Motor vehicle detection remote supervision system

Abstract

The invention discloses a remote supervision system for motor vehicle detection, and relates to the technical field of motor vehicle detection, and the system comprises a detection data collection module which employs a multi-type sensor array to collect tail gas emission, vehicle speed, braking, light and axle load data at a detection line, and transmits the data to a data collection unit for caching through a high-speed wired network; the data encryption transmission module is used for encrypting data through a national cryptographic algorithm, transmitting the data to a remote supervision center through a wireless network or a VPN network, and authenticating the data through a digital certificate during transmission; the remote supervision center module is used for processing, analyzing and verifying data by a high-performance server cluster and storing the data in a distributed database; and the intelligent analysis and early warning module analyzes the data by using big data and an artificial intelligence algorithm, and pushes early warning in multiple modes when abnormity occurs. According to the invention, the supervision efficiency and precision are improved, multiple types of sensors and an intelligent identification technology ensure accurate and standard detection, guarantee data security and reliable encryption transmission and distributed storage, and can early warn risks in time and optimize the management of a detection mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of motor vehicle detection, and in particular to a motor vehicle detection remote monitoring system. Background Art

[0002] With the continuous growth of the number of motor vehicles, motor vehicle inspection plays a vital role in ensuring road traffic safety and controlling environmental pollution. The traditional motor vehicle inspection and supervision model mainly relies on manual on-site supervision and paper records. This method has many drawbacks and is difficult to adapt to the needs of modern traffic management.

[0003] In the traditional model, supervisors need to be present at the inspection site for supervision, which not only consumes a lot of manpower, material resources and time, but also has low supervision efficiency. Due to the subjectivity and limitations of manual supervision, it is difficult to achieve comprehensive and real-time monitoring of the inspection process, which is prone to violations such as inspection cheating and data falsification. For example, some inspection agencies may modify the inspection data in the exhaust emission inspection by improper means in pursuit of economic interests, so that vehicles exceeding the standard can pass the inspection, which causes serious pollution to the environment and endangers public health.

[0004] At the same time, paper-based inspection data is inconvenient to store and manage, difficult to query and count, and poorly shareable, which makes it impossible to provide timely and accurate data support for traffic management departments, and is not conducive to the analysis and decision-making of the overall status of motor vehicles. In addition, the traditional supervision model lacks effective data analysis and early warning mechanisms, making it difficult to timely discover abnormal trends and potential risks in inspection data, and unable to achieve dynamic management and precise control of motor vehicle inspection quality.

[0005] With the rapid development of information technology, especially the widespread application of emerging technologies such as big data, artificial intelligence, and the Internet of Things, new opportunities and solutions have been provided for remote supervision of motor vehicle inspections. The use of sensor technology can realize the automatic collection and real-time transmission of motor vehicle inspection data, improving the accuracy and timeliness of data; the encryption transmission technology can ensure the security and confidentiality of data during network transmission; with the help of big data analysis and artificial intelligence algorithms, it is possible to conduct in-depth mining and intelligent analysis of massive inspection data, timely detect abnormal situations and issue early warnings; high-definition cameras and intelligent image recognition technology can monitor the entire inspection process and standardize the operating behavior of inspection personnel; and the establishment of a complete inspection agency management module will help to achieve standardized and standardized management of inspection agencies and improve the quality of inspection services.

[0006] Therefore, the development of a motor vehicle inspection remote supervision system based on advanced technology has important practical significance. It can effectively improve the level of motor vehicle inspection supervision, ensure the fairness, accuracy and reliability of motor vehicle inspection work, and promote the sustainable development of the transportation industry. Summary of the invention

[0007] The present invention proposes a motor vehicle detection remote monitoring system to solve the problems mentioned in the above-mentioned prior art.

