An anti-tampering offset printing quality data acquisition system and method

Abstract

The present invention belongs to the technical field of color difference detection and management of printed products, and discloses an anti-tampering offset printing quality data acquisition system. A networked color difference acquisition instrument is used to detect the color difference of printed sheets during printing and upload the detection data to the local database and the Internet cloud; a rail robot with a high-definition camera conducts inspections on the ceiling rail in a specified direction, takes photos or videos of the color difference acquisition process above the printing equipment and uploads them to the local database and the Internet cloud; the system forms a multi-level networked monitoring system through Ethernet, and the distributed intelligent monitoring system obtains the status of video acquisition through the acquisition signals of the acquisition points; a complete record report is formed for each color difference acquisition, forming permanent traceable information. The results of this part of the data can be stored locally and on the cloud server. The data on both sides can mutually verify the validity of the original records of the data through the MD5 encryption algorithm, forming an anti-tampering mechanism.

Description

Technical Field

[0001] The present invention belongs to the technical field of color difference detection and management of printed products, and particularly relates to an anti-tampering offset printing quality data acquisition system and method. Background Art

[0002] At present, there are multiple production lines in a workshop of cigarette package printing production enterprises. During the production process and for the data of the final product detection indicators (the color difference value ΔE of CIELAB and the Lab value of the sample color during the test process), a color difference acquisition instrument is used to collect color difference data, and then workers manually record the color difference data. Manual recording not only has a large workload, but also inevitably generates errors. If the operation is careless or the process is not standardized, it is very easy to cause data inaccuracy, and the color difference problem cannot be discovered in time, resulting in an impact on the final quality of the product. In addition, in order to provide good detection data to customers, some factories often artificially modify the detection data, resulting in the situation that the actual color difference of the product cannot be adjusted in time and the product quality does not match the data. Therefore, there are problems such as ineffective quality control, large errors, and a lot of data moisture in offset printing products. Summary of the Invention

[0003] The purpose of the present invention is to provide an anti-tampering offset printing quality data acquisition device and method to solve the technical problems of large errors and easy tampering in manual color difference acquisition of existing offset printing products.

[0004] To solve the above technical problems, the specific technical solutions of an anti-tampering offset printing quality data acquisition system and method of the present invention are as follows:

[0005] An anti-tampering offset printing quality data acquisition system includes a hardware part and a software part. The hardware part includes a networked color difference acquisition instrument, a ceiling track, a track robot, and a high-definition camera. The networked color difference acquisition instrument is arranged beside the printing equipment, performs color difference detection on the printed sheet during printing, and uploads the detection data to the local database and the Internet cloud. There is a ceiling track above the printing equipment, and a point is set above each printing equipment. The track robot is installed on the ceiling track, and a high-definition camera is installed on the track robot. The track robot takes the high-definition camera to perform patrol inspection on the ceiling track in a specified direction. When it reaches the point above the printing equipment, it can take photos or videos of the color difference acquisition process and upload them to the local database and the Internet cloud. The software part includes a local database and a patrol robot control platform. The local database is used to synchronously save the basic data collected by the networked color difference acquisition instrument in hardware. The patrol robot control platform forms a multi-level networked monitoring system through Ethernet to perform real-time monitoring on the color difference acquisition process.

[0006] Furthermore, the detection data includes the color difference value ΔE and the Lab value of the sample color.

[0007] Furthermore, in the offset printing production workshop, there are multiple production lines, and each production line has multiple printing devices. The networked color difference acquisition instrument is configured according to the number of printing devices. Each printing device is equipped with an operator. The operator presses the "Start Detection" button of the networked color difference acquisition instrument to perform color detection on the printed sheet. If the detected color difference data exceeds the specified range, the worker will make real-time adjustments to the printing device to make the color difference data meet the requirements.

[0008] Furthermore, the rail robot has a horizontal movement mechanism and can move horizontally on the ceiling rail. There is a lifting rod between the high-definition camera and the rail robot, and the lifting rod can adjust the height of the high-definition camera.

[0009] Furthermore, the local database has a basic color difference data table. Each color difference data collection has a standard computer timestamp data. The basic fields of the local basic color difference data table include order number, process order number, color difference data, system timestamp, and release status.

[0010] Furthermore, the local database has an event trigger. Every time new data is added or the table data changes, the newly added or changed data is recorded in another new table. The basic fields of the new table include order number, process order number, color difference data, system timestamp, SQL command, release status, and data uniqueness identification field.

