self-calibration network, and further calculating an energy distribution proportion of each level of electric equipment; and finally, generating a control signal according to the energy distribution proportion, adjusting the power supply power of each stage of electric equipment, distributing the exceeded power to the electric equipment with the secondary high energy conversion efficiency when the power value exceeds a target power threshold value, and outputting a self-adaptive energy balance control instruction according to the prediction control model to adjust the operation state of the electric equipment.

The invention discloses an intelligent sensing algorithm and system for crop growth vigor, computer equipment and a medium, and the algorithm comprises the following steps: 1, carrying out the image collection of a farmland, and collecting the spectral data of different wavebands in the farmland; 2, preprocessing the collected images and spectral data, and extracting multi-dimensional feature information of the crops; 3, fusing the extracted multi-dimensional feature information of the crops to obtain comprehensive and accurate crop growth feature information; 4, performing data analysis on the crop growth feature information through deep learning, and constructing an intelligent decision model; through the implementation of the invention, the characteristics and beneficial effects of multi-information fusion, high-precision perception, cost reduction, quality improvement, wide application and the like are realized through the crop growth vigor intelligent perception algorithm, and the method plays an important role in improvement of agricultural production and agricultural product quality.

The invention relates to the field of parking lot management, in particular to a parking management method and system based on data analysis. The method comprises the following steps: acquiring real-time state information of a parking lot and a historical parking monitoring log of the parking lot; analyzing the dynamic characteristics of the vehicle in the fixed parking space according to the real-time state information of the parking lot, and predicting the available time so as to generate the predicted available time of the fixed parking space; acquiring traffic flow data of a target parking lot area; performing multi-section traffic flow analysis on the traffic flow data of the target parking lot area, and performing traffic flow time sequence trend evolution to generate real-time road state characteristics of the target area; and performing time sequence parking demand analysis on the historical parking monitoring log of the parking lot, and performing dynamic parking demand prediction of the target parking lot according to the real-time road state characteristics of the target area so as to generate a dynamic parking demand prediction value. According to the invention, parking lot management with high efficiency and high utilization rate is realized.

The invention relates to the technical field of building management, and discloses a building green construction whole process management method and system based on a BIM technology, and the method comprises the following steps: data collection and integration: collecting multi-dimensional data of energy consumption, environment and equipment state of a building construction site through an arranged Internet of Things sensor network, data preprocessing and transmission are carried out through edge calculation; identification management is carried out on the building materials and equipment through RFID or two-dimensional codes; energy efficiency analysis and evaluation: performing real-time analysis on the energy efficiency and carbon emission of each construction link based on the collected data, and displaying the distribution condition of the energy efficiency and the carbon emission through a BIM model; and intelligent decision support and optimization: utilizing a machine learning algorithm to predict energy consumption and material consumption. Efficient resource allocation is realized through real-time monitoring and intelligent optimization; meanwhile, based on the BIM model and seamless data sharing in the operation and maintenance stage, the system realizes green management of the whole life cycle of the building, and supports sustainable development of the building industry.

The invention provides a Web-based MBSE collaborative research and development management system, which belongs to the field of model-based system engineering and comprises a demand center used for managing demands generated in a system development process and supporting system models, simulation data and demand entries to trace; the model center is used for managing model data generated in a system development process taking a demand as an input; the simulation center is used for calling and executing each model and recording simulation configuration, simulation tasks and simulation result data; the document center is used for extracting data and automatically generating and managing various documents; the digital clue is used for managing digital clue data of the MBSE and displaying an association tracing relation of data in a forward design process based on a model; and the project management module is used for managing the information of the MBSE research and development project. According to the method, a model-based system digital research and development process is realized, team cooperation efficiency and product design quality are improved, and tool support is provided for complex product MBSE activities.

