Safety production monitoring system and method based on Internet of Things equipment

Abstract

The invention relates to the technical field of Internet of Things and safety production monitoring, in particular to a safety production monitoring system and method based on Internet of Things equipment. Comprising Internet of Things equipment, a transmission architecture, a remote monitoring center, a safety report generation module and an alarm device, and the remote monitoring center comprises a data interaction user interface, an intelligent data analysis module and an intelligent data early warning module. By means of the monitoring system and the monitoring method, the real-time performance and the comprehensiveness of construction site monitoring are greatly improved, and more efficient, intelligent and stable monitoring and management are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things technology and production safety monitoring, and in particular to a production safety monitoring system and method based on Internet of Things equipment. Background Art

[0002] In modern construction site safety management, traditional methods mainly include manual inspection and monitoring equipment. However, with the expansion of construction site scale and the increase of complexity, these traditional methods have gradually exposed many problems. Choudhry, RM, Fang, D., and Ahmed, SM mentioned in "Construction Safety Management in Hong Kong: Best Practices" that manual inspection is inefficient and cannot achieve real-time monitoring around the clock due to human resources and working hours. In addition, manual inspection is easily affected by subjective factors, and there may be problems such as missed inspections and false inspections.

[0003] Guo, H., Yu, Y., and Skitmore, M. pointed out in "Construction Safety Management Based on Visualization Technology: A Review" that although traditional monitoring equipment, such as cameras and sensors, have improved monitoring capabilities to a certain extent, they still have many limitations when dealing with complex and changing construction site environments. These devices usually only provide limited monitoring coverage and lack intelligent data analysis and processing capabilities, and cannot effectively respond to emergencies or potential safety hazards. With the development of Internet of Things (IoT) technology, more and more research and applications have begun to introduce IoT technology into the field of production safety monitoring. Kanan, R., Elhassan, O., and Bensalem, R. and

[0004] Zhong, RY, Peng, Y., Xue, F., Fang, J., Zou, W., Luo, H., Ng, ST, Lu, W., Shen, GQ, and Huang, GQ discussed how IoT technology can achieve real-time collection, transmission and analysis of environmental data by connecting various sensors, devices and systems in "Autonomous worker safety system based on IoT: real-time alarm, monitoring and positioning strategy" and "Prefabrication construction supported by IoT". Woodhead, R., Stephenson, P., and Morrey, D. also mentioned in "Digital construction: from point solutions to IoT ecosystem" that applying IoT to construction site safety production monitoring can not only improve the real-time monitoring, but also realize the analysis and early warning of complex data through intelligent algorithms, thereby improving the level of safety management. However, Augustin, A., Yi, J., Clausen, T., and Townsley, W. pointed out in "LoRa Research: Long-distance, Low-power Networks for the Internet of Things" that current research and applications are mostly concentrated in relatively closed and stable environments, such as industrial plants and smart buildings. For the open and complex environment of construction sites, Zhang, M., Shi, R., and Yang, Z. emphasized in "A Critical Review of Vision-based Occupational Health and Safety Monitoring for Construction Workers" that existing IoT monitoring systems often lack targeted designs and are difficult to fully adapt to the diverse needs of construction site environments. For example, Lee, UK, Kim, JH, Cho, H., and Kang, KI mentioned in "Development of Mobile Safety Monitoring Systems for Construction Sites" that many IoT-based safety monitoring systems in existing technologies only consider limited environmental parameters, such as temperature and humidity, while ignoring the unique hazardous factors in construction sites, such as dust concentration, vibration, and toxic gas concentration. In addition, Wu, W., Yang, H., Chew, DA, Yang, SH, Gibb, AG, and Li, Q. found in their study "Automated System for Real-time Tracking of Near Miss Accidents on Construction Sites" that these systems rely on centralized cloud computing models for data processing and cannot quickly respond to emergencies on site, thus affecting real-time safety monitoring and emergency response on construction sites. Therefore, in this context, it is urgent to develop a safety production monitoring system based on the Internet of Things technology for construction sites to adapt to the complexity and diverse needs of the construction site environment.