[0008] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a motor vehicle detection remote supervision system, comprising: Detection data acquisition module: It uses a multi-type sensor array and is installed on the motor vehicle inspection line to collect various vehicle inspection data, including exhaust emission data, vehicle speed data, braking performance data, light intensity data, and axle weight data. The exhaust emission sensor uses electrochemical sensor and infrared sensor fusion technology to detect multiple pollutants at the same time; the vehicle speed sensor uses the laser Doppler speed measurement principle; the braking performance sensor is a combination of a pressure sensor and a displacement sensor; the light intensity sensor uses a photodiode array; and the axle weight sensor uses a strain gauge sensor; The sensor and data acquisition unit are connected via a high-speed wired transmission network. The data acquisition unit has a real-time data cache function to capture dynamic data changes during vehicle detection. Data encryption transmission module: performs real-time encryption processing on the collected detection data, adopts national encryption algorithm, including SM4 encryption algorithm to encrypt the data, and the encryption key length is 128 bits; The encrypted data is transmitted to the remote monitoring center via a wireless communication network or a dedicated virtual private network VPN. The wireless communication module supports multi-band adaptive switching; Remote monitoring center module: equipped with a high-performance server cluster, the server uses Intel Xeon series multi-core processors; The data analysis and processing software runs on the server, which decrypts, analyzes and verifies the encrypted data. The analyzed data is stored in the database according to the vehicle inspection items. The database adopts a distributed storage architecture, including the Hadoop distributed file system. Intelligent analysis and early warning module: Based on big data analysis technology and artificial intelligence algorithms, it conducts real-time analysis of the detection data stored in the database, and uses deep learning algorithms, including convolutional neural networks, to build an abnormal detection model for vehicle detection data, including normal vehicle detection data and various types of faulty vehicle detection data; When abnormal vehicle detection data is detected, the system automatically generates warning information, which is pushed to the supervisor's terminal in a variety of ways; Inspection process monitoring module: A high-definition camera array is installed on the motor vehicle inspection line, which has night vision and intelligent image recognition functions. It can capture the key links of the vehicle inspection process in real time, including appearance inspection and online inspection, and automatically identify the vehicle model, license plate number, and inspection personnel's operating behavior information through image recognition technology; The video data collected by the camera is transmitted to the remote monitoring center in real time through the network, and the supervisor can view the video of the detection process in real time through the monitoring terminal; Testing agency management module: establish a testing agency information management database to store the basic information, personnel information, and equipment information of the testing agency. The database has data update and query functions; The testing business process of the testing agency is monitored and managed in real time. According to the testing standards and specifications, the testing agency's testing sequence, execution of testing items, timeliness of testing data upload, etc. are automatically checked and compared. When it is found that the testing agency has violated the regulations or does not comply with the testing process, the system automatically records the violation and generates a rectification notice.

[0009] Furthermore, the sensor array in the detection data acquisition module has an automatic calibration function. The calibration process uses a standard source for comparison, and the calibration data is automatically recorded and uploaded to the remote monitoring center.

[0010] Furthermore, during the data transmission process, the data encryption transmission module uses digital certificate technology to authenticate the identity of the data sender and receiver.

[0011] Furthermore, the intelligent analysis and early warning module in the remote supervision center module has self-learning and self-adaptation capabilities, and the model optimization cycle does not exceed 1 month.

[0012] Furthermore, the high-definition camera array in the inspection process monitoring module uses intelligent tracking technology to automatically track the moving position of the vehicle on the inspection line.

[0013] Furthermore, the testing agency management module has the function of automatic review of testing reports. According to the preset review rules and standards, the testing reports uploaded by the testing agency are automatically reviewed. The review content includes the rationality of the test data, the completeness of the test items, and the accuracy of the conclusions. The review time does not exceed 5 minutes, and the review results are automatically fed back to the testing agency. For reports that fail the review, the testing agency needs to modify them and re-upload them for review.