[0011] Furthermore, the order number is the order number to which the product of this color difference collection belongs, and the system reads it from the MES production management system. The process order number is the process number to which the product of this color difference collection belongs (which is a subset of the order number), and the system reads it from the shift scheduling information of the MES production management system. The color difference data is collected from the printing device through the networked color difference acquisition instrument. The release status has two states: uploaded and not uploaded. The system timestamp is the Internet timestamp obtained from the server. The SQL command is the operation statement executed when the local server submits data, which is used to mark operations such as addition and modification. The data uniqueness identification field is obtained through the MD5 algorithm. The input parameter value of the MD5 algorithm is composed of the string "order number + process order number + color difference data + timestamp + SQL command", which is used to identify the uniqueness of the data.

[0012] Furthermore, the inspection robot control platform includes a user management module, a basic data management module, an AI intelligent monitoring module, and a data anti-tampering module. The user management module is used to set and manage the roles and permissions of users. The basic data management module is used to preset the detection standard values and record abnormal data. The AI intelligent monitoring module is used to take photos or videos and save them.

[0013] Furthermore, the user management module includes user addition / import, user role management, user group management, and user management; the function of user addition / import is to add the basic registration information of users; the function of user role management is to add user roles, set role functions, and hierarchical permission information; the function of user group management is to custom-create the user group architecture; the function of user management is to support users to retrieve users according to different groups or user information, and support exporting the user list: exporting different user information according to different user groups.

[0014] Furthermore, the basic data management module includes an alarm parameter configuration library, device monitoring and capture, abnormal data summary, color difference position template library, main color difference standard, and template library; the function of the alarm parameter configuration library is to set the alarm parameters of different detection items according to the detection standard; the function of device monitoring and capture is to capture and retain the detection targets that exceed the detection standard; the function of abnormal data summary is to summarize and record the data that exceeds the detection standard; the function of the color difference position template library is to preset the color difference detection point positions of each product according to different products; the function of the main color difference standard is to select the main color and color difference standard values of different products; the function of the template library is to store the visual detection position ranges of different products as the standard images for detection benchmarks.

[0015] Furthermore, the AI intelligent monitoring module includes AI intelligent learning and training, training template storage, camera preset positions, video clip saving, AI intelligent warning / alarm; the function of AI intelligent learning and training is to learn and train the standard personnel recognition; the function of training template storage is to save the templates of the scenes to be recorded; the function of camera preset positions is to record and save the camera shooting positions; the function of video clip saving is to synchronously record the detection videos; the function of AI intelligent warning / alarm is that when the detection data is abnormal, the system automatically gives an alarm, and if no one processes it, it automatically escalates the alarm to the superior responsible person; the data anti-tampering module includes data comparison, data acquisition, and alarm; the function of data comparison is to record all uploaded data using the MD5 algorithm and compare whether the MD5 value of the data after local upload is consistent with the original MD5 value recorded in the cloud; the function of the alarm is to actively trigger an alarm for the data with abnormal comparison results.

[0016] The present invention also discloses an anti-tampering method for collecting offset printing quality data, including the following steps:

[0017] Step 1: Construct an anti-tampering local system for collecting offset printing quality data and a cloud web quality data query system platform; the cloud web quality data query system platform is used to query the data saved by the anti-tampering offset printing quality data collection system.

[0018] Step 2: The local database synchronously saves the basic data collected by the networked color difference collector in hardware.

[0019] Step 3: When the local data saves the color difference data, it synchronously notifies the track robot. The track robot determines whether it is near the color difference collection point. If it is near and can arrive at the collection location within 30 seconds of the color difference collection time, it notifies the track robot to come to the collection point.

[0020] Step 4: After the track robot arrives at the collection point, the high-definition camera on the track robot synchronously starts taking photos or videos and uploads the taken photos or videos, along with the color difference data and the collection time, to the local database and cloud storage.

[0021] Step 5: The local database and cloud data are compared to determine whether the data uniqueness identification fields of the local data and cloud data uploaded this time are the same. At this time, if the local data is manually modified, a new piece of data is generated. When the new data is uploaded, the system will compare it with the original data saved in the cloud. If the comparison result is different at this time, an alarm is issued.