[0005] Traditional monitoring methods cannot achieve comprehensive real-time monitoring in complex and changeable construction site environments, resulting in insufficient timeliness and accuracy of monitoring data; existing systems mainly rely on manual inspections or simple sensor alarms, lack intelligent analysis and early warning functions, and cannot identify potential safety hazards in advance, thereby increasing the safety risks of the construction site; due to the openness and complexity of the construction site environment, the data transmission process of the existing monitoring system is susceptible to interference, resulting in loss or delay of monitoring data, affecting the monitoring effect; in addition, traditional systems usually rely on a single monitoring center for centralized management, lack flexible remote control and multi-terminal management functions, and are difficult to meet the needs of modern construction site management. The present invention aims to effectively solve these problems by providing a production safety monitoring system based on the Internet of Things technology, thereby achieving more efficient, intelligent and stable monitoring and management. Summary of the invention

[0006] In response to the technical problems mentioned in the background technology, the present invention proposes a production safety monitoring system and method based on Internet of Things devices.

[0007] To achieve this purpose, the present invention adopts the following technical solution: a production safety monitoring system based on Internet of Things devices, comprising:

[0008] IoT devices are installed at the construction site to collect multi-source data in real time, including on-site environmental data, personnel activity data, and equipment status information data;

[0009] The transmission architecture is used to transmit the collected multi-source data to the remote monitoring center through the LoRa gateway, 5G / LET router, and the Internet in sequence;

[0010] Remote monitoring center, including data interactive user interface, intelligent data analysis module, and intelligent data early warning module;

[0011] The data interactive user interface is used to receive environmental data and personnel activity data and convert them into monitoring images for viewing;

[0012] The intelligent data analysis module is connected to the data intelligent data warning module, and is used to receive and analyze environmental data. When the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data warning module; the intelligent data analysis module also receives and analyzes personnel activity data. The intelligent data analysis module stores verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data warning module; the intelligent data analysis module also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data warning module; the intelligent data analysis module also receives and analyzes equipment status information data. The intelligent data analysis module stores the equipment safety operation threshold. When the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data warning module;

[0013] An intelligent data early warning module is connected to a safety report generation module, and is used to receive environmental anomalies, personnel anomalies, protection anomalies, and equipment anomalies, and generate corresponding alarm data and send them to the safety report generation module;

[0014] A safety report generation module, connected to the data interaction user interface and simultaneously connected to an alarm device, for receiving alarm data and generating a safety report, displaying it on the data interaction user interface, and controlling the alarm device to generate an alarm;

[0015] An alarm device is used to generate an alarm.

[0016] As a further technical solution of the present invention, the Internet of Things device includes an environmental sensor, an equipment sensor, and a camera. The environmental sensor is used to collect environmental data, the equipment sensor is used to collect equipment status information data, and the camera is used to collect personnel activity data.

[0017] As a further technical solution of the present invention, the LoRa gateway is installed at the center of the construction site and is used to connect the environmental sensors, equipment sensors, and cameras of the entire construction site.

[0018] As a further technical solution of the present invention, the LoRa gateway is connected to the Internet through a 5G / LET router at the same time, and realizes data transmission with the Internet through the TCP / IP protocol.