The invention provides a sewage treatment operation cloud platform based on Internet of Things and GIS, and the platform is characterized in that a data collection layer is used for obtaining user water consumption data and sewage pipe network data, and distributing all the data to each edge calculation node; the data storage layer is used for temporarily storing the data preprocessed by the edge computing node into a high-frequency storage chain, aggregating to obtain sewage pipe network comprehensive data, and permanently storing the sewage pipe network comprehensive data into a low-frequency storage chain; the data analysis layer is used for extracting sewage pipe network comprehensive data in the low-frequency storage chain, constructing a multi-dimensional dynamic GIS model by utilizing a GIS system, analyzing and predicting the multi-dimensional dynamic GIS model through a sewage treatment rectification analysis model, and generating a sewage treatment rectification plan of the sewage pipe network according to an analysis and prediction result; and the application service layer is used for acquiring all the sewage treatment and rectification plans and distributing all the sewage treatment and rectification plans to a management client held by a sewage pipe network manager. The sewage treatment device has the effect of efficiently and intelligently realizing sewage treatment.

The invention relates to the technical field of data processing, in particular to an automatic rule configuration process processing method, system and device and a medium, and the method specifically comprises the following steps: obtaining first delivery rule data, and carrying out semantic analysis and structured extraction on the first delivery rule data to form second delivery rule data; establishing a standard index library, and performing index systematic construction on the second putting rule data according to the standard index library to generate a multi-way tree rule; performing automatic verification on the multi-way tree rule according to a rule verification tool, determining whether the multi-way tree rule is reasonable or not, and if the multi-way tree rule is not reasonable, optimizing the multi-way tree rule; and obtaining historical advertisement putting data, and performing an advertisement putting scene simulation test on the multi-way tree rule according to the historical advertisement putting data. According to the invention, through generation, optimization and application of the multi-way tree rule, intelligent configuration, management and optimization of the advertisement putting rule are realized.

The invention relates to the technical field of industrial equipment management, and discloses an equipment management method for a 3D digital factory, and the method comprises the following steps: sensing the operation parameters of a network collection device through the Internet of Things; processing the operation parameters by utilizing a cloud computing or edge computing technology; dynamically generating an equipment health state based on the processed data; the equipment management system of the 3D digital factory comprises an Internet of Things sensing network used for collecting operation parameters of the equipment; the data processing module is used for carrying out cleaning, noise reduction, dynamic modeling and anomaly detection on equipment operation parameters; and the equipment health state generation module is used for generating the health state of the equipment. According to the invention, through the Internet of Things sensing network, dynamic modeling, intelligent scheduling and full-life-cycle management technology, the effects of equipment state real-time monitoring, accurate maintenance, energy efficiency optimization and comprehensive asset management are realized.

The invention discloses a distribution network line fault early warning and accurate positioning system, and relates to the technical field of distribution network line monitoring. In order to solve the problems that in actual operation, due to the complexity of a power grid, the situation of false alarm or missing alarm may exist, and in actual application, accurate fault positioning is crucial for quickly recovering power supply and reducing power failure time, and the accuracy of fault position positioning is low. Distribution network line data and traveling wave signals are accurately acquired in real time through the data acquisition unit, abnormal changes in a distribution network can be found in time through the fault early warning unit, the fault type can be rapidly identified, the fault occurrence position can be accurately calculated through the fault positioning unit, the rod fixing data of a fault point can be determined, and the fault positioning accuracy can be improved. According to the invention, the time of troubleshooting by operation and maintenance personnel is reduced, the fault processing efficiency is improved, the operation and maintenance personnel can remotely monitor the operation state of the power distribution network, the convenience and efficiency of operation and maintenance are improved, intelligent monitoring and management of the power distribution network are realized, and the operation and maintenance cost is reduced.

The invention discloses a digital archive management method and system, particularly relates to the field of digital archive management, and aims to evaluate the fracture or abnormal jump degree of time data through continuous analysis of the time data in a digital archive. And carrying out integrity analysis on the spatial data in the digital archive, and evaluating the abnormal deviation or missing degree of the spatial data. And according to the evaluation results of the time data and the spatial data, screening out archives with time-space association abnormity. And based on the digital archive with the space-time association abnormity, the space-time association between the time data and the space data is evaluated by analyzing the space-time association matrix. The digital archive management model is established according to the fracture or abnormal jump degree of the time data, the abnormal deviation or missing degree of the space data and the space-time correlation of the digital archive space-time data, so that the digital archive management efficiency and the digital archive integrity are improved.

