Industrial production line safety monitoring system and method based on artificial intelligence

Abstract

The invention relates to the field of data processing, and discloses an artificial intelligence-based industrial production line safety monitoring system and method, and the method comprises the steps that a cloud data server calls corresponding personnel verification information in a cloud personnel database according to the production cycle information generated by a production management module, sending the data to the cloud security monitoring container corresponding to the production cycle serial number; according to the IP address information of the local service module, the local service module collects information of personnel entering the production line through the personnel management module; the cloud security monitoring container corresponding to the production cycle serial number sends the information of the personnel entering the production line and the first verification information of the corresponding personnel to the local service module; and if no personnel verification abnormity exists, the information of the personnel leaving the production line is verified at the cut-off moment when the personnel leave the production line, and safety monitoring of the production cycle of the industrial production line is completed. According to the invention, early warning can be carried out when abnormal personnel access characteristics are detected.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to an industrial production line safety monitoring system and method based on artificial intelligence. Background Art

[0002] With the rapid development of Industry 4.0 and smart manufacturing, industrial production lines have higher and higher requirements for automation and intelligence. However, as an important part of the production line, personnel safety monitoring still faces some technical bottlenecks and challenges. Traditional monitoring systems mainly rely on manual monitoring and simple sensor technology, which cannot monitor safety hazards on the production line in real time and accurately, and it is even more difficult to achieve early warning and prevention.

[0003] Traditional monitoring systems usually rely on simple access control systems or biometrics to monitor people in and out. However, these methods can only record people in and out, but cannot monitor and analyze people's behavior and status in real time.

[0004] Therefore, how to more effectively monitor and analyze the people entering and leaving the production line is a topic that researchers need to study now. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide an industrial production line safety monitoring method based on artificial intelligence, comprising the following steps: Step 1: The cloud data server generates a cloud security monitoring container corresponding to the production cycle number in the production cycle information according to the production cycle information generated by the production management module, and calls the corresponding personnel verification information in the cloud personnel database according to the production cycle personnel information list in the production cycle information, and sends it to the cloud security monitoring container corresponding to the production cycle number; Step 2: At the start and end time of the production cycle, the cloud data server connects the cloud security monitoring container corresponding to the production cycle number to the local service module according to the IP address information of the local service module, and the local service module collects the personnel information entering the production line through the personnel management module; Step 3: The local service module sends the personnel information of the personnel entering the production line collected by the personnel management module to the cloud security monitoring container corresponding to the production cycle number, and performs personnel verification in the cloud security monitoring container corresponding to the production cycle number. If the personnel verification passes, the first verification information of the corresponding personnel is generated. At the end time of the personnel verification entering the production line, the cloud security monitoring container corresponding to the production cycle number sends the personnel information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel to the local service module; Step 4: The local service module verifies the personnel entering and leaving the production line according to the personnel information that has passed the verification and the first verification information of the corresponding personnel. If there is an abnormality in the personnel verification, the local service module sends an alarm message to the production management module; if there is no abnormality in the personnel verification, the production management module enters step 5 at the cut-off time for the personnel to leave the production line. Step 5: The local service module collects the information of the personnel leaving the production line through the personnel management module, and verifies the information of the personnel leaving the production line according to the information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel. If there is no personnel leaving the production line who has not passed the verification, proceed to step 7, otherwise proceed to step 6; Step 6: Based on the information of the personnel who have passed the verification and entered the production line, the information of the personnel who have not passed the verification and left the production line is obtained. The local service module sends the information of the personnel who have not passed the verification and left the production line to the cloud security monitoring container corresponding to the production cycle number. The cloud security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud personnel database and sends it to the local service module. The production site data collection module identifies the personnel at the production site based on the characteristic information of the corresponding personnel. If the corresponding personnel is identified, a departure notification message is issued and the process returns to step 5; otherwise, the local service module sends an alarm message to the production management module. Step seven: Complete safety monitoring of the industrial production line production cycle.

[0006] Furthermore, the production cycle information generated by the production management module includes: The production management module obtains the production cycle personnel information list, production cycle start and end time, and production cycle sequence number of the corresponding production line in the production plan according to the production line information corresponding to the IP address of the local service module; The production cycle includes the cut-off time for personnel to enter the production line for verification and the cut-off time for personnel to leave the production line.