[0019] Another object of the present invention is to provide a safety production monitoring method based on Internet of Things devices, comprising the following steps:

[0020] S1. Collect environmental data, personnel activity data and equipment status information data using IoT devices and transmit them to the remote monitoring center in real time through the transmission architecture;

[0021] S2, the remote monitoring center receives and analyzes the environmental data, and when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0022] S2', the remote monitoring center receives and analyzes the personnel activity data synchronously with step S2, and the intelligent data analysis module stores the verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data early warning module; jump to step S3; the intelligent data analysis module also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0023] S2”, the remote monitoring center receives and analyzes the equipment status information data synchronously with step S2, the intelligent data analysis module stores the equipment safety operation threshold, and when the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0024] S3, the remote monitoring center receives environmental anomalies, personnel anomalies, protection anomalies and equipment anomalies and sends them to the intelligent data warning module;

[0025] S4, the intelligent data warning module generates corresponding alarm data and sends it to the security report generation module;

[0026] S5. The safety report generation module receives the alarm data and generates a safety report, which is displayed on the data interaction user interface, and at the same time controls the alarm device to generate an alarm.

[0027] As a further technical solution of the present invention, the collected environmental data in step S1 is collected by an environmental sensor, and the environmental data includes: environmental temperature and humidity, air quality, concentration of harmful gases and noise level. In step S2, when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module.

[0028] As a further technical solution of the present invention, the personnel activity data in step S1 is collected by a camera, and the personnel activity data includes facial data; in step S2', the intelligent data analysis module stores the verified personnel identity data, and when the received facial data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data warning module.

[0029] As a further technical solution of the present invention, in the step S1, the equipment status information data is collected by the equipment sensor, and the equipment status information data includes: equipment vibration and equipment temperature; in the step S2", the intelligent data analysis module stores the equipment safety operation threshold, and when the received equipment vibration and equipment temperature exceed the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module.

[0030] Compared with the existing technology, the present invention has the following beneficial effects: Greatly improved real-time and comprehensiveness: By deploying environmental sensors, equipment sensors, cameras and other devices, multi-source data of the construction site is collected in real time, and all-round on-site monitoring is achieved through LoRa wireless communication technology. Whether it is environmental data, personnel activity data or equipment status information data, the system can monitor and feedback in real time, greatly improving the safety management level of the construction site;

[0031] The stability and efficiency of data transmission are significantly enhanced: the present invention adopts a layered data transmission architecture, combining the advantages of TCP / IP wired communication and LoRa wireless communication to ensure high stability and efficiency of data transmission. With its long distance and low power consumption, LoRa technology is particularly suitable for remote data transmission at large construction sites, and can ensure reliable data transmission even in areas with weak or no signals.

[0032] Strengthening of intelligent analysis and early warning capabilities: The present invention can conduct in-depth analysis and mining of collected multi-source data. The system can not only automatically identify potential risks at the construction site, but also generate safety reports and promptly notify management personnel through the early warning function. This intelligent safety management method significantly improves the accuracy and response speed of risk identification, and effectively reduces the incidence of safety accidents.

[0033] The system is more scalable and adaptable: The system architecture of the present invention is highly scalable, and the deployment and management of IoT devices can be flexibly adjusted according to the actual needs of different construction sites. At the same time, the system supports seamless connection with third-party platforms (such as BIM, project management systems), further expanding the application scenarios of the system and being able to adapt to the needs of construction projects of different scales and complexities.

[0034] Improved management efficiency and data transparency: The system collects and analyzes multi-source data in real time, makes the data transparent and presents it in a centralized data interactive user interface, enabling managers to fully and timely understand the actual situation on the construction site.

[0035] Balance between economic benefits and safety: Through the automated monitoring and intelligent management of IoT devices, the system can significantly reduce the cost of manual inspections while improving the safety of construction sites. By identifying and preventing potential safety hazards early, the system can effectively avoid the occurrence of safety accidents, thereby reducing downtime, fines and other related costs caused by accidents, and ultimately achieving a win-win situation for safety and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the structure of the monitoring system of the present invention.

[0037] Figure 2 It is a schematic diagram of the connection relationship between the transmission architecture of the present invention, the Internet of Things equipment and the remote monitoring center.

[0038] Figure 3 It is a flow chart of the production safety monitoring method of the present invention. DETAILED DESCRIPTION

[0039] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with specific embodiments. 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.