[0014] Furthermore, a method for applying a motor vehicle detection remote supervision system comprises the following steps: Data collection step: by installing a multi-type high-precision sensor array on the motor vehicle inspection line, various vehicle inspection data are collected according to claim 1, including exhaust emissions, vehicle speed, braking performance, light intensity, and axle weight data. The sensor collects data in real time and transmits it to the data acquisition unit; Data encryption and transmission step: after receiving the sensor data, the data acquisition unit encrypts the data using the national secret algorithm as described in claim 3, adds a digital certificate for identity authentication, and then transmits the encrypted data to the remote monitoring center via a wireless communication network or a dedicated VPN; Data parsing and storage step: after receiving the encrypted data, the remote monitoring center uses the data parsing and processing software on the server to decrypt, parse and verify the data according to claim 1, and stores the parsed data in a distributed database according to the classification of vehicle inspection items; Intelligent analysis and early warning step: The intelligent analysis and early warning module performs real-time analysis on the detection data stored in the database based on big data analysis technology and artificial intelligence algorithms as described in claim 4, and uses the trained anomaly detection model to identify abnormal patterns and potential risks in the data. When an abnormality is detected, it generates early warning information as described in claim 1 and pushes it to the supervisor terminal; Inspection process monitoring step: using a high-definition camera array installed on the inspection line to shoot a video of the vehicle inspection process in real time according to claim 5, using intelligent image recognition technology to automatically identify vehicle and inspection personnel information, and transmitting video data to a remote monitoring center, and the supervisory personnel viewing the monitoring video in real time through the monitoring terminal according to claim 1; Testing agency management step: The testing agency management module establishes a testing agency information management database as described in claim 6, stores and manages testing agency related information, monitors the testing agency business process in real time, generates rectification notices for violations and tracks rectification status, and automatically reviews the testing report.

[0015] Furthermore, in the data collection step, the sensor array performs a pre-detection before the vehicle enters the detection line to check whether the sensor is working normally. If a sensor failure is found, the system automatically alarms and prompts to replace the sensor.

[0016] Furthermore, in the intelligent analysis and early warning step, after the early warning information is pushed to the supervisor's terminal, the supervisor analyzes the abnormal data through the analysis tool of the remote supervision center, checks the data trend, compares the historical data, and assists in determining the cause of the abnormality. The analysis tool has data visualization functions, including line graphs, bar graphs, and scatter graphs.

[0017] Furthermore, in the testing agency management step, remote random inspections are carried out on the testing equipment of the testing agency on a regular basis. Standard sample inspections are carried out by remotely controlling the testing equipment, and the test data are obtained and compared with the standard values ​​to evaluate the accuracy and reliability of the testing equipment. The inspection frequency is once a month.

[0018] Compared with the prior art, the present invention has the following beneficial effects: Automatically collect test data through multi-type high-precision sensor arrays, avoiding the errors and subjectivity of manual testing. The data collection is comprehensive and accurate, such as the exhaust emission detection accuracy of ±0.01ppm. Combined with intelligent image recognition technology to monitor the testing process, it can accurately identify vehicle and test personnel information to ensure the standardization of the testing process. It can monitor multiple testing stations in real time, and supervisors do not need on-site supervision, which greatly improves the efficiency of supervision and effectively prevents cheating in testing and data falsification.

[0019] Data encryption transmission uses national secret algorithms and digital certificate authentication to ensure data confidentiality, integrity and authenticity, and prevent data leakage and tampering. The distributed storage architecture ensures reliable data storage and facilitates query statistics, providing strong support for long-term data analysis, helping traffic management departments to accurately grasp the overall status of motor vehicles and provide a scientific basis for decision-making.

[0020] Intelligent analysis based on big data and artificial intelligence algorithms can quickly and accurately identify abnormal patterns in test data, discover potential risks in advance, such as potential safety hazards of vehicles or excessive emissions, and push early warning information in a timely manner so that supervisors can handle it quickly. The testing agency management module automatically reviews test reports, finds problems in a timely manner and requires rectification to ensure the quality of testing.

[0021] Establish an information database of testing institutions, realize all-round management of testing institutions, standardize business processes, and improve service quality. Regularly conduct remote sampling of testing equipment to ensure the accuracy and reliability of equipment, prompt testing institutions to improve their technical level and management capabilities, and promote the healthy development of the entire motor vehicle testing industry.