[0007] Furthermore, according to the production cycle personnel information list in the production cycle information, the corresponding personnel verification information is called in the cloud personnel database and sent to the cloud security monitoring container corresponding to the production cycle sequence number, wherein the personnel verification information is the preset basic identity information and the first feature information associated with the basic identity information; The first characteristic information associated with the basic identity information is unified characteristic information or independent characteristic information; the unified characteristic information, i.e., the first characteristic associated with the basic identity information, is of the same characteristic type; the independent characteristic information, i.e., the first characteristic types associated with the basic identity information are all different; the characteristic types of the first characteristic include height, weight and resting pulse rate.

[0008] Furthermore, the personnel verification is performed in the cloud security monitoring container corresponding to the production cycle sequence number. If the personnel verification passes, the first verification information of the corresponding personnel is generated, including: The personnel management module collects the basic identity information and on-site first feature information of personnel entering the production line, and verifies the basic identity information of the personnel in the cloud-based security monitoring container corresponding to the production cycle number. If the basic identity information verification passes, the difference between the on-site first feature information and the first feature information is the first verification information of the corresponding personnel.

[0009] Further, the verifying of the information of the personnel leaving the production line according to the verified information of the personnel entering the production line and the first verification information of the corresponding personnel includes: The personnel management module collects the basic information of the personnel leaving the production line and the first characteristic information of the second site, and matches and verifies the basic information of the personnel leaving the production line with the information of the personnel entering the production line after verification. If the information of the personnel entering the production line after verification is matched and verified, there is no person who has not passed the verification and left the production line; otherwise, there is a person who has not passed the verification and left the production line; If the basic information verification of the personnel leaving the production line is passed, the difference between the second-site first feature information and the first feature information of the personnel leaving the production line is obtained. If the difference and the difference between the first verification information of the corresponding personnel are within the set difference threshold range, the personnel safety verification passes; otherwise, the personnel safety verification fails.

[0010] Furthermore, the cloud-based security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud-based personnel database, wherein the characteristic information is the preset second verification information; the second verification information is the personnel identification information, and the personnel identification information includes infrared information and facial information.

[0011] An artificial intelligence-based industrial production line safety monitoring system, applying the artificial intelligence-based industrial production line safety monitoring method, includes a production management module, a local service module, a cloud data server, a communication module, a personnel management module and a production site data acquisition module; The communication module, personnel management module and production site data acquisition module are respectively connected to the local service module; the cloud data server is connected to the communication module; and the production management module is connected to the cloud data server.

[0012] The beneficial effect of the present invention is that through the technical solution provided by the present invention, it is possible to monitor and analyze the personnel entering and exiting the production line, and when abnormal personnel entry and exit characteristics are detected, an early warning can be issued. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flowchart of an industrial production line safety monitoring method based on artificial intelligence; Figure 2 This is a schematic diagram of the principle of an industrial production line safety monitoring system based on artificial intelligence. DETAILED DESCRIPTION