[0022] Step 6: The user can view the color difference collection situation and production information in real time through the cloud web quality data query system platform, check whether the color difference data is collected under production conditions, and can remotely operate the track robot to go to the specified node to view the production status in real time, as well as check whether someone is handling the situation when the color difference exceeds the standard. Through permission control, different user permissions can be set in the monitoring systems at all levels, and information sharing can be carried out through authorization.

[0023] The anti-tampering offset printing quality data collection system and method of the present invention have the following advantages:

[0024] The present invention realizes the inspection of machine operators and the operation conditions of all offset printing presses by adding an inspection track robot with a camera inside the offset printing workshop and installing a ceiling track. At the same time, an online color difference acquisition instrument is added to enhance the online data acquisition ability. Meanwhile, according to the route for inspection, it can quickly locate key positions. Operators can issue control commands through a remote workstation to achieve the inspection point control function of the robot. The system can form a multi-level network monitoring system through Ethernet, and the distributed intelligent monitoring system can obtain the status of video acquisition through the acquisition signals at the acquisition points. It realizes all-round and full-platform information management and monitoring of the color difference data acquisition process, forms a complete record report for each color difference acquisition, and forms permanent traceable information. The results of this part of the data can be stored locally and on the cloud server. The data on both sides can mutually verify the validity of the original records of the data through the MD5 encryption algorithm, forming an anti-tampering mechanism. At the same time, through role-based permission control, permissions can be set in each level of the monitoring system, and information sharing can be carried out through authorization. Compared with the original manual supervision in the industry, it is more rigorous, standardized, reliable, and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a schematic diagram of the hardware structure of the present invention;

[0026] Figure 2 is a schematic diagram of the layout of the track robot of the present invention;

[0027] Figure 3 is a schematic diagram of the overall architecture of the data acquisition system and server of the present invention;

[0028] Figure 4 is a core flowchart of the color difference acquisition of the present invention;

[0029] Figure 5 is a framework diagram of the core functional modules of the present invention;

[0030] Figure 6 is a schematic diagram of the local database columns of the present invention;

[0031] Figure 7 is a schematic diagram of the cloud database columns of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] In order to better understand the purpose, structure and function of the present invention, the following further describes in detail an anti-tampering offset printing quality data acquisition system and method of the present invention with reference to the accompanying drawings.

[0033] As Figure 1As shown in the figure, an anti-tampering offset printing quality data acquisition system of the present invention includes a hardware part and a software part. The hardware part includes a networked color difference acquisition instrument, a ceiling track, a track robot, and a high-definition camera. The networked color difference acquisition instrument is set beside the printing equipment, and can detect the color difference of the printed sheet during printing (the detected data includes the color difference value ΔE and the Lab value of the sample color), and upload the detected data to the local database and the Internet cloud. As Figure 2 shown, in the offset printing production workshop, there are multiple production lines, and each production line has multiple printing equipment. The networked color difference acquisition instruments are configured according to the number of printing equipment. Each printing equipment is equipped with an operator. The operator presses the "start detection" button of the networked color difference acquisition instrument at regular intervals to detect the color of the printed sheet. If the detected color difference data exceeds the specified range, the operator makes real-time adjustments to the printing equipment to make the color difference data meet the specifications. The color difference acquisition process is as shown in the following table:

[0034] Table 1: Color difference acquisition process

[0035] Serial number Color difference acquisition process Process description 1 Sampling Sampling is carried out for every about 1000 printed sheets. One tray is called one process, and one process has about 3000 printed sheets 2 Judgment of detection position Confirm the position of the detection color block area corresponding to each product 3 Detection Perform color difference detection according to the printed sheets 4 Record the test value Record the color difference value into the system through the networked color difference acquisition instrument. Each value needs to be measured 3 times at the color difference acquisition angles of 15°, 30°, and 45° 5 Measurement end Record the CIELab value and place the sample sheet separately

[0036] In order to prevent post-event detection, a ceiling track is arranged within a range of 2-3 meters above the printing equipment, and a point is set above each printing equipment. The track robot is installed on the ceiling track. The track robot has a horizontal movement mechanism and can move horizontally on the ceiling track. A high-definition camera is installed on the track robot. There is a lifting rod between the high-definition camera and the track robot, and the lifting rod can adjust the height of the high-definition camera. The track robot takes the high-definition camera to conduct inspections on the ceiling track in a specified direction. When it reaches the point above the printing equipment, it can take photos or videos of the color difference acquisition process and upload them to the local database and the Internet cloud. In this way, it can be proved that the color difference acquisition process is carried out during the production process, rather than artificial post-event detection.