[0022] It helps to ensure that motor vehicles on the road have good performance and meet emission standards, reduce potential traffic accidents and environmental pollution, create a safer and more environmentally friendly traffic environment for the public, and improve public satisfaction with traffic management departments, with significant social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic block diagram of a motor vehicle detection remote supervision system proposed by the present invention; Figure 2 The present invention is a schematic block diagram of a motor vehicle detection remote supervision method. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0026] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0027] Reference Figure 1-Figure 2 :A motor vehicle detection remote supervision system, comprising: Detection data acquisition module: It uses a multi-type high-precision sensor array, which is installed at key positions on the motor vehicle inspection line to collect various vehicle inspection data, including but not limited to exhaust emission data, vehicle speed data, braking performance data, light intensity data, axle weight data, etc. The exhaust emission sensor uses electrochemical sensor and infrared sensor fusion technology to simultaneously detect multiple pollutants such as carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), particulate matter (PM), etc., with a measurement accuracy of ±0.01ppm; the vehicle speed sensor uses the laser Doppler speed measurement principle, with a measurement accuracy of ±0.1km / h; the braking performance sensor is a combination of high-precision pressure sensor and displacement sensor, with a pressure measurement accuracy of ±0.01MPa and a displacement measurement accuracy of ±0.1mm; the light intensity sensor uses a photodiode array to accurately measure the intensity and light type of different lights, with a measurement accuracy of ±10cd; the axle weight sensor uses a strain gauge sensor with a measurement accuracy of ±1%.

[0028] The sensor and data acquisition unit are connected via a high-speed wired transmission network (such as Gigabit Ethernet). The data acquisition unit has a real-time data caching function with a cache capacity of no less than 1GB to ensure that data is not lost in the event of network failure or data transmission abnormality. The data acquisition frequency is 1kHz-10kHz, which can accurately capture dynamic data changes during vehicle detection.

[0029] Data encryption transmission module: The collected detection data is encrypted in real time, and the national secret algorithm (such as SM4 encryption algorithm) is used to encrypt the data. The encryption key length is 128 bits. Efficient encryption operations are achieved through hardware encryption chips to ensure the confidentiality of data during transmission.

[0030] The encrypted data is transmitted to the remote monitoring center through a wireless communication network (such as a 5G network) or a dedicated virtual private network (VPN). The wireless communication module supports multi-band adaptive switching to ensure stable transmission in different signal environments. The transmission rate is not less than 100Mbps, and the network transmission delay is no more than 50 milliseconds, ensuring the real-time nature of the data.

[0031] Remote supervision center module: equipped with a high-performance server cluster. The server uses a multi-core processor (such as Intel Xeon series processors with no less than 16 cores), a memory capacity of no less than 128GB, and has powerful data processing capabilities. It can process massive detection data from multiple detection stations at the same time.

[0032] Data parsing and processing software runs on the server, which can quickly decrypt, parse and verify the encrypted data to ensure the integrity and accuracy of the data. The parsed data is stored in the database according to the vehicle inspection items. The database adopts a distributed storage architecture (such as Hadoop distributed file system) with high reliability and scalability, and can store at least 10 years of inspection data history.

[0033] Intelligent analysis and early warning module: Based on big data analysis technology and artificial intelligence algorithms, it conducts real-time analysis of the detection data stored in the database, and uses deep learning algorithms (such as convolutional neural networks) to build a vehicle detection data anomaly detection model. The number of model training samples is no less than 100,000 groups, covering normal vehicle detection data and various types of faulty vehicle detection data. By learning from historical data, it can automatically identify abnormal patterns and potential risks in vehicle detection data; Introducing an improved formula It is used to evaluate the abnormality of vehicle detection data, where E is the abnormality evaluation value, n is the detection data dimension, and D i is the actual detection value of the i-th dimension, M i is its normal mean, w i is the dimension weight, m ​​is the number of detection item categories, and pj is the abnormal penalty factor, F j It is an abnormal sign of the project.