The invention relates to the technical field of assembly line scheduling, in particular to an intelligent scheduling method and system for an automatic assembly line of a charging pile. The method comprises the following steps: acquiring a charging pile assembly production log; performing sliding window segmentation processing on the charging pile assembly production log, and performing staged assembly demand feature analysis to obtain assembly demand feature data of different stages; the real-time production progress of each assembly line is extracted based on the charging pile assembly production log; demand supply deviation prediction is carried out on the real-time production progress of each assembly line according to the assembly demand characteristic data of different stages, and assembly lines lack of productivity are marked; an all-dimensional real-time monitoring image of the assembly line is collected; and carrying out dynamic behavior analysis on the omnibearing real-time monitoring image of the assembly line, carrying out process operation logic analysis, and generating multi-stage process operation logic. According to the invention, high-efficiency and self-adaptive intelligent scheduling of the assembly line is realized.

The invention discloses a method and system for independent application of multi-modal data after fusion and archiving, and relates to the technical field of archive management. The technical key points are as follows: establishing a service management platform, including a user group and an archive group, managing the user group and the archive group, defining an archive as a node by adopting a chain network structure, starting archiving management, generating an archiving package, and performing independent application between nodes, so that a user can quickly retrieve and position the archive; effective interaction between data is realized to a certain extent; state data of an archiving packet is processed through a target decision network, an archiving score is calculated, a corresponding archiving interval is matched according to the archiving score, different calling levels are correspondingly set, different users are endowed with corresponding permissions for management, and the whole system judges the management quality by designing evaluation factors, so that the management efficiency is improved. And the management efficiency is further improved.

The invention provides a prediction and management method and system suitable for pollen multi-dimensional information, and the method comprises the steps: carrying out the statistics of historical item data of a display region, inputting the data into a plurality of first-stage models in an initial prediction model, carrying out the training, obtaining an intermediate prediction result, carrying out the combination, inputting the combined data into a second-stage model, and carrying out the training, and generating a pollen prediction model; receiving a plurality of allergy factors set by the user side, acquiring real-time data of the display area based on the allergy factors, inputting the real-time data into the pollen forecasting model to obtain pollen concentration data, and inputting the pollen concentration data into the pollen health influence model for calculation to obtain a pollen influence logarithm; when the pollen influence logarithm is greater than a preset influence value, generating an initial diffusion region corresponding to each planting region based on an allergen display strategy and the planting region of each allergy factor in the display region; and receiving area data of the display area, adjusting the initial diffusion area to determine an allergen area, generating early warning information based on the real-time position information of the user side and the allergen area, and sending the early warning information to the user side.

The invention relates to the technical field of logistics informatization management, and discloses a warehousing method for logistics informatization management, and the method comprises the steps: 1, determining the target and demands of warehouse management, and reasonably planning a warehouse region according to the actual condition of a warehouse; 2, inputting detailed information of the goods into a warehouse management system, and inputting and managing customer information; 3, receiving purchased commodities, and carrying out inventory management and ex-warehouse management; 4, collecting various data in the warehousing operation process in real time, including the warehousing quantity, the ex-warehouse quantity, the stock quantity and the operation efficiency, and providing a decision support function according to a data analysis result; and 5, regularly maintaining and checking the warehouse management system to ensure the stable operation of the system and the safety of data. According to the warehousing system for reducing manual operation and paper file processing and logistics informatization management, automatic equipment, an information system and the Internet of Things technology are adopted, and the management efficiency and accuracy are greatly improved.