[0014] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0015] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0016] like Figure 1 As shown, the artificial intelligence-based industrial production line safety monitoring method includes the following steps: Step 1: The cloud data server generates a cloud security monitoring container corresponding to the production cycle number in the production cycle information according to the production cycle information generated by the production management module, and calls the corresponding personnel verification information in the cloud personnel database according to the production cycle personnel information list in the production cycle information, and sends it to the cloud security monitoring container corresponding to the production cycle number; Step 2: At the start and end time of the production cycle, the cloud data server connects the cloud security monitoring container corresponding to the production cycle number to the local service module according to the IP address information of the local service module, and the local service module collects the personnel information entering the production line through the personnel management module; Step 3: The local service module sends the personnel information of the personnel entering the production line collected by the personnel management module to the cloud security monitoring container corresponding to the production cycle number, and performs personnel verification in the cloud security monitoring container corresponding to the production cycle number. If the personnel verification passes, the first verification information of the corresponding personnel is generated. At the end time of the personnel verification entering the production line, the cloud security monitoring container corresponding to the production cycle number sends the personnel information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel to the local service module; Step 4: The local service module verifies the personnel entering and leaving the production line according to the personnel information that has passed the verification and the first verification information of the corresponding personnel. If there is an abnormality in the personnel verification, the local service module sends an alarm message to the production management module; if there is no abnormality in the personnel verification, the production management module enters step 5 at the cut-off time for the personnel to leave the production line. Step 5: The local service module collects the information of the personnel leaving the production line through the personnel management module, and verifies the information of the personnel leaving the production line according to the information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel. If there is no personnel leaving the production line who has not passed the verification, proceed to step 7, otherwise proceed to step 6; Step 6: Based on the information of the personnel who have passed the verification and entered the production line, the information of the personnel who have not passed the verification and left the production line is obtained. The local service module sends the information of the personnel who have not passed the verification and left the production line to the cloud security monitoring container corresponding to the production cycle number. The cloud security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud personnel database and sends it to the local service module. The production site data collection module identifies the personnel at the production site based on the characteristic information of the corresponding personnel. If the corresponding personnel is identified, a departure notification message is issued and the process returns to step 5; otherwise, the local service module sends an alarm message to the production management module. Step seven: Complete safety monitoring of the industrial production line production cycle.

[0017] The production cycle information generated by the production management module includes: The production management module obtains the production cycle personnel information list, production cycle start and end time, and production cycle sequence number of the corresponding production line in the production plan according to the production line information corresponding to the IP address of the local service module; The production cycle includes the cut-off time for personnel to enter the production line for verification and the cut-off time for personnel to leave the production line.

[0018] According to the production cycle personnel information list in the production cycle information, the corresponding personnel verification information is called in the cloud personnel database and sent to the cloud security monitoring container corresponding to the production cycle sequence number, wherein the personnel verification information is the preset basic identity information and the first feature information associated with the basic identity information; The first characteristic information associated with the basic identity information is unified characteristic information or independent characteristic information; the unified characteristic information, i.e., the first characteristic associated with the basic identity information, is of the same characteristic type; the independent characteristic information, i.e., the first characteristic types associated with the basic identity information are all different; the characteristic types of the first characteristic include height, weight and resting pulse rate.

[0019] The personnel verification is performed in the cloud security monitoring container corresponding to the production cycle sequence number. If the personnel verification passes, the first verification information of the corresponding personnel is generated, including: The personnel management module collects the basic identity information and on-site first feature information of personnel entering the production line, and verifies the basic identity information of the personnel in the cloud-based security monitoring container corresponding to the production cycle number. If the basic identity information verification passes, the difference between the on-site first feature information and the first feature information is the first verification information of the corresponding personnel.

[0020] The step of verifying the information of personnel leaving the production line according to the information of personnel entering the production line and the first verification information of the corresponding personnel includes: The personnel management module collects the basic information of the personnel leaving the production line and the first characteristic information of the second site, and matches and verifies the basic information of the personnel leaving the production line with the information of the personnel entering the production line after verification. If the information of the personnel entering the production line after verification is matched and verified, there is no person who has not passed the verification and left the production line; otherwise, there is a person who has not passed the verification and left the production line; If the basic information verification of the personnel leaving the production line is passed, the difference between the second-site first feature information and the first feature information of the personnel leaving the production line is obtained. If the difference and the difference between the first verification information of the corresponding personnel are within the set difference threshold range, the personnel safety verification passes; otherwise, the personnel safety verification fails.

[0021] The cloud-based security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud-based personnel database, wherein the characteristic information is the preset second verification information; the second verification information is the personnel identification information, and the personnel identification information includes infrared information and face information.

[0022] like Figure 2 As shown, the industrial production line safety monitoring system based on artificial intelligence applies the industrial production line safety monitoring method based on artificial intelligence, including a production management module, a local service module, a cloud data server, a communication module, a personnel management module and a production site data acquisition module; The communication module, personnel management module and production site data acquisition module are respectively connected to the local service module; the cloud data server is connected to the communication module; and the production management module is connected to the cloud data server.