[0034] When abnormal vehicle detection data is detected, that is, the E value meets the warning condition, E≥ T1, and T1 is the mild warning threshold, the system automatically generates warning information. The warning information includes vehicle information (license plate number, frame number, etc.), detection items, abnormal data values, warning levels (divided into mild, moderate, and severe), etc. The warning information is pushed to the supervisor terminal through various methods, such as SMS push, mobile APP push, email push, etc. The push time does not exceed 10 seconds to ensure that the supervisor obtains the warning information in time and takes corresponding measures.

[0035] Inspection process monitoring module: A high-definition camera array is installed on the motor vehicle inspection line. The camera resolution is not less than 1080p, the frame rate is 25fps, and it has night vision and intelligent image recognition functions. It can capture the key links in the vehicle inspection process (such as appearance inspection, online inspection, etc.) in real time, and automatically identify vehicle model, license plate number, inspection personnel's operating behavior and other information through image recognition technology. The image recognition accuracy rate is not less than 95%.

[0036] The video data collected by the camera is transmitted to the remote monitoring center in real time via the network. Supervisors can view the detection process video in real time through the monitoring terminal. The monitoring terminal supports functions such as simultaneous display of multiple screens, video playback, and screenshots. Supervisors can switch to view the video images of different detection stations at any time as needed. The video transmission delay does not exceed 100 milliseconds, ensuring the real-time and effectiveness of monitoring.

[0037] Testing agency management module: Establish a testing agency information management database to store basic information of the testing agency (such as agency name, address, legal person, qualification certificate, etc.), personnel information (list of testing personnel, qualification certificate, training records, etc.), equipment information (list of testing equipment, calibration records, maintenance records, etc.). The database has data update and query functions, and supervisors can query and update relevant information of the testing agency at any time; Real-time monitoring and management of the testing business process of the testing agency. According to the testing standards and specifications, automatic inspection and comparison are carried out on the testing sequence, execution of testing items, and timeliness of uploading testing data of the testing agency. When it is found that the testing agency has violated the regulations or does not comply with the testing process, the system automatically records the violation and generates a rectification notice. The rectification notice is automatically sent to the terminal of the testing agency manager through the system, requiring the testing agency to rectify within a time limit and tracking the rectification status to ensure that the testing agency carries out the testing work in strict accordance with the specifications; Specifically: Introduce the formula , C represents the comprehensive compliance assessment value of the testing organization, which is used to measure the overall compliance level of the testing organization; k represents the key link category of the testing business process, k=1 represents the testing sequence, k=2 represents the execution of the testing items, and k=3 represents the timeliness of uploading the testing data; a k represents the weight of the kth key link category in the compliance assessment; Q k represents the compliance score corresponding to the kth key link category; l represents the violation type category; b l represents the penalty coefficient of the lth violation type in the comprehensive evaluation; P l Indicates the number of times the lth violation type occurs within a certain period of time; By establishing a testing agency information management database, the system can obtain detailed information on all aspects of the testing agency and provide basic data for evaluating its compliance.

[0038] For the monitoring and management of the testing business process, when evaluating the compliance of the testing sequence, if the testing agency conducts the test in full accordance with the prescribed sequence, Q1=10; if there is a partial reversal of the sequence, etc., the corresponding score will be given according to the actual situation. In terms of the execution of the test items, if all items are executed accurately, Q2=10; if there are missed or wrongly inspected items, points will be deducted according to the severity of the problem. For the timeliness of uploading the test data, Q3=10 will be obtained if it is uploaded on time, and points will be deducted accordingly if it is uploaded late or incorrectly.

[0039] The system calculates the C value according to the above formula. If C is lower than the threshold, it is determined that the testing agency has violated the rules or does not comply with the testing process. At this time, the system automatically records the violations, such as violations of the testing sequence (P1 plus 1), missed testing items (P2 plus 1), or delayed uploading of testing data (P3 plus 1), and increases the negative impact on the comprehensive evaluation value through the second half of the formula according to the type and number of violations.