The invention discloses an enterprise cloud asset global data integration management method based on a data center station, and aims to solve the problems of data source dispersion, complex management, data islanding and the like, and the method comprises the following steps: automatically identifying and classifying various data sources of an enterprise through an evolutionary algorithm, and generating a dynamic data source directory; based on the directory, a self-adaptive data access strategy is generated, unified access of structured, semi-structured and unstructured data and data synchronization of a cross-cloud platform are realized, a unified data model is constructed in a data platform, and unified mapping of data of different sources is realized through a semantic mapping technology. In the data transmission process, the optimal path set is adopted to ensure high efficiency and stability of data transmission. According to the method, the received data is dynamically treated through a self-adaptive strategy, a cross-cloud data virtualization layer is constructed based on the treated data, transparent management of data resources is realized, and data analysis is performed by adopting real-time processing and a differential privacy enhancement algorithm.

The invention discloses an intelligent emergency control system of an arrangement ship steering oar, and belongs to the technical field of arrangement ship steering oar control. An intelligent emergency control system of an arrangement ship steering oar comprises a main control module, a steering oar driving module and a steering oar control module. The problem that in the prior art, when a main steering system breaks down, a ship is prone to being out of control, colliding or other safety accidents are caused is solved, the steering oar driving module is used for conducting driving operation on the arrangement ship steering oar in an emergency mode, the state of the arrangement ship steering oar is monitored in real time, and the safety of the arrangement ship steering oar is improved. When potential problems and fault trends exist in the arrangement ship steering oar, a control instruction of the arrangement ship steering oar is adjusted so as to ensure safe operation of the arrangement ship steering oar, quick response can be made and an emergency mode can be started in emergency, dangerous situations such as out-of-control of the ship can be effectively avoided, remote monitoring and management can be achieved, and the safety of the arrangement ship steering oar is improved. Safety and management efficiency of the ship are improved, and safe driving of the ship is effectively guaranteed.

The invention relates to an intelligent electric meter reading method and system, and the method comprises the steps: enabling a high-definition camera to shoot an intelligent electric meter according to a preset meter reading time interval, obtaining an electric meter image, and uploading the electric meter image to an edge computing device through the Internet of Things; the high-definition camera is installed right in front of a dial plate of the intelligent electric meter. The edge computing device carries out image preprocessing on the electric meter image and transmits the electric meter image after image preprocessing to a server; the server recognizes the received electric meter images by adopting a plurality of image recognition models based on a deep learning algorithm, compares and verifies the electric meter readings obtained by recognition of the plurality of image recognition models, and if the comparison and verification are passed, sends the electric meter readings to the server; if yes, the current ammeter reading of the intelligent ammeter is obtained according to the ammeter reading obtained through identification processing of various image identification models; and the server performs associated storage according to the ammeter number of the intelligent ammeter and the current ammeter reading. According to the invention, the meter reading efficiency can be improved.

The invention relates to the technical field of battery monitoring and management, and discloses a power battery monitoring and management system and method based on the Internet, and the system comprises a data collection unit, a preprocessing unit, a data transmission unit, a feature extraction unit, a data analysis unit, a fault diagnosis unit, and a remote management unit. In battery state evaluation, the charge state is calculated by combining an ampere-hour integral method with an open-circuit voltage method, and errors are calibrated and reduced; the health state is calculated through the internal resistance change rate, maintenance or replacement requirements can be prompted in time, voltage, temperature, charge and health state parameter trends are analyzed through setting observation points, faults including potential faults are efficiently diagnosed in combination with normal threshold value comparison and change rate comparison, and finally a user can remotely check the visual battery state. When a fault occurs, an instruction can be sent remotely, control such as power limiting and balance operation starting is achieved, and convenience and high efficiency are achieved.