[0023] Specifically, the artificial intelligence-based industrial production line safety monitoring method of the present invention comprises the following steps: Step 1: Cloud Data Preparation The data server generates a cloud-based security monitoring container corresponding to the production cycle number in the production cycle information based on the production cycle information generated by the production management module. The production cycle information is obtained by the production management module based on the production line information corresponding to the IP address of the local service module, including the production cycle personnel information list of the corresponding production line in the production plan, the production cycle start and end times (including the start time and the end time), and the production cycle number. Among them, the production cycle also specifically defines the cut-off time for personnel to enter the production line for verification and the cut-off time for personnel to leave the production line to ensure the timeliness of monitoring.

[0024] The cloud data server calls the corresponding personnel verification information in the cloud personnel database according to the production cycle personnel information list in the production cycle information, and sends it to the cloud security monitoring container corresponding to the production cycle sequence number. The personnel verification information is the preset basic identity information and the first feature information associated with the basic identity information. The first feature information can be unified feature information (such as the height and weight of all people) or independent feature information (that is, each person has a different feature type). The feature type includes but is not limited to height, weight, and resting pulse frequency, etc., to enhance the accuracy and flexibility of the verification.

[0025] Step 2: Production cycle start and personnel information collection At the start and end time of the production cycle, the cloud data server connects the cloud security monitoring container corresponding to the production cycle number to the local service module according to the IP address information of the local service module. The local service module collects the personnel information entering the production line through the personnel management module, including basic identity information and the first characteristic information collected on site.

[0026] Step 3: Personnel entry verification The local service module sends the collected personnel information to the cloud security monitoring container corresponding to the production cycle number for verification. The verification process includes basic identity information comparison and the difference calculation between the first feature information on site and the preset first feature information. If the basic identity information verification passes and the feature information difference is within the allowable range, the first verification information of the corresponding personnel (i.e., the feature information difference) is generated, and the verified personnel information and the first verification information are sent back to the local service module before the personnel enter the production line verification deadline.

[0027] Step 4: Verification of personnel entering and leaving The local service module verifies the personnel who subsequently enter and exit the production line based on the received verified personnel information and the first verification information. If there is a mismatch in the basic information of the personnel or an abnormal difference in the characteristic information (exceeding the set threshold), it is determined that the personnel verification is abnormal, and the local service module immediately sends an alarm message to the production management module. If there is no non-abnormal situation, the next step is entered at the deadline for the personnel to leave the production line.

[0028] Step 5: Verification of personnel leaving the venue The local service module collects the basic information of the personnel leaving the site and the first characteristic information of the second site through the personnel management module, and compares it with the information of the personnel entering the production line who have passed the verification. If all the personnel leaving the site can find a match in the information of the personnel entering the production line, and the difference in characteristic information is within the set threshold, it is considered that the personnel safety verification has passed and enter step 7; otherwise, enter step 6 for further processing.

[0029] Step 6: Exception handling For personnel who leave the production line without verification, the local service module sends their information to the cloud security monitoring container. The cloud data server calls the second verification information of the person from the cloud personnel database (such as infrared information, facial information and other more detailed identification information) and sends it to the local service module. The production site data acquisition module uses this information to identify personnel at the production site through artificial intelligence algorithms. If the corresponding personnel is identified, a departure notification message is issued and the process returns to step five for re-verification; if not identified, the local service module sends an alarm message to the production management module, indicating that there may be personnel retention or illegal departure.

[0030] Step 7: Monitoring completed When all personnel leaving the site have passed the verification and confirmed that there are no omissions, the safety monitoring of the production cycle of the industrial production line is completed, and the system is ready to enter the monitoring preparation stage of the next production cycle.

[0031] To implement the above method, the present invention also provides an industrial production line safety monitoring system based on artificial intelligence, comprising: Production management module: responsible for generating production cycle information according to the production plan, including production line information, production cycle personnel information list, production cycle start and end time and production cycle serial number, etc.

[0032] Local service module: deployed on the production line, responsible for communicating with the production management module and cloud data server, and performing functions such as personnel information collection, verification and abnormal alarm.

[0033] Cloud data server: stores the cloud personnel database, generates cloud security monitoring containers according to the instructions of the production management module, processes personnel verification information, and exchanges data with the local service module.