[0040] The system then generates a rectification notice, which is automatically sent to the terminal of the testing agency manager through the system. The notice clearly points out the violation and the evaluation result calculated according to the formula, and requires the testing agency to rectify the problem within a time limit. During the rectification period, the system continuously tracks the rectification situation, and recalculates the C value based on the execution of the business process after the rectification during the re-evaluation. If the C value meets the qualified standard, the rectification is deemed qualified; if it is still unqualified, further strengthen the supervision measures, such as increasing the frequency of random inspections, etc., to ensure that the testing agency strictly carries out the inspection work in accordance with the regulations and ensure the standardized and orderly operation of the motor vehicle inspection market. In the present invention, the sensor array in the detection data acquisition module has an automatic calibration function, and is automatically calibrated at regular intervals (such as 1 hour). The calibration process uses a standard source for comparison to ensure the long-term stability of the sensor measurement accuracy. The calibration data is automatically recorded and uploaded to the remote monitoring center.

[0041] In the present invention, the data encryption transmission module uses digital certificate technology to authenticate the data sender and receiver during the data transmission process to ensure the security and reliability of data transmission. The digital certificate is issued by an authoritative certification body and is valid for 1 year. The certificate update process is automatic and does not affect the normal operation of the system.

[0042] In the present invention, the intelligent analysis and early warning module in the remote supervision center module has self-learning and self-adaptation capabilities, can continuously optimize the anomaly detection model according to new detection data, improve the accuracy and timeliness of the early warning, the model optimization cycle does not exceed 1 month, and the model performance is improved by no less than 10% after each optimization.

[0043] In the present invention, the high-definition camera array in the detection process monitoring module adopts intelligent tracking technology, which can automatically track the moving position of the vehicle on the detection line, ensure that the vehicle is always in the center of the monitoring screen, improve the monitoring effect, and the intelligent tracking error does not exceed ±0.5 meters.

[0044] In the present invention, the testing agency management module has the function of automatic review of the testing report. According to the preset review rules and standards, the testing report uploaded by the testing agency is automatically reviewed. The review content includes the rationality of the testing data, the completeness of the testing items, the accuracy of the conclusions, etc. The review time does not exceed 5 minutes, and the review results are automatically fed back to the testing agency. For reports that fail the review, the testing agency needs to modify them and re-upload them for review.

[0045] The present invention also discloses a method for remote monitoring of motor vehicle detection, comprising the following steps: Data collection steps: Various types of high-precision sensor arrays installed on the motor vehicle inspection line are used to collect various vehicle inspection data, including exhaust emissions, vehicle speed, braking performance, light intensity, axle weight and other data. The sensors collect data in real time and transmit it to the data acquisition unit.

[0046] Data encryption and transmission steps: After the data acquisition unit receives the sensor data, it encrypts the data using the national secret algorithm as described in claim 3, adds a digital certificate for identity authentication, and then transmits the encrypted data to the remote monitoring center through a wireless communication network or a dedicated VPN to ensure the confidentiality, integrity and authenticity of the data during transmission.

[0047] Data analysis and storage step: After receiving the encrypted data, the remote monitoring center uses the data analysis and processing software on the server to decrypt, analyze and verify the data as described in claim 1, and stores the analyzed data in a distributed database according to the vehicle inspection item classification to establish a complete vehicle inspection data file.

[0048] Intelligent analysis and early warning step: The intelligent analysis and early warning module, as described in claim 4, performs real-time analysis on the detection data stored in the database based on big data analysis technology and artificial intelligence algorithms, uses the trained anomaly detection model to identify abnormal patterns and potential risks in the data, and when an anomaly is detected, generates early warning information and pushes it to the supervisor terminal, notifying the supervisor to take measures in a timely manner.

[0049] Inspection process monitoring steps: The high-definition camera array installed on the inspection line captures the vehicle inspection process in real time, and uses intelligent image recognition technology to automatically identify vehicle and inspection personnel information. The video data is transmitted to the remote supervision center, and the supervisor views the monitoring video in real time through the monitoring terminal to ensure that the inspection process is standardized and accurate.

[0050] Testing agency management steps: Establish a testing agency information management database to store and manage testing agency related information, monitor the testing agency business processes in real time, generate rectification notices for violations and track rectification status, and automatically review test reports to ensure the quality of the testing agency's work.

