102results about How to "Guarantee fairness" patented technology

The invention provides a game platform management method and system based on artificial intelligence. The method belongs to the technical field of game platform management, and comprises the following steps: acquiring multi-source data through multiple channels, constructing a user portrait based on the acquired multi-source data, training the user data through a deep learning model, and identifying user preferences, habits and potential demands; the server load, the game popularity and the user distribution are monitored in real time, the game peak period is pre-judged through time sequence analysis based on historical data, and resource allocation is dynamically adjusted according to a prediction result; through collection and analysis of multi-source data, an accurate user portrait is constructed, and in combination with deep learning and an emotion analysis model, preferences, emotion changes and potential demands of the user can be identified and understood, so that personalized game recommendation, customer service and content pushing are provided.

The invention relates to the technical field of data fusion, in particular to a multi-source data fusion law enforcement record generation system and method, and the system comprises a data collection module which normalizes and eliminates repeated data, an anomaly detection module which carries out the data verification and cleaning, and an information source evaluation module which carries out the quantitative scoring of a data source. And the weight adjustment module dynamically adjusts the weight based on the score, and the data fusion module executes weight fusion and field verification and outputs a collaborative law enforcement record. According to the method, the data quality is further ensured through the verification of the data value range and the calculation of the deviation value, and the reliability of the data set is enhanced by removing the abnormal data. And through quantitative scoring and dynamic weight adjustment, the quality evaluation of the data source and the fairness of input are ensured, so that the law enforcement record is more comprehensive and authoritative. The refined data processing not only improves the accuracy of law enforcement records, but also enhances the security and integrity of information, thereby significantly improving the response speed and decision quality of a law enforcement agency.

The invention discloses an energy industry intelligent algorithm optimization method based on federal learning. The method comprises the following steps: S1, collecting and preprocessing local energy data; s2, acquiring and preprocessing expert example data; s3, constructing a comprehensive data set by applying a multi-modal data fusion technology; s4, each participant performs local model training on the comprehensive data set by using a federal adaptive optimization algorithm to generate local model update; s5, the central server aggregates local model updating to generate a global model; s6, applying a soft actor-commentator algorithm in the global model, and combining an inverse reinforcement learning technology to optimize an energy distribution strategy; s7, creating a virtual simulation environment by using a digital twinning technology, and testing and optimizing the performance of the global model; and S8, providing a user-friendly interface and a natural language processing interface, and realizing personalized energy management suggestions. According to the method, federated learning, a soft actor-commentator algorithm and an inverse reinforcement learning technology are combined, and an energy distribution strategy is optimized.

The invention relates to the technical field of medical behavior data monitoring, in particular to a medical insurance common outpatient service supervision system and method based on a fraud abnormal portrait technology, and the system comprises a medical transaction data collection module, a medical behavior analysis module, a risk assessment feedback module and a medical transaction database. According to the medical insurance ordinary outpatient service supervision system and method based on the fraud anomaly portrait technology, a more comprehensive risk assessment system is provided, and by means of an intelligent means, the medical object behavior anomaly risk, the medical institution behavior anomaly risk and the number of abnormal behavior overlapping cycles are comprehensively analyzed, so that the risk assessment efficiency is improved. According to the invention, the method achieves the precise recognition, early warning and prevention of fraud abnormal behaviors in a common medical insurance outpatient service, facilitates the improvement of the use efficiency of medical insurance funds, guarantees the fairness and sustainability of a medical insurance system, protects the benefits of a patient, maintains the fairness and efficiency of a medical system, and also facilitates the improvement of the management level and service quality of a medical institution.

The invention relates to the technical field of data processing and financial science and technology, in particular to an agent resource allocation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining the working state information and historical working information of a plurality of agents, generating a weight list of the plurality of seats according to the working state information and the historical working information; obtaining value evaluation information and remaining deadline information of a plurality of allocation objects in a resource pool, and generating an allocation sequence list of the plurality of allocation objects according to the value evaluation information and the remaining deadline information; and matching an allocation object for the seat according to the allocation sequence list and the weight list. According to the method and the device, the order grabbing pool algorithm for allocating the customer lists to the seats is provided, the insurance renewal pool lists are allocated by the algorithm through weight, evaluation and resource allocation, the business transaction rate is improved, the fairness and efficiency of allocation of the lists in the resource pool are guaranteed, and the efficiency and the quality of customer services are improved at the same time.