[0037] As Figure 3 shown, the software part of an anti-tampering offset printing quality data acquisition system of the present invention includes a local database and an inspection robot control platform. The platform can form a multi-level networked monitoring system through Ethernet to achieve distributed real-time intelligent monitoring of the color difference acquisition process.

[0038] The local database uses sql server, and other databases can also be used, which is not limited here. The local database is used to synchronously save the basic data collected by the networked color difference acquisition instrument in hardware.

[0039] The local database has a basic color difference data table. Each color difference data collection has a standard computer timestamp to prevent artificial post - detection. The basic fields of the local basic color difference data table include order number, process order number, color difference data, system timestamp, and release status. The local database also has an event trigger. Every time new data is added or the table data changes, the newly added or changed data is recorded in another new table. The basic fields of the new table include order number, process order number, color difference data, system timestamp, SQL command, release status, and data uniqueness identification field. Order number: It is the order number to which the product for this color difference collection belongs. The system reads it from the MES production management system. Process order number: It is the process number to which the product for this color difference collection belongs (a subset of the order number). The system reads it from the shift scheduling information of the MES production management system. Color difference data: It is collected from the printing equipment through an online color difference collector. Release status: There are two statuses, uploaded and not uploaded. System timestamp: The Internet timestamp is obtained from the server. SQL command: It is the operation statement executed when the local server submits data, used to mark operations such as addition and modification. Data uniqueness identification field: It is obtained through the MD5 algorithm. The input parameter values of the MD5 algorithm are composed of the following string: "order number + process order number + color difference data + timestamp + SQL command", used to identify the uniqueness of the data. The system only needs to compare the data between the local and the cloud through the data uniqueness identification field, without the need to compare multiple fields separately, which has the advantages of high efficiency and speed. When there is a large amount of collected data, it can also quickly calculate, save computer resources, and increase the comparison efficiency.

[0040] The inspection robot control platform includes a user management module, a basic data management module, an AI intelligent monitoring module, and a data anti - tampering module.

[0041] The user management module is used to set and manage the roles and permissions of users. It includes user addition / import, user role management, user group management, and user management. The function of user addition / import is to add the basic registration information of users, such as user name, password / change password, and other user information. The function of user role management is to add user roles, set role functions, hierarchical permissions, and other information. The function of user group management is to custom - create the user group structure. The function of user management is to support user retrieval according to different groups or user information; support exporting the user list: export different user information according to different user groups.

[0042] The basic data management module is used to preset the detection standard values and record abnormal data. It includes an alarm parameter configuration library, device monitoring and capturing, abnormal data summary, color difference position template library, main color difference standard, and template library. The function of the alarm parameter configuration library is to set the alarm parameters for different detection items according to the detection standards. The function of device monitoring and capturing is to capture and retain the detection targets that exceed the detection standards. The function of abnormal data summary is to summarize and record the data that exceeds the detection standards (values, frequencies, change curves, etc.). The function of the color difference position template library is to preset the color difference detection point positions for each product according to different products. The function of the main color difference standard is to select the main colors and color difference standard values of different products. The function of the template library is to store the visual detection position ranges of different products as standard images for detection reference.

[0043] The AI intelligent monitoring module is used to take photos or videos and save them. It includes AI intelligent learning and training, training template storage, camera preset positions, video segment saving, and AI intelligent warning / alert. The function of AI intelligent learning and training is to learn and train the recognition of standard personnel. The function of training template storage is to save the templates of the scenes to be recorded. The function of camera preset positions is to record and save the camera shooting positions. The function of video segment saving is to synchronously record the detection videos. The function of AI intelligent warning / alert is that when abnormal detection data occurs, the system automatically gives an alarm, and if no one handles it, it automatically escalates the alarm to the superior responsible person. The data anti-tampering module includes data comparison, data acquisition, and alarm. The function of data comparison is to record all uploaded data using the MD5 algorithm and compare whether the MD5 value of the data after local upload is the same as the original MD5 value recorded in the cloud. The function of the alarm is to actively trigger an alarm for the data with abnormal comparison results.