[0051] In the data collection step of the present invention, the sensor array performs a pre-detection before the vehicle enters the detection line to check whether the sensor is working normally. If a sensor failure is found, the system automatically alarms and prompts to replace the sensor to ensure the accuracy of the collected data.

[0052] In the intelligent analysis and early warning step of the present invention, after the early warning information is pushed to the supervisor terminal, the supervisor can conduct further in-depth analysis of the abnormal data through the analysis tool of the remote supervision center, view data trends, compare historical data, etc., to assist in determining the cause of the abnormality. The analysis tool has data visualization functions, such as line graphs, bar graphs, scatter graphs, etc., which are convenient for supervisors to intuitively view data features.

[0053] In the testing agency management step of the present invention, remote random inspections are regularly carried out on the testing equipment of the testing agency, standard sample inspections are carried out by remotely controlling the testing equipment, the test data are obtained and compared with the standard values, and the accuracy and reliability of the testing equipment are evaluated. The random inspection frequency is once a month. For testing agencies whose equipment accuracy does not meet the requirements, they are required to suspend their testing business and calibrate or repair the equipment.

[0054] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A motor vehicle inspection remote supervision system, characterized in that: include: Detection data acquisition module: It uses a multi-type sensor array and is installed on the motor vehicle inspection line to collect various vehicle inspection data, including exhaust emission data, vehicle speed data, braking performance data, light intensity data, and axle weight data. The exhaust emission sensor uses electrochemical sensor and infrared sensor fusion technology to detect multiple pollutants at the same time; the vehicle speed sensor uses the laser Doppler speed measurement principle; the braking performance sensor is a combination of a pressure sensor and a displacement sensor; the light intensity sensor uses a photodiode array; and the axle weight sensor uses a strain gauge sensor; The sensor and data acquisition unit are connected via a high-speed wired transmission network. The data acquisition unit has a real-time data cache function to capture dynamic data changes during vehicle detection. Data encryption transmission module: Real-time encryption processing of the collected detection data is performed, and the national encryption algorithm, including the SM4 encryption algorithm, is used to encrypt the data. The encryption key length is 128 bits; The encrypted data is transmitted to the remote monitoring center via a wireless communication network or a dedicated virtual private network VPN. The wireless communication module supports multi-band adaptive switching; Remote monitoring center module: equipped with a high-performance server cluster, the server uses Intel Xeon series multi-core processors; The data analysis and processing software runs on the server, which decrypts, analyzes and verifies the encrypted data. The analyzed data is stored in the database according to the vehicle inspection items. The database adopts a distributed storage architecture, including the Hadoop distributed file system. Intelligent analysis and early warning module: Based on big data analysis technology and artificial intelligence algorithms, it conducts real-time analysis of the detection data stored in the database, and uses deep learning algorithms, including convolutional neural networks, to build an abnormal detection model for vehicle detection data, including normal vehicle detection data and various types of faulty vehicle detection data; When abnormal vehicle detection data is detected, the system automatically generates warning information, which is pushed to the supervisor's terminal in a variety of ways; Inspection process monitoring module: A high-definition camera array is installed on the motor vehicle inspection line, which has night vision and intelligent image recognition functions. It can capture the key links of the vehicle inspection process in real time, including appearance inspection and online inspection, and automatically identify the vehicle model, license plate number, and inspection personnel's operating behavior information through image recognition technology; The video data collected by the camera is transmitted to the remote monitoring center in real time through the network, and the supervisor can view the video of the detection process in real time through the monitoring terminal; Testing agency management module: establish a testing agency information management database to store the basic information, personnel information, and equipment information of the testing agency. The database has data update and query functions; The testing business process of the testing agency is monitored and managed in real time. According to the testing standards and specifications, the testing agency's testing sequence, execution of testing items, timeliness of testing data upload, etc. are automatically checked and compared. When it is found that the testing agency has violated the regulations or does not comply with the testing process, the system automatically records the violation and generates a rectification notice.

2. The motor vehicle inspection remote supervision system according to claim 1 is characterized in that: The sensor array in the detection data acquisition module has an automatic calibration function. The calibration process uses a standard source for comparison, and the calibration data is automatically recorded and uploaded to the remote monitoring center.