The invention relates to a grouping HotStuff Raft consensus mechanism construction method based on whole-process multi-dimensional dynamic reputation, and belongs to the technical field of block chains. Comprising the following steps: designing a node scoring mechanism of whole-process multi-dimensional dynamic reputation, and monitoring and evaluating the behavior and performance of each node in real time; designing a new cross grouping strategy, and grouping different nodes in the candidate node set; the nodes of each group are responsible for collecting transactions from the client and gathering the transactions to the grouped leader nodes of the group where the corresponding nodes are located; transactions of the grouped leader nodes in the HotStuff consensus stage are summarized, the transactions are quickly verified, a consensus is achieved, a client is informed that the transactions are linked, and the leader nodes in the Raft consensus stage distribute messages of achieving the consensus to the grouped leader nodes in the HotStuff consensus stage; and the grouped leader nodes in the HotStuff consensus stage return a consensus reaching message to the corresponding intra-group nodes. The method solves the problems that an existing consensus mechanism is low in throughput, insufficient in safety and high in consensus cost.

The invention relates to the technical field of employment management, in particular to a flexible employment management system based on a block chain and big data and a skill evaluation method. According to the invention, through autonomic skill label selection of the user and intelligent skill index generation, recommendation and matching are more accurately carried out on service supply and demand parties; according to the technical scheme, skill authentication information of a user is linked through the block chain technology, the skill authentication information comprises skill certificates and training experiences, the key problems of information asymmetry, non-transparent evaluation, low matching efficiency, insufficient right and interest guarantee and the like in a traditional system are effectively solved through combination of the block chain technology and the big data technology, and the user experience is improved. According to the flexible employment management system, a complete and coherent closed loop is formed from skill authentication to matching recommendation to right and interest guarantee and occupational development, the efficiency and fairness of a flexible employment market are greatly improved, and the sense of trust and the degree of participation of users are enhanced.

The invention discloses a shared parking method for real-time sharing adjustment and dynamic income optimization, and belongs to the technical field of shared parking system optimization. The problem that an existing shared parking method is low in parking space utilization rate is solved. According to the method, an owner can flexibly adjust the sharing state of the parking space according to actual requirements, modification in a common mode can be carried out, instant modification in an emergency situation is also supported, and personalized requirements are met. Different pricing modes are provided, meanwhile, an overtime pricing mechanism is introduced, when the vehicle owner parks in an overtime mode, the system can increase prices according to the overtime duration, the vehicle owner is motivated to leave on time, and the circulation efficiency of the parking space is ensured. According to the invention, a bidirectional credit evaluation mechanism is also introduced, the behavior of frequently modifying the parking space state by the owner and the overtime parking behavior of the owner are recorded and brought into a credit scoring system, the occurrence of improper behaviors is reduced, the fairness of the shared environment is ensured, and the win-win situation of both parties is realized. The method can be applied to optimization of the shared parking scheme.

The invention discloses a time-controlled fine-grained traceability method for large-scale supply chain data, and belongs to the technical field of fine-grained traceability processing. Comprising the following steps: constructing a large-scale supply system; initialization is carried out, and public parameters and a master key are generated; encrypting the user data; performing traceability processing on the encrypted user data; the user data is decrypted; and obtaining data. According to the method, an aggregation access control tree method is adopted, all attribute nodes of a user are included, a basic access strategy is adopted, fine-grained access control is achieved according to different attributes of the user, and the problem of calculation amount increased in the encryption and decryption process is effectively solved; the timeliness of the user permission is controlled by dynamically updating the access strategy, the fairness and the non-tampering property of access control are ensured by using the smart contract and the block chain timestamp verification, the access control problem oriented to different identities is solved, the access permission control of the time dimension is realized, and the privacy and the security of data are ensured.

The invention provides a method and system for improving bid evaluation accuracy, and relates to the technical field of bid evaluation, and the method comprises the steps: bid file data preprocessing including data cleaning and feature selection, bid insensitive learning model building and fusion, and real-time fusion model performance evaluation including fairness constraint, cross validation and bid detection. Updating according to an evaluation result, substituting the feature information to calculate a bid evaluation score, adding an expert review mechanism to adjust the score, and archiving a final bid evaluation score; according to the method, the labor cost is reduced through a rule calculation engine, the scoring accuracy and generalization ability are improved through data cleaning and other technologies, expert review and fairness constraint are introduced to guarantee fairness, review traceability is guaranteed through an archiving result, project decision is supported, and the bid evaluation accuracy is improved through multiple innovation strategies.