[0044] An anti-tampering method for offset printing quality data is realized through an anti-tampering offset printing quality data acquisition system to protect the data of a website platform using dynamic web technology from being tampered with, so as to prove that the color difference data has not been manually changed during the user's use and has not been corrected in the online background. Through local network storage at the security level, the saved data is divided into two forms: local storage and cloud storage. The cloud mainly stores on public cloud platforms such as Alibaba Cloud.

[0045] As Figure 4 shown, the method of the present invention includes the following steps:

[0046] Step 1: As Figure 5 shown, construct an anti-tampering offset printing quality data acquisition local system and a cloud web quality data query system platform as described above. The cloud web quality data query system platform is used to query the data saved by the anti-tampering offset printing quality data acquisition system.

[0047] Step 2: The local database synchronously saves the basic data collected by the networked color difference collector in hardware.

[0048] Step 3: When the local data saves the color difference data, it synchronously notifies the track robot. The track robot judges whether it is near the color difference collection point. If it is near and can reach the collection location within 30 seconds of the color difference collection time, it notifies the track robot to come to the collection point. In actual production, the length of the ceiling track can be set within the range that the track robot can reach within 30 seconds, so as to synchronously take photos or videos during each color difference collection.

[0049] Step 4: After the track robot reaches the collection point, the high-definition camera on the track robot synchronously starts taking photos or videos and uploads the taken photos or videos, along with the color difference data and collection time, to the local database and cloud storage.

[0050] Step 5: As Figure 6 、 Figure 7 shown, the local database and cloud data are compared to judge whether the data uniqueness identification fields of the locally uploaded data and cloud data are the same. At this time, if the local data is manually modified, a new piece of data is generated. When the new data is uploaded, the system will compare it with the original data saved in the cloud. If the comparison result is different at this time, an alarm is issued.

[0051] Step 6: The user can view the color difference collection situation and production information in real time through the cloud web quality data query system platform, and check whether the color difference data is collected under the production state. And can remotely operate the track robot to go to the specified node to view the production status in real time, and check whether someone is dealing with the color difference exceeding the standard. Through permission control, different user permissions can be set in each level of monitoring system, and information sharing can be carried out through authorization.

[0052] It can be understood that the present invention is described through some embodiments. Those skilled in the art know that without departing from the spirit and scope of the present invention, various changes or equivalent replacements can be made to these features and embodiments. In addition, under the teaching of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application belong to the scope protected by the present invention.

Claims

1. A method for collecting offset printing quality data using a tamper-proof offset printing quality data collection system, the tamper-proof offset printing quality data collection system comprising a hardware portion and a software portion. The hardware portion comprises a networked color difference collector, a ceiling track, a track robot, and a high-definition camera. The networked color difference collector is disposed near a printing device and performs color difference detection on printed sheets during printing and uploads the detection data to a local database and an Internet cloud. The printing device is provided with a ceiling track above, and a point is provided above each printing device. The track robot is mounted on the ceiling track and is equipped with a high-definition camera. The track robot, carrying the high-definition camera, patrols along the ceiling track in a specified direction. When it reaches a point above the printing device, it can take photos or videos of the color difference collection process and upload them to a local database and an Internet cloud. The software portion comprises a local database and a patrol robot control platform. The local database is used to synchronize hardware storage of basic data collected by the networked color difference collector. The patrol robot control platform forms a multi-level networked monitoring system via Ethernet to monitor the color difference collection process in real time. The local database is provided with a basic color difference data table, and each time the color difference data is collected, there is a standard computer timestamp data. The basic fields of the local basic color difference data table include order number, process number, color difference data, system timestamp and release status; the local database has an event trigger, and each time the table data is added or changed, the new or changed data is recorded in another new table: the basic fields of the new table include order number, process number, color difference data, system timestamp, SQL command, release status and data uniqueness identification field; the inspection robot control platform includes a user management module, a basic data management module, an AI intelligent monitoring module and a data tamper-proof module; the user management module is used to set and manage the user's role and authority; the basic data management module is used to preset the detection standard value and record abnormal data; the AI intelligent monitoring module is used to take photos or videos and save them; the track robot has a horizontal motion mechanism, which can move horizontally on the ceiling track, and there is a lifting rod between the high-definition camera and the track robot, and the lifting rod can adjust the height of the high-definition camera; it is characterized in that The method comprises the following steps: Step 1: Build a tamper-proof offset printing quality data collection local system and a cloud web quality data query system platform; the cloud web quality data query system platform is used to query the data stored in the tamper-proof offset printing quality data collection system; Step 2: The local database will synchronize and save the basic data collected by the networked colorimeter; Step 3: When the local data saves the color difference data, it notifies the track robot synchronously. The track robot determines whether it is near the color difference collection point. If it is nearby and can arrive at the collection location within the 30-second color difference collection time, the track robot is notified to come to the collection point. Step 4: After the track robot arrives at the collection point, the high-definition camera on the track robot starts taking photos or videos synchronously and uploads the photos or videos along with the color difference data and collection time to the local database and cloud storage; Step 5: Compare the local database and cloud data to determine whether the data uniqueness identification fields of the uploaded local data and cloud data are the same. If the local data is manually modified, a new data will be generated. When the new data is uploaded, the system will compare it with the original data saved in the cloud. If the comparison results are different, an alarm will be issued. Step 6: Users can view the color difference collection status and production information in real time through the cloud web quality data query system platform, check whether the color difference data is collected during production, and remotely operate the track robot to go to the designated node to view the production status in real time and check whether someone is handling the problem when the color difference exceeds the standard; Through permission control, the permissions of different users can be set in monitoring systems at all levels, and information sharing can be carried out through authorization.