[0034] Communication module: realizes data transmission between local service module and cloud data server.

[0035] Personnel management module: integrated into the local service module, responsible for collecting personnel information entering and leaving the production line, including basic identity information and on-site feature information.

[0036] Production site data collection module: uses cameras, infrared sensors and other equipment, combined with artificial intelligence algorithms, to achieve production site personnel identification and monitoring. Example

[0037] An assembly production line of a certain automobile manufacturing plant adopts the artificial intelligence-based industrial production line safety monitoring method of the present invention to perform safety management of daily production cycles.

[0038] According to the production plan, the production management module generates the production cycle information for a certain week (production cycle number: 2023W10), including the list of production personnel of the assembly line during the cycle (Zhang San, Li Si, etc.), the start and end time of the production cycle (8:00 on March 6, 2023 to 17:00 on March 10, 2023), the deadline for personnel to enter the production line for verification is 1 hour after the start of work every day, and the deadline for personnel to leave the production line is half an hour before the end of work every day.

[0039] Based on the list of production personnel, the cloud data server retrieved the basic information (such as name, work number) and first characteristic information (such as height, weight, and resting pulse rate) of Zhang San, Li Si, and others from the cloud personnel database, and sent this information to the cloud security monitoring container with serial number 2023W10.

[0040] Production cycle start-up and personnel information collection: At 8:00 on March 6, the cloud data server connected the cloud security monitoring container with serial number 2023W10 to the local service module of the assembly production line.

[0041] The local service module collects the basic identity information and the first feature information of Zhang San, Li Si and others who enter the production line through the personnel management module.

[0042] Personnel entry verification: The local service module sends the collected personnel information to the cloud security monitoring container for verification. The basic identity information of Zhang San and Li Si matches, and the difference between the first feature information on the scene and the preset information is within the allowable range. Their first verification information is generated, and the verified personnel information and the first verification information are sent back to the local service module before 9:00.

[0043] Verification of personnel entering and exiting the production line: The local service module verifies the personnel entering and exiting the production line based on the information of the personnel who have passed the verification. On March 7, the basic information of a person who tried to enter the production line did not match, and the local service module immediately sent an alarm message to the production management module.

[0044] Verification of personnel leaving the site: At 16:30 on March 10, the local service module collected the basic information of personnel leaving the site and the first characteristic information of the second site, and compared it with the information of personnel entering the production line who passed the verification. All personnel were matched and the difference in characteristic information was within the set threshold.

[0045] Monitoring completed: After confirming that all personnel leaving the site have passed the verification, the system completes the safety monitoring of this production cycle and prepares to enter the monitoring preparation stage of the next production cycle.

Claims

1. An industrial production line safety monitoring method based on artificial intelligence, characterized in that: The steps include: Step 1: The cloud data server generates a cloud security monitoring container corresponding to the production cycle number in the production cycle information according to the production cycle information generated by the production management module, and calls the corresponding personnel verification information in the cloud personnel database according to the production cycle personnel information list in the production cycle information, and sends it to the cloud security monitoring container corresponding to the production cycle number; Step 2: At the start and end time of the production cycle, the cloud data server connects the cloud security monitoring container corresponding to the production cycle number to the local service module according to the IP address information of the local service module, and the local service module collects the personnel information entering the production line through the personnel management module; Step 3: The local service module sends the personnel information of the personnel entering the production line collected by the personnel management module to the cloud security monitoring container corresponding to the production cycle number, and performs personnel verification in the cloud security monitoring container corresponding to the production cycle number. If the personnel verification passes, the first verification information of the corresponding personnel is generated. At the end time of the personnel verification entering the production line, the cloud security monitoring container corresponding to the production cycle number sends the personnel information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel to the local service module; Step 4: The local service module verifies the personnel entering and leaving the production line according to the personnel information that has passed the verification and the first verification information of the corresponding personnel. If there is an abnormality in the personnel verification, the local service module sends an alarm message to the production management module; if there is no abnormality in the personnel verification, the production management module enters step 5 at the cut-off time for the personnel to leave the production line. Step 5: The local service module collects the information of the personnel leaving the production line through the personnel management module, and verifies the information of the personnel leaving the production line according to the information of the personnel entering the production line who have passed the verification and the first verification information of the corresponding personnel. If there is no personnel leaving the production line who has not passed the verification, proceed to step 7, otherwise proceed to step 6; Step 6: Based on the information of the personnel who have passed the verification and entered the production line, the information of the personnel who have not passed the verification and left the production line is obtained. The local service module sends the information of the personnel who have not passed the verification and left the production line to the cloud security monitoring container corresponding to the production cycle number. The cloud security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud personnel database and sends it to the local service module. The production site data collection module identifies the personnel at the production site based on the characteristic information of the corresponding personnel. If the corresponding personnel is identified, a departure notification message is issued and the process returns to step 5; otherwise, the local service module sends an alarm message to the production management module. Step seven: Complete safety monitoring of the industrial production line production cycle.