The invention discloses a financial comprehensive auditing method and system, and the method comprises the steps: deploying a financial smart contract on a block chain, carrying out the modular design of the smart contract, and enabling each sub-module to correspond to a department; configuring an auditing rule template for each sub-module, and customizing auditing rules by corresponding departments based on the auditing rule templates; analyzing auditing rules of all departments based on a decision tree algorithm, and generating auditing check points; based on an intelligent contract event monitoring mechanism, auditing check points of all departments are monitored in real time, when a detection event does not accord with a corresponding auditing rule, early warning is carried out, and an auditing report is generated; the audit report is analyzed regularly, audit rules of all departments are updated based on analysis results, and the audit rules are encrypted and deployed on the block chain; and comprehensively auditing the finance of each department based on the updated auditing rule. According to the invention, high efficiency, flexibility and safety of financial auditing are realized through technical means of modular design, version control, real-time monitoring, data analysis and the like.

The invention discloses a task scheduling system and method of a content distribution network, a medium, equipment and a product. The task scheduling system comprises a task storage module used for storing domain name configuration tasks into domain name task queues according to domain names in the domain name configuration tasks, and one domain name task queue is used for storing the domain name configuration tasks corresponding to the same domain name; and the task scheduling module is used for determining a target task queue according to the priority of the domain name corresponding to each domain name task queue, and issuing the target configuration task in the target task queue to the content distribution network system. By setting exclusive task queues of domain names of different users, a basis is provided for reasonable domain name configuration task scheduling of the content distribution network, the fairness of task scheduling of the content distribution network is guaranteed, long-time accumulation of domain name configuration tasks of the content distribution network of individual users is avoided, and the user experience is improved. And certain priority scheduling can be realized based on the priority of each domain name task queue, so that the user experience is further improved.

The invention relates to the technical field of keyword filtering, and discloses a multi-channel vocabulary filtering method. Obtaining filtering system target information or filtering system requirement information, and generating a filtering word library according to the filtering system target information or the filtering system requirement information; acquiring sample data, and preprocessing the sample data; selecting a natural language processing model and an image / video recognition model according to the filtering system target information or the filtering system requirement information, and training the natural language processing model and the image / video recognition model by using the sample data; obtaining to-be-detected text information, and performing context and semantic analysis on the to-be-detected text information through the natural language processing model to generate analysis result information; sending the analysis result information to a manual auditing terminal, and obtaining auditing result information of the manual auditing terminal; obtaining filtering vocabulary updating information, and updating the filtering word library according to the filtering vocabulary updating information; the method has the advantages of low false alarm rate and high accuracy.

The invention belongs to the technical field of labor tool management, and particularly relates to a multifunctional labor tool operation management system, which comprises an acquisition module, a PCBA (Printed Circuit Board Assembly) module, a wear detection module, a service life prediction module and a work quality analysis module, according to the invention, authority management is carried out through the RFID card reading unit, in-place and integrity detection is carried out on the labor tool by using the micro contact switch and the electric conduction contact reed, the state of the labor tool is monitored through the Internet of Things detection unit, and data transmission is realized through wireless communication, so that safe use and management of the labor tool are ensured; by configuring the wireless data transmission unit, the working state and the state of the labor tool are displayed in real time, the intuition and the effectiveness of management are further improved, the use permission, the in-place state and the integrity of the labor tool are effectively managed, and safe use of the labor tool is guaranteed.

The invention relates to a three-camera linkage and intelligent evaluation eight-brocade intelligent scoring system based on machine learning and a sum-product method. In an eight-section brocade scoring scene, a traditional subjective scoring mode has many defects. In order to solve the problems, an intelligent scoring system is constructed. The system comprises a video data acquisition module, a posture recognition module, an intelligent scoring module, a score integration module and the like. The video data acquisition module acquires multi-angle videos through three high-definition cameras; the posture recognition module accurately recognizes actions by using an advanced algorithm and a deep neural network technology; the intelligent scoring module designs a multi-dimensional index, and scores based on a sum-product algorithm; and the score integration module gathers scores from different perspectives to obtain a comprehensive score. According to the method, various measures are adopted to overcome the limitation of the existing AI technology in sports detection, including environment optimization and action detail identification, construction of a diversity and balance data set, research of cross-group adaptability, establishment of a man-machine cooperation trust relationship and the like. The system improves objectivity, accuracy and fairness of eight-segment brocade scoring, and is of great significance to eight-segment brocade teaching and competition. Meanwhile, a new technical means is provided for the fields of physical education and detection, the application range of the artificial intelligence technology in the field of physical education is expanded, and fusion innovation of the AI technology and the traditional field is promoted.