The invention relates to the technical field of power system monitoring, in particular to an electric energy quality monitoring method and system considering broadband transmission characteristics of a mutual inductor, and the method comprises the following steps: collecting current, voltage and frequency data of the mutual inductor under various load conditions in real time based on the operation log information of a power grid, and recording the operation data and time information of the power grid; and generating mutual inductor operation data. According to the invention, the transmission characteristics of the mutual inductor under various power grid load changes are analyzed to ensure that the monitoring data accurately reflect the actual operation state of the power grid, the data processing parameters and the data verification threshold are adjusted in combination with the real-time load to ensure the accuracy of the data acquisition process, and the occurrence frequency of the abnormal parameters is identified to ensure the accuracy of the data acquisition process. The influence of various operation parameters on the electric energy quality is quantified, the operation stability of the power grid is evaluated by calculating statistical data and volatility of various power grid quality parameters, visual power grid health condition evaluation is provided for power grid operators, and monitoring and management of the electric energy quality are achieved.

The invention discloses a wind generating set blade state intelligent monitoring system which comprises a plurality of sensors installed on a wind generating set blade, and the sensors are used for collecting stress, vibration and temperature data of the blade; the data processing module is used for receiving and processing data acquired by the sensor; the invention relates to the technical field of wind power generation. According to the method, the blade state can be monitored in real time, the fault features of the blade can be recognized in time, shutdown and maintenance cost caused by blade damage is reduced, the accuracy and timeliness of fault early warning can be effectively improved through fault prediction based on the artificial intelligence algorithm, and the fault early warning efficiency is improved through fault classification and early warning signals of different levels. According to the wind generating set remote monitoring system, workers can carry out maintenance in a more targeted mode, the overall maintenance cost is reduced, the remote monitoring platform can achieve unified monitoring and management on the multiple wind generating sets, and the overall operation efficiency is improved.

The invention discloses a power transmission and transformation project cost intelligent review method based on cost fluctuation characteristics, and relates to the technical field of intelligent review, and the method comprises the following steps: collecting historical cost data, preprocessing the data based on NACEMD, and recognizing power transmission and transformation project cost influence factors; judging main influence factors influencing the cost by adopting correlation analysis, and carrying out clustering analysis on different project types to obtain different types of power transmission and transformation project sample sets; on the basis of the historical cost data and the transmission and transformation project sample set, cost intervals of different types of costs of the transmission and transformation project are calculated through a Cheff-Snow ratio inequality for different types of costs, and fluctuation intervals of different types of costs are judged; corresponding intelligent methods are set for different types of fees, and based on prediction analysis of the three types of fees, evaluation standard determination of the power transmission and transformation project cost is realized through input of related project parameters. And the scientificity and accuracy of the review process are ensured through model selection for different fluctuation types.

The invention relates to the technical field of block chains, DID, data cross-border and data sharing, in particular to a security industry cross-border data sharing method and system based on a block chain and DID, and the method comprises the steps: S1, identity registration and authority distribution; s2, data release and contract release; s3, data receiving and contract execution; and S4, supervision auditing: each supervision party issues a supervision intelligent contract through a specified DID identity and a block chain account according to own business characteristics, and each participant participating in data sharing can select the supervision party needing submission, and triggers the corresponding intelligent contract to carry out flow data submission. The method has the advantages that the authenticity of the data in the data sharing process is ensured; digitalization, automation and standardization of a data sharing process are realized; constructing an on-chain identity system; the access and data uploading of the cross-border main body mechanism are facilitated, and the cross-border interaction of the data is facilitated; information errors are avoided, and execution efficiency and transparency of data sharing are improved.

The invention relates to the technical field of charging equipment management, and discloses a charging equipment intelligent management system and method, and the specific steps are as follows: constructing an intelligent management system comprising a charging station information unit, a charging equipment information unit and a user information unit, setting a charging equipment recommendation platform, and recommending a nearby charging station to a user. The method comprises the following steps: recording a search event of a user, collecting position information of a charging station, a use state of charging equipment and electric quantity data, dividing a monitoring area and monitoring search points to identify peak and low peak time periods, and executing a charging equipment supplement strategy and a charging station matching strategy to optimize distribution of the charging equipment and charging selection of the user. The method comprises the following steps: collecting search points of each monitoring area in a monitoring time period, executing a charging equipment supplement strategy, and in addition, executing a charging station matching strategy by a system according to personal information data collected in a peak time period.