2. The artificial intelligence-based industrial production line safety monitoring method according to claim 1 is characterized in that: The production cycle information generated by the production management module includes: The production management module obtains the production cycle personnel information list, production cycle start and end time, and production cycle sequence number of the corresponding production line in the production plan according to the production line information corresponding to the IP address of the local service module; The production cycle includes the cut-off time for personnel to enter the production line for verification and the cut-off time for personnel to leave the production line.

3. The artificial intelligence-based industrial production line safety monitoring method according to claim 2 is characterized in that: According to the production cycle personnel information list in the production cycle information, the corresponding personnel verification information is called in the cloud personnel database and sent to the cloud security monitoring container corresponding to the production cycle sequence number, wherein the personnel verification information is the preset basic identity information and the first feature information associated with the basic identity information; The first characteristic information associated with the basic identity information is unified characteristic information or independent characteristic information; the unified characteristic information, i.e., the first characteristic associated with the basic identity information, is of the same characteristic type; the independent characteristic information, i.e., the first characteristic types associated with the basic identity information are all different; the characteristic types of the first characteristic include height, weight and resting pulse rate.

4. The artificial intelligence-based industrial production line safety monitoring method according to claim 3 is characterized in that: The personnel verification is performed in the cloud security monitoring container corresponding to the production cycle sequence number. If the personnel verification passes, the first verification information of the corresponding personnel is generated, including: The personnel management module collects the basic identity information and on-site first feature information of personnel entering the production line, and verifies the basic identity information of the personnel in the cloud-based security monitoring container corresponding to the production cycle number. If the basic identity information verification passes, the difference between the on-site first feature information and the first feature information is the first verification information of the corresponding personnel.

5. The artificial intelligence-based industrial production line safety monitoring method according to claim 4 is characterized in that: The step of verifying the information of personnel leaving the production line according to the information of personnel entering the production line and the first verification information of the corresponding personnel includes: The personnel management module collects the basic information of the personnel leaving the production line and the first characteristic information of the second site, and matches and verifies the basic information of the personnel leaving the production line with the information of the personnel entering the production line after verification. If the information of the personnel entering the production line after verification is matched and verified, there is no person who has not passed the verification and left the production line; otherwise, there is a person who has not passed the verification and left the production line; If the basic information verification of the personnel leaving the production line is passed, the difference between the second-site first feature information and the first feature information of the personnel leaving the production line is obtained. If the difference and the difference between the first verification information of the corresponding personnel are within the set difference threshold range, the personnel safety verification passes; otherwise, the personnel safety verification fails.

6. The artificial intelligence-based industrial production line safety monitoring method according to claim 5 is characterized in that: The cloud-based security monitoring container corresponding to the production cycle number calls the characteristic information of the corresponding personnel from the cloud-based personnel database, wherein the characteristic information is the preset second verification information; the second verification information is the personnel identification information, and the personnel identification information includes infrared information and face information.

7. The industrial production line safety monitoring system based on artificial intelligence is characterized by: The artificial intelligence-based industrial production line safety monitoring method according to any one of claims 1 to 6 is applied, comprising a production management module, a local service module, a cloud data server, a communication module, a personnel management module and a production site data acquisition module; The communication module, personnel management module and production site data acquisition module are respectively connected to the local service module; the cloud data server is connected to the communication module; and the production management module is connected to the cloud data server.

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