3. The motor vehicle inspection remote supervision system according to claim 1, characterized in that: During the data transmission process, the data encryption transmission module uses digital certificate technology to authenticate the sender and receiver of the data.

4. The motor vehicle inspection remote supervision system according to claim 1, characterized in that: The intelligent analysis and early warning module in the remote supervision center module has self-learning and self-adaptation capabilities, and the model optimization cycle does not exceed 1 month.

5. The motor vehicle inspection remote supervision system according to claim 1, characterized in that: The high-definition camera array in the inspection process monitoring module uses intelligent tracking technology to automatically track the movement of the vehicle on the inspection line.

6. The motor vehicle inspection remote supervision system according to claim 1, characterized in that: The testing agency management module has the function of automatic review of testing reports. According to the preset review rules and standards, it automatically reviews the testing reports uploaded by the testing agencies. The review content includes the rationality of the test data, the completeness of the test items, and the accuracy of the conclusions. The review time does not exceed 5 minutes, and the review results are automatically fed back to the testing agency. For reports that fail the review, the testing agency needs to modify them and re-upload them for review.

7. A method for applying the motor vehicle inspection remote supervision system according to claims 1-6, characterized in that: The following steps are involved: Data collection step: by installing a multi-type high-precision sensor array on the motor vehicle inspection line, various vehicle inspection data are collected according to claim 1, including exhaust emissions, vehicle speed, braking performance, light intensity, and axle weight data. The sensor collects data in real time and transmits it to the data acquisition unit; Data encryption and transmission step: after receiving the sensor data, the data acquisition unit encrypts the data using the national secret algorithm as described in claim 3, adds a digital certificate for identity authentication, and then transmits the encrypted data to the remote monitoring center via a wireless communication network or a dedicated VPN; Data parsing and storage step: after receiving the encrypted data, the remote monitoring center uses the data parsing and processing software on the server to decrypt, parse and verify the data according to claim 1, and stores the parsed data in a distributed database according to the classification of vehicle inspection items; Intelligent analysis and early warning step: The intelligent analysis and early warning module performs real-time analysis on the detection data stored in the database based on big data analysis technology and artificial intelligence algorithms as described in claim 4, and uses the trained anomaly detection model to identify abnormal patterns and potential risks in the data. When an abnormality is detected, it generates early warning information as described in claim 1 and pushes it to the supervisor terminal; Inspection process monitoring step: using a high-definition camera array installed on the inspection line to shoot a video of the vehicle inspection process in real time according to claim 5, using intelligent image recognition technology to automatically identify vehicle and inspection personnel information, and transmitting video data to a remote monitoring center, and the supervisory personnel viewing the monitoring video in real time through the monitoring terminal according to claim 1; Testing agency management step: The testing agency management module establishes a testing agency information management database as described in claim 6, stores and manages testing agency related information, monitors the testing agency business process in real time, generates rectification notices for violations and tracks rectification status, and automatically reviews the testing report.

8. The motor vehicle inspection remote supervision method according to claim 7, characterized in that: In the data collection step, the sensor array performs a pre-detection before the vehicle enters the detection line to check whether the sensor is working normally. If a sensor fault is found, the system automatically alarms and prompts to replace the sensor.

9. The motor vehicle inspection remote supervision method according to claim 7, characterized in that: In the intelligent analysis and early warning step, after the early warning information is pushed to the supervisor's terminal, the supervisor uses the analysis tool of the remote supervision center to analyze the abnormal data, view data trends, compare historical data, and assist in determining the cause of the abnormality. The analysis tool has data visualization functions, including line graphs, bar graphs, and scatter graphs.

10. The motor vehicle inspection remote supervision method according to claim 7, characterized in that: In the testing agency management steps, regular remote spot checks are carried out on the testing equipment of the testing agency. Standard sample tests are carried out through remote control of the testing equipment. The test data is obtained and compared with the standard values ​​to evaluate the accuracy and reliability of the testing equipment. The frequency of spot checks is once a month.

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