The invention relates to the field of bidding and tendering data supervision, and discloses a bidding and tendering supervision system for an engineering project, comprising a data acquisition module for acquiring bidding and tendering data, a bidding and tendering data supervision module comprising: a time sequence construction module for acquiring time sequence data of the bidding and tendering data, obtaining similarity ontology features based on the time sequence data; the time sequence management module is used for creating a time sequence feature matrix based on the similarity ontology features, extracting periodic data point features from the time sequence feature matrix, and separating the periodic data point features by using a time sequence decomposition algorithm to obtain periodic data points; and the anomaly analysis module is used for constructing an anomaly analysis model, inputting the periodic data points into the anomaly analysis model, obtaining an anomaly score of each periodic data point, automatically detecting the abnormal data points through a machine learning model, and distributing the anomaly score for each periodic data point, so that the workload of manual examination is reduced.

The invention provides an examination room digital twinning and intelligent identification system based on a visual large model, and the system comprises the steps: carrying out the digital twinning mapping through a digital twinning mapping module, and obtaining a digital twinning virtual examination room; object behavior actions in the digital twin virtual examination room are captured through a violation judgment module, and an examination room monitoring array is constructed; extracting behavior constraint features of the digital twin virtual examination room based on the examination room monitoring array, and scoring the behavior constraint features through machine learning; when the behavior constraint score is lower than a preset threshold value, the object behavior action is compared with a preset illegal behavior standard, and illegal behavior judgment is achieved; after the violation recording and archiving module judges that violation information exists, corresponding violation video clips are returned to the system interaction interface, and the violation video clips are automatically uploaded to the cloud storage center for archiving, so that abnormal recognition and evidence retention of examinee behaviors are realized, the examination safety is improved, and remote examination room situation comprehensive control is realized.

The invention relates to the technical field of auxiliary bid evaluation, in particular to an auxiliary bid evaluation system and method based on intelligent expert management, and the system comprises a project information collection and processing module which is used for collecting bid evaluation time limit characteristics and project data information of a to-be-evaluated project, and carrying out the word segmentation of the project data information, obtaining a project representation phrase set; the bid evaluation time limit matching module is used for traversing in a bid evaluation expert database according to the bid evaluation time limit characteristics, screening out bid evaluation experts matched with the bid evaluation time limit characteristics, and marking the bid evaluation experts as first-order bid evaluation experts; the benefit conflict detection module is used for screening all the first-order bid evaluation experts by utilizing a pre-introduced conflict detection mechanism, rejecting the first-order bid evaluation experts having a benefit relationship with the to-be-evaluated item, and marking the remaining first-order bid evaluation experts as second-order bid evaluation experts; the system can improve the quality and efficiency of the overall bid evaluation work.

The invention discloses an assessment method and system combining a language model and a virtual technology, and the method comprises the following steps: drilling a police and people dialogue process, analyzing the drilling language output of a subject through a first language model, and obtaining a drilling analysis result; obtaining a drill score of the subject based on the drill analysis result; when the drill score of the subject meets a preset score requirement, obtaining an assessment permission; based on the examination permission, combining a virtual technology to construct police and people dialogue scene questions; the subject is assessed based on the police and people dialogue scene questions, and assessment language output is obtained; and analyzing the assessment language output by adopting a second language model to obtain an assessment evaluation report of the subject. According to the method and the system, the language model is combined with the virtual technology, so that the more advanced and efficient assessment method and system are constructed, and the assessment quality and effect are improved.

The invention relates to a camera control priority regulation and control system and method, belongs to the field of camera holder control, and aims to solve the problem of scrambling of camera control in the prior art. The priority is distributed and stored when the user creates an account; when the camera is requested to be controlled, the system intercepts and checks whether there is a controller by using the AOP technology. When no controller exists, direct authorization is carried out; and when there is a controller, determining whether to switch the control right or add the user into the waiting queue according to the priority. According to the invention, through the modular design, the efficiency and fairness of controlling the camera by multiple users are optimized. The system ensures reasonable distribution and rapid circulation of control rights by distributing user priorities, processing requests by using an AOP technology, an intelligent countdown locking mechanism and a dynamic queuing queue.