[0040] See also Figure 1 As shown, a safety production monitoring system based on Internet of Things devices includes

[0041] The IoT device 10 is installed at the construction site and is used to collect multi-source data in real time, wherein the multi-source data includes on-site environmental data, personnel activity data, and equipment status information data;

[0042] The transmission architecture 20 is used to transmit the collected multi-source data to the remote monitoring center 30 through the LoRa gateway 21, the 5G / LET router 22, and the Internet 23 in sequence;

[0043] The remote monitoring center 30 includes a data interaction user interface 31, an intelligent data analysis module 32, and an intelligent data early warning module 33;

[0044] The data interaction user interface 31 is used to receive environmental data and personnel activity data and convert them into monitoring images for viewing;

[0045] The intelligent data analysis module 32 is connected to the intelligent data warning module 33, and is used to receive and analyze environmental data. When the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data warning module 33; the intelligent data analysis module 32 also receives and analyzes personnel activity data. The intelligent data analysis module 32 stores verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data warning module 33; the intelligent data analysis module 32 also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data warning module 33; the intelligent data analysis module 32 also receives and analyzes equipment status information data. The intelligent data analysis module 32 stores the equipment safety operation threshold. When the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data warning module 33;

[0046] The intelligent data early warning module 33 is connected to a safety report generation module 40, and is used to receive environmental anomalies, personnel anomalies, protection anomalies and equipment anomalies, and generate corresponding alarm data and send them to the safety report generation module 40;

[0047] A safety report generation module 40, connected to the data interaction user interface 31 and simultaneously connected to an alarm device 50, for receiving alarm data and generating a safety report, displaying it on the data interaction user interface 31, and controlling the alarm device 50 to generate an alarm;

[0048] The alarm device 50 is used to generate an alarm.

[0049] The IoT device includes an environmental sensor 11, an equipment sensor 12, and a camera 13. The environmental sensor 11 is used to collect environmental data, the equipment sensor 12 is used to collect equipment status information data, and the camera 13 is used to collect personnel activity data. The environmental data includes: environmental temperature and humidity, air quality, harmful gas concentration, and noise level. When the environmental data analysis result received by the intelligent data analysis module 32 is abnormal, the environmental abnormality is sent to the intelligent data early warning module 33. Personnel activity data includes face data; the intelligent data analysis module 32 stores the verified personnel identity data. When the received face data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data early warning module 33. The equipment status information data includes equipment vibration and equipment temperature. The intelligent data analysis module 32 stores the equipment safety operation threshold. When the received equipment vibration and equipment temperature exceed the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module 33.

[0050] The real-time and comprehensiveness of the safety production monitoring system of this embodiment has been greatly improved: by deploying environmental sensors, equipment sensors, cameras and other devices, multi-source data of the construction site is collected in real time, and all-round on-site monitoring is achieved through LoRa wireless communication technology. Whether it is environmental data, personnel activity data or equipment status information data, the system can monitor and feedback in real time, greatly improving the safety management level of the construction site.

[0051] In some embodiments, Figure 2 As shown, the LoRa gateway is installed at the center of the construction site to connect the environmental sensors, equipment sensors, and cameras of the entire construction site. The LoRa gateway is also connected to the Internet through a 5G / LET router, and realizes data transmission with the Internet through the TCP / IP protocol. The layered data transmission architecture is adopted, combining the advantages of TCP / IP wired communication and LoRa wireless communication to ensure high stability and efficiency of data transmission. With its long distance and low power consumption, LoRa technology is particularly suitable for remote data transmission in large-scale construction sites, and can still ensure reliable data transmission even in areas with weak or no signals.