2. The method according to claim 1, characterized in that The detection data includes the color difference value ΔE and the Lab value of the sample color.

3. The method according to claim 1, characterized in that In an offset printing production workshop, there are multiple production lines, each of which has multiple printing devices. The networked colorimeter is configured according to the number of printing devices. Each printing device is equipped with an operator, who presses the "Start Detection" button on the networked colorimeter to perform color detection on the printed sheet. If the detected color difference data exceeds the specified range, the operator will make real-time adjustments to the printing device to ensure that the color difference data meets the requirements.

4. The method according to claim 1, wherein The order number is the order number of the product to which the color difference collection belongs, and the system reads it from the MES production management system; the process number is the process number of the product to which the color difference collection belongs, and the system reads it from the scheduling information of the MES production management system; the color difference data is collected from the printing equipment through a networked color difference collector; the publishing status has two states: uploaded and not uploaded; The system timestamp is an Internet timestamp obtained on the server; The SQL command is an operation statement executed when the local server submits data, and is used to mark addition and modification operations; the data uniqueness identification field is obtained through the MD5 algorithm, and the MD5 algorithm input parameter value is composed of the "order number + process order number + color difference data + timestamp + SQL command" string, which is used to identify the uniqueness of the data.

5. The method according to claim 4, characterized in that The user management module includes user addition / import, user role management, user group management and user management; the function of user addition / import is to add the basic registration information of the user; The functions of the user role management are to add user roles, set role functions and hierarchical authority information; the function of the user group management is to create a custom user group structure; The user management function supports users to search for users according to different groups or user information, and supports exporting user lists: exporting different user information according to different user groups; The basic data management module includes an alarm parameter configuration library, equipment monitoring snapshots, abnormal data summary, color difference position template library, main color tone color difference standard and template library; the function of the alarm parameter configuration library is to set alarm parameters for different detection items according to the detection standards; the function of the equipment monitoring snapshot is to capture and retain detection targets that exceed the detection standards; the function of the abnormal data summary is to summarize and record data that exceed the detection standards; the function of the color difference position template library is to preset the color difference detection point position of each product according to different products; the function of the main color tone color difference standard is to select the main color and color difference standard values of different products; the function of the template library is to store the visual detection position range of different products as a standard diagram for detection benchmarks; The AI intelligent monitoring module includes AI intelligent learning and training, training template storage, camera preset points, video clip storage, and AI intelligent early warning / alarm; the function of the AI intelligent learning and training is to learn and train standard personnel recognition; The function of the training template storage is to save the template of the scene that needs to be recorded; the function of the camera preset point is to record and save the camera shooting point; the function of the video clip saving is to synchronously record the detection video; the function of the AI intelligent early warning / alarm is that when the detection data is abnormal, the system automatically alarms, and if no one handles it, it automatically escalates the alarm to the superior person in charge; the data tamper-proof module includes data comparison, data acquisition and alarm; the function of the data comparison is to record all uploaded data using the MD5 algorithm, and compare the MD5 of the data after local upload with the original MD5 data value recorded in the cloud to see if they are consistent; the function of the alarm is to actively trigger an alarm for data with abnormal comparison results.

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