The utility model discloses a tire with easy-to-determine starting time and a management system. An anti-transfer electronic tag is fixed in an easy-to-wear area of the tire. The management system comprises a tire of which the starting time is easy to determine, an electronic tag identification terminal provided with a program, and an internet server provided with a program, wherein the internet server and the electronic tag identification terminal are in data interconnection; and when the electronic tag identification terminal scans the anti-transfer electronic tag, the scanning time is recorded in a management system database of the Internet server and is used for calculating the tire use time. The time difference between the time when the tire has the quality problem or the time when the tire stops using and the tire starting time is determined as the actual using time of the tire. And charging according to the actual use time of the tire. The system reduces the indirect transaction cost, is very low in direct use cost, and is suitable for large-scale popularization. The method is applied to the tire industry with huge yield and is economical and practical.

The invention discloses an electronic file management system assisted by a block chain, and relates to the technical field of auxiliary file management, and the system achieves the omnibearing management and intelligent processing of file evidence through the organic combination of a collection unit, a recognition unit, an evaluation unit, an early warning unit, a strategy unit, a block chain storage unit and other modules. The acquisition unit is responsible for collecting file information and corresponding evidence data and cleaning and preprocessing the file information and the corresponding evidence data; the recognition unit is used for recognizing and analyzing evidences in different forms through character recognition, video processing and voice recognition technologies; the evaluation unit evaluates the identification result to generate a corresponding evaluation result; the early warning unit sends out an early warning instruction when the evaluation result does not reach the standard; the strategy unit generates a corresponding strategy according to the evaluation result and executes the strategy; and the block chain storage unit is responsible for archiving qualified file evidence data on a block chain to ensure the security and non-tampering of the data.

The invention discloses a delivery control system and method based on a large model and a sound cloning technology, and relates to the technical field of text delivery. Texts needing to be delivered in history are classified, a template of each text is generated, and a template database is constructed; inputting user data into the text template to automatically generate a delivery text, and constructing a text generation large model; selecting the receiving channel with the highest comprehensive efficiency as a conveying channel, processing the text according to the type of the conveying channel, and conveying the text to a delivery target; generating an evidence chain by using the data in the delivery process, and judging whether the delivery task is successful or not according to the generated evidence chain; carrying out secondary conveying by utilizing the optimized conveying channel, and carrying out secondary judgment on a conveying task; and communicating with the delivery target by using the personalized voice, explaining the text content to the delivery target, and performing opinion feedback after the delivery target clarifies the text content.

The invention provides an industrial Internet of Things hierarchical access control method and system based on a block chain. The method comprises the steps that a data owner and a data user register in the block chain and an identity authority node, and an identity sequence is obtained after verification; the data owner encrypts data by using the main private key and the identity sequence, stores the data in an out-of-chain module, and uploads related information to the block chain; and the data user applies for data access to the block chain, obtains a data ciphertext address after the judgment is passed based on an access strategy, decrypts the data by using an identity private key based on identity level verification to obtain the data, and performs integrity verification. According to the method, the authenticity and reliability of the user identity are ensured through dual verification of the block chain and the identity authority node; in the stage of acquiring the ciphertext by the data user, the illegal intrusion of the unauthorized user is further limited by using a dual protection mechanism of a data access strategy and user identity comparison, so that the confidentiality and integrity of the data are ensured, and the security and access efficiency of the industrial Internet of Things system are improved.

The present invention relates to the field of blockchain technology and electric vehicle charging scheduling technology, and specifically to an orderly charging guidance method and system for electric vehicles based on blockchain smart contracts. Electric vehicle users submit charging demand parameters to the charging platform, and the blockchain system obtains the distance between the user and each charging station through a commercial map interface to form a set of charging stations accessible to electric vehicle users and a distance matrix. The charging station nodes take turns to call the orderly guidance model constructed in the smart contract to solve, obtain a recommended set of charging stations, and store the calculated data in the blockchain system through a consensus mechanism. The present invention combines blockchain technology, introduces a fairness index, limits the volatility of single-pile revenue, provides users with a set of charging stations through a user selection model and an orderly charging guidance model, ensures the fairness of the revenue distribution of charging station operators, and improves user charging utility.