[0052] like Figure 3 As shown, a safety production monitoring method based on Internet of Things devices includes the following steps:

[0053] S1. Collect environmental data, personnel activity data and equipment status information data using IoT devices and transmit them to the remote monitoring center in real time through the transmission architecture;

[0054] S2, the remote monitoring center receives and analyzes the environmental data, and when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0055] S2', the remote monitoring center receives and analyzes the personnel activity data synchronously with step S2, and the intelligent data analysis module stores the verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data early warning module; jump to step S3; the intelligent data analysis module also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0056] S2”, the remote monitoring center receives and analyzes the equipment status information data synchronously with step S2, the intelligent data analysis module stores the equipment safety operation threshold, and when the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1;

[0057] S3, the remote monitoring center receives environmental anomalies, personnel anomalies, protection anomalies and equipment anomalies and sends them to the intelligent data warning module;

[0058] S4, the intelligent data warning module generates corresponding alarm data and sends it to the security report generation module;

[0059] S5. The safety report generation module receives the alarm data and generates a safety report, which is displayed on the data interaction user interface, and at the same time controls the alarm device to generate an alarm.

[0060] The collected environmental data in step S1 is collected by environmental sensors, and the environmental data include: environmental temperature and humidity, air quality, harmful gas concentration and noise level. In step S2, when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module. The personnel activity data in step S1 is collected by a camera, and the personnel activity data includes facial data; in step S2', the intelligent data analysis module stores the verified personnel identity data. When the received facial data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data early warning module. In step S1, the equipment status information data is collected by the equipment sensor, and the equipment status information data includes: equipment vibration and equipment temperature; in step S2", the intelligent data analysis module stores the equipment safety operation threshold. When the received equipment vibration and equipment temperature exceed the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module.

[0061] The present invention can conduct in-depth analysis and mining of the collected multi-source data. The system can not only automatically identify potential risks at the construction site, but also generate safety reports and promptly notify management personnel through the early warning function. This intelligent safety management method significantly improves the accuracy and response speed of risk identification and effectively reduces the incidence of safety accidents.

[0062] The system is more scalable and adaptable: The system architecture of the present invention is highly scalable, and the deployment and management of IoT devices can be flexibly adjusted according to the actual needs of different construction sites. At the same time, the system supports seamless connection with third-party platforms (such as BIM, project management systems), further expanding the application scenarios of the system and being able to adapt to the needs of construction projects of different scales and complexities.

[0063] Improved management efficiency and data transparency: The system collects and analyzes multi-source data in real time, makes the data transparent and presents it in a centralized data interactive user interface, enabling managers to fully and timely understand the actual situation on the construction site.

[0064] Balance between economic benefits and safety: Through the automated monitoring and intelligent management of IoT devices, the system can significantly reduce the cost of manual inspections while improving the safety of construction sites. By identifying and preventing potential safety hazards early, the system can effectively avoid the occurrence of safety accidents, thereby reducing downtime, fines and other related costs caused by accidents, and ultimately achieving a win-win situation for safety and economy.

[0065] The technical principle of the present invention is described above in conjunction with specific embodiments. These descriptions are only for explaining the principle of the present invention and cannot be interpreted as limiting the scope of protection of the present invention in any way. Based on the explanations herein, those skilled in the art can associate other specific implementations of the present invention without paying creative labor, and these methods will fall within the scope of protection of the present invention.

Claims

1. A production safety monitoring system based on Internet of Things devices, characterized by: include IoT devices are installed at the construction site to collect multi-source data in real time, including on-site environmental data, personnel activity data, and equipment status information data; The transmission architecture is used to transmit the collected multi-source data to the remote monitoring center through the LoRa gateway, 5G / LET router, and the Internet in sequence; Remote monitoring center, including data interactive user interface, intelligent data analysis module, and intelligent data early warning module; The data interactive user interface is used to receive environmental data and personnel activity data and convert them into monitoring images for viewing; The intelligent data analysis module is connected to the data intelligent data warning module, and is used to receive and analyze environmental data. When the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data warning module; the intelligent data analysis module also receives and analyzes personnel activity data. The intelligent data analysis module stores verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data warning module; the intelligent data analysis module also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data warning module; the intelligent data analysis module also receives and analyzes equipment status information data. The intelligent data analysis module stores the equipment safety operation threshold. When the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data warning module; An intelligent data early warning module is connected to a safety report generation module, and is used to receive environmental anomalies, personnel anomalies, protection anomalies, and equipment anomalies, and generate corresponding alarm data and send them to the safety report generation module; A safety report generation module, connected to the data interaction user interface and simultaneously connected to an alarm device, for receiving alarm data and generating a safety report, displaying it on the data interaction user interface, and controlling the alarm device to generate an alarm; An alarm device is used to generate an alarm.