The invention relates to a coupler system based on MECHATROLINK-III and a communication method, the system comprises a MECHATROLINK-III master station, a MECHATROLINK-III special cable, a MECHATROLINK-III coupler and a plurality of plug-in IO modules, the MECHATROLINK-III coupler is used for managing all the plug-in IO modules in a slot so as to carry out ordered IO input and output, and the plug-in IO modules are used for carrying out plug-in IO input and output. The communication module is used for carrying out communication interaction between IO data of the whole coupler system and a MECHATROLINK-III master station; and the MECHATROLINK-III coupler is integrated with a plurality of control units or execution units. The MECHATROLINK-III coupler has the advantages that the communication stability and the communication efficiency are guaranteed while the cost of the MECHATROLINK-III coupler system is reduced.

The invention relates to an efficient deployment method and system for a privatized large language model ecological service. The system comprises an evaluation module, an index collector, a monitoring module, a vLLM framework, a model cluster service module and a request distribution module. The evaluation module performs quantitative evaluation on the performance of the system under different hardware platforms; the index collector collects server cluster performance indexes, cluster resource states and load information in real time; the monitoring module is used for monitoring the server cluster; the vLLM framework dynamically allocates computing resources to realize management of a multi-modal server cluster, and performs unified management and scheduling through PM2 to realize multi-model efficient parallel task processing; a vLLM framework is started by the model cluster service module, and different large model instances are packaged in a Docker container; the request distribution module distributes external requests in a self-adaptive mode according to cluster resource states and load information fed back by the index collector in real time. Intelligent request distribution and dynamic load balancing are realized, and integration and efficient management of a multi-modal large language model are realized.

The invention discloses a mining plan making method and system, and relates to the technical field of automatic management, and the method comprises the steps: obtaining a mine image and environment data; extracting multi-dimensional features of the mine image, and fusing the multi-dimensional features to obtain fused features; inputting the fusion features into a recognition model to obtain a mineral recognition result; combining the environment data with the mineral identification result to form a mine environment-resource distribution map; and inputting the mine environment-resource distribution map into the mining model to obtain a mine mining plan. According to the mining plan based on machine vision and a large model, real-time and high-definition monitoring of the mine environment is achieved by integrating the high-precision camera shooting function and the advanced video processing technology, subjectivity and errors of manual judgment are reduced, the mining process is accelerated, optimal configuration and efficient utilization of resources are achieved, and the mining efficiency is improved. And higher production efficiency and economic benefits are brought to mine enterprises.

The invention discloses a big data system based on building industry multi-data source project information unification, and relates to the technical field of big data systems. The system comprises a data acquisition layer which is directly connected with an external data source and is responsible for acquiring data and providing original materials for subsequent processing; the data preprocessing and cleaning layer is used for receiving data input of the data acquisition layer and carrying out primary processing on original data; the data storage layer is used for receiving the data of the data preprocessing and cleaning layer, storing the cleaned data, providing a basis for data analysis and supporting the storage requirement of large-scale data; the data processing layer is used for directly reading the data of the data storage layer and deeply analyzing the stored data; the big data system provided by the invention solves the problem of project information management in the building industry through improvements in the aspects of data unified management, data integrated analysis, decision-making efficiency improvement, data security guarantee and the like, and brings better effects and positive influences.

The invention discloses an intelligent monitoring system for a transformer substation channel cover plate based on the Internet of Things, and relates to the technical field of transformer substations. The acquisition monitoring module is used for acquiring environment and state data of the channel cover plate in real time; the acquisition monitoring module is also used for converting the environment and state data of the channel cover plate into a transmission format; the network connection module is used for receiving the environment and state data of the channel cover plate after the transmission format is converted by the acquisition monitoring module; interconnection, intercommunication and remote management of equipment and sensors are achieved through the Internet of Things technology, and collection and transmission of the state, temperature, humidity and other data of the trench cover plate are achieved through the sensors. Data transmission and remote management between intelligent devices are realized, and finally data acquired by a sensor is processed and analyzed, so that state prediction and maintenance plan making are realized.