The invention discloses a coordinated scheduling method and device for a multi-energy complementary system, and a storage medium. The method comprises the steps of obtaining pre-scheduling data of multiple historical periods and pre-scheduling data of a next period chained on multiple target nodes in the multi-energy complementary system from a block chain; wherein the pre-scheduling data is data obtained by predicting power supply and demand conditions of all subjects in the multi-energy complementary system in each time period by a plurality of target nodes by using respective prediction models; the plurality of target nodes comprise a photovoltaic node, a wind power node, a thermal power node, an energy storage node and a power grid electricity purchasing node; determining scheduling data of all main bodies in the multi-energy complementary system in the next time period based on the pre-scheduling data of the plurality of historical time periods and the pre-scheduling data of the next time period; and uploading the scheduling data to the block chain, and performing coordinated scheduling on the power resources of the plurality of target nodes according to the scheduling data in the next time period.

The present invention discloses a fast consensus method and system for identity authentication based on blockchain, including: obtaining user identity information of blockchain network; encrypting the user identity information using an improved encryption variant algorithm to generate a digital identity certificate; building an improved identity consensus signature framework by closely combining multiple Schnorr signature technology with blockchain consensus mechanism; introducing an optimized consensus algorithm to realize the special needs of identity authentication under multi-entity secure access to shared resources; introducing an adaptive intelligent dynamic weight distribution system to identify the user identity information; and encrypting and protecting it through an advanced encryption algorithm of the Sovrin architecture. The present invention not only realizes technical innovation through the improved algorithm, but also brings significant improvements in practical applications, meeting the needs of modern digital society for efficient, secure and scalable identity authentication solutions.

The invention provides a tone quality evaluation system, a tone quality evaluation method and a medium. The tone quality evaluation system comprises a control unit, a conveying unit and a plurality of samples to be tested, the control unit is used for determining a current evaluation sample from the plurality of to-be-tested samples based on the random evaluation sequence, and performing sound quality evaluation operation on the current evaluation sample; under the condition that a sample switching instruction is received, taking the next to-be-tested sample of the current evaluation sample as the current evaluation sample based on the random evaluation sequence, and returning to execute the tone quality evaluation operation; the tone quality evaluation operation comprises the steps of controlling the transmission unit to transmit the current evaluation sample to the evaluation point position, and controlling the current evaluation sample to play the evaluation audio after the transmission is completed. According to the tone quality evaluation system, the tone quality evaluation method and the medium provided by the invention, subjective prejudice of evaluation personnel caused by a sample sequence is effectively reduced through a random evaluation sequence. The evaluation efficiency is remarkably improved through automatic sample switching and conveying operation, and delay and personal errors caused by manual operation are avoided.

The invention discloses an assessment construction method based on artificial intelligence, and belongs to the technical field of workplace training assessment, and the method comprises the steps: S10, generating question data information according to the historical training content of an industry, generating a knowledge base based on the question data information, and generating assessment test paper based on the knowledge base; s20, collecting knowledge point features of the industry historical training content, distinguishing the knowledge point features, and obtaining relevance between examination questions in the examination paper and the knowledge point features; s30, obtaining the number of persons participating in the examination, obtaining the score number of each person participating in the examination, collecting the highest score and the median score in the score number, and checking the difficulty of the examination paper based on the highest score; according to the method, knowledge points and features of industry historical training are obtained, and test paper examination questions generated during historical training examination are collected, so that the knowledge base is deeply integrated and constructed, examination test paper can be intelligently generated in a future time period, the burdensome manual question setting burden of a trainee is relieved, and the question setting efficiency is improved.

The invention discloses an intelligent mine unattended system and method, and relates to the technical field of mining, and the system comprises a vehicle information intelligent recognition module which is used for automatically capturing and verifying vehicle information before a vehicle arrives at a wagon balance, and automatically releasing the vehicle to enter a weighing area after the vehicle is confirmed to be correct; and the automatic weighing operation module is used for enabling the vehicle to be stably parked on an unattended weighing platform, enabling the system to automatically start a weighing program, and rapidly capturing and displaying weight data. Real-time monitoring and data management of the weighing process can be intelligently realized, an intelligent identification technology (such as license plate identification and RFID) and a monitoring system are integrated, cheating behaviors in the weighing process are prevented, the transaction fairness is ensured, in-and-out route planning, remote monitoring, data encryption and intelligent analysis are realized, and in-and-out route planning, remote monitoring, data encryption and intelligent analysis are realized. Seamless integration of weighing data and other management systems is realized, automatic circulation and sharing of data are realized, and data query, analysis and decision support are facilitated.