2. A safety production monitoring system based on Internet of Things devices according to claim 1, characterized in that: The Internet of Things device includes an environmental sensor, an equipment sensor, and a camera. The environmental sensor is used to collect environmental data, the equipment sensor is used to collect equipment status information data, and the camera is used to collect personnel activity data.

3. A production safety monitoring system based on Internet of Things devices according to claim 2, characterized in that: The LoRa gateway is installed at the center of the construction site and is used to connect the environmental sensors, equipment sensors, and cameras of the entire construction site.

4. A production safety monitoring system based on Internet of Things devices according to claim 3, characterized in that: The LoRa gateway is connected to the Internet through a 5G / LET router and realizes data transmission with the Internet through the TCP / IP protocol.

5. A safety production monitoring method based on Internet of Things equipment, characterized in that: The steps include: S1. Collect environmental data, personnel activity data and equipment status information data using IoT devices and transmit them to the remote monitoring center in real time through the transmission architecture; S2, the remote monitoring center receives and analyzes the environmental data, and when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module; Jump to step S3; otherwise jump back to step S1; S2', the remote monitoring center receives and analyzes the personnel activity data synchronously with step S2, and the intelligent data analysis module stores the verified personnel identity data. When the received personnel activity data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data early warning module; jump to step S3; the intelligent data analysis module also analyzes the wearing of protective equipment by the active personnel. When the active personnel do not wear protective equipment, the protective abnormality is sent to the intelligent data early warning module; jump to step S3; otherwise jump back to step S1; S2”, the remote monitoring center receives and analyzes the equipment status information data synchronously with step S2, the intelligent data analysis module stores the equipment safety operation threshold, and when the received equipment status information data exceeds the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module; Jump to step S3; otherwise jump back to step S1; S3, the remote monitoring center receives environmental anomalies, personnel anomalies, protection anomalies and equipment anomalies and sends them to the intelligent data warning module; S4, the intelligent data warning module generates corresponding alarm data and sends it to the security report generation module; S5. The safety report generation module receives the alarm data and generates a safety report, which is displayed on the data interaction user interface, and at the same time controls the alarm device to generate an alarm.

6. A method for monitoring production safety based on Internet of Things devices according to claim 5, characterized in that: The collected environmental data in step S1 is collected by environmental sensors, and the environmental data includes: environmental temperature and humidity, air quality, harmful gas concentration and noise level. In step S2, when the analysis result of the received environmental data is abnormal, the environmental abnormality is sent to the intelligent data early warning module.

7. A method for monitoring production safety based on Internet of Things devices according to claim 6, characterized in that: The personnel activity data in step S1 is collected by a camera, and the personnel activity data includes facial data; in step S2', the intelligent data analysis module stores the verified personnel identity data, and when the received facial data does not match the verified personnel identity data, the personnel abnormality is sent to the intelligent data warning module.

8. A method for monitoring production safety based on Internet of Things devices according to claim 7, characterized in that: In the step S1, the equipment status information data is collected by the equipment sensor, and the equipment status information data includes: equipment vibration and equipment temperature; in the step S2", the intelligent data analysis module stores the equipment safety operation threshold, and when the received equipment vibration and equipment temperature exceed the equipment safety operation threshold, the equipment abnormality is sent to the intelligent data early warning module.

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