Fireworks and crackers safety production risk monitoring and early warning system based on Internet of Things

Abstract

The invention discloses a firework and cracker safety production risk monitoring and early warning system based on the Internet of Things, which belongs to the field of monitoring and early warning systems and comprises a comprehensive information supervision subsystem, a risk monitoring and early warning subsystem, a meteorological disaster early warning subsystem, a dose acquisition and monitoring subsystem, an overload monitoring and early warning subsystem and an intelligent analysis and display subsystem. The comprehensive information supervision subsystem provides a management function including enterprise basic information, warehouse information, main principal information, equipment facility information, high-definition azimuth map information, firework and cracker experts and peripheral emergency resources; the risk monitoring and early warning subsystem collects real-time monitoring and alarm data of existing field real-time monitoring videos, environmental parameters, smoke alarms and perimeter intrusion of an access enterprise. According to the invention, various hidden dangers in the production process of fireworks and crackers can be comprehensively monitored, early warning is given out in time after abnormity is found, and the requirements of modern safety management are fully met.

Description

Technical Field

[0001] The present invention relates to the field of monitoring and early warning systems, and in particular to a fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things. Background Art

[0002] As a traditional festival product, fireworks and firecrackers have many potential safety hazards during production, storage and sales, such as fire and explosion. In order to further eliminate hidden dangers and improve safety, it is necessary to conduct safety monitoring on enterprises producing fireworks and firecrackers. Traditional safety monitoring usually relies on manual inspections and simple physical measurements, which have monitoring loopholes and safety hazards. With the development of Internet of Things technology, people apply the Internet of Things to the field of security monitoring.

[0003] However, existing security monitoring methods based on the Internet of Things often have problems such as incomplete monitoring and untimely warning, which are difficult to meet the needs of modern safety management. Therefore, those skilled in the art provide a fireworks and firecrackers safety production risk monitoring and early warning system based on the Internet of Things to solve the problems raised in the above background technology. Summary of the invention

[0004] The purpose of the present invention is to provide a fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things, which can comprehensively monitor various hidden dangers in the production process of fireworks and firecrackers, and issue early warnings in time after discovering abnormalities, fully meeting the needs of modern safety management and solving the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things, including a comprehensive information supervision subsystem, a risk monitoring and early warning subsystem, a meteorological disaster early warning subsystem, a drug quantity collection and monitoring subsystem, an overcrowding monitoring and early warning subsystem, and an intelligent analysis and display subsystem;

[0007] The comprehensive information supervision subsystem provides management functions including basic enterprise information, warehouse information, information of main responsible persons, equipment and facility information, high-definition location map information, fireworks and firecrackers experts, and surrounding emergency resources, providing data support for remote supervision of fireworks and firecrackers storage enterprises and emergency response in the event of emergencies;

[0008] The risk monitoring and early warning subsystem collects and accesses the company's existing on-site real-time monitoring video, environmental parameters, smoke alarms, and real-time monitoring and alarm data of perimeter intrusions, analyzes whether there are any abnormalities, and provides early warning functions when abnormalities occur. It also provides remote video inspection, video patrol, and historical video review functions;

[0009] The meteorological disaster warning subsystem is connected to the meteorological department's meteorological disaster warning data and analyzes it. In order to prevent disasters caused by severe weather such as heavy snow and thunderstorms, it can automatically push warning information to enterprises before severe weather arrives to remind them to take precautions.

[0010] The drug quantity collection and monitoring subsystem is used to collect the in-and-out information of fireworks and firecrackers in real time, set the alarm threshold through the background, and compare the real-time data with the alarm threshold in real time in the background, and issue an early warning in case of excessive storage;

[0011] The overcrowding monitoring and early warning subsystem adds intelligent recognition cameras to the front and rear doors of the enterprise warehouse, and uses the AI ​​intelligent analysis function to perform real-time analysis and calculation of the number of people entering and leaving the warehouse in the same period of time, so as to determine whether the actual number of people in the warehouse is overcrowded, and issue an early warning if overcrowding occurs;

[0012] The intelligent analysis and display subsystem uses a display mode that combines EGIS maps and big data analysis charts to display fireworks and firecracker storage companies, warehouses of various types / levels, surrounding emergency resources, real-time monitoring videos, each company's existing drug capacity, overcrowding / overquantity warning data, environmental alarm data, intrusion alarm data and meteorological data based on a large model.

[0013] As a further solution of the present invention: the risk monitoring and early warning subsystem combines the collected real-time monitoring video on site with AI intelligent analysis technology to achieve all-round monitoring of the fireworks and firecrackers warehouse; demarcates the area in preset areas, equipment and channels, and is equipped with a fireworks recognition algorithm to perform real-time detection and analysis of the monitoring video. Once flames or smoke are detected, the system will automatically trigger an alarm; at the same time, real-time detection and analysis of video images are performed. Once someone smokes in the factory, it can be immediately captured and an alarm can be issued to stop them. Voice linkage can also be performed to conduct real-time voice alarms with the scene; the risk monitoring and early warning subsystem uses face recognition technology to authenticate and register employees entering the fireworks and firecrackers factory; at the same time, unauthorized personnel are warned and alarmed to reduce the entry of illegal personnel, and the behavior of employees can be monitored for abnormal behavior analysis; no-entry areas are set around the factory and at each entrance and exit. Once someone enters the restricted area, an alarm will be immediately issued to drive them away, and the intruder image will be automatically saved to retain evidence for later tracing.

[0014] As a further solution of the present invention: the specific process of the abnormal behavior analysis is: by collecting and analyzing monitoring video data, combining artificial intelligence technology, an abnormal behavior detection model is established; and then the abnormal behavior detection model is used to detect whether the employee's current behavior shows that he or she has left the work post without authorization or fails to comply with any of the factory rules and regulations. If so, an alarm is issued and relevant personnel are notified in a timely manner to discover potential safety risks and illegal behaviors, and take timely measures to deal with them.

[0015] As a further solution of the present invention: the specific process of the risk monitoring and early warning subsystem for analyzing whether an abnormality occurs in environmental parameters is:

[0016] Obtain production environment monitoring data, i.e. environmental parameters, for each production area;

[0017] Calculate and analyze the risk coefficient of production environment monitoring data to determine whether there is a production risk area at the current moment;

[0018] Extract the abnormal types of production risk areas, analyze the corresponding production risk areas of environmental abnormal types, and obtain the optimal control solution under multiple environmental parameters by introducing intelligent algorithms and adaptive control technology;

[0019] Based on the optimal control solution, environmental parameters of environmental conditioning equipment located in the corresponding production risk area are adjusted;

[0020] The alarm device located in the corresponding production risk area is controlled to issue a risk alarm until the risk degree coefficient is less than the risk degree threshold, then the environmental parameter adjustment and risk alarm are stopped.

[0021] As a further solution of the present invention: the risk degree coefficient involves the weighted sum calculation of multiple environmental parameters, the environmental parameters include temperature, humidity and smoke concentration parameters, each environmental parameter corresponds to a risk warning factor, when calculating and analyzing the risk degree coefficient, the predicted value of each risk warning factor is converted into a risk level evaluation of the fireworks and firecrackers site, in order to comprehensively consider the contribution of all risk warning factors to the risk level, first determine the danger index C of each risk warning factor i , the calculation formula is as follows:

[0022]

[0023] Among them, y is the predicted value of the risk warning factor; m is the lower limit warning value set by the system; n is the upper limit warning value set by the system;

[0024] According to the preset rules, the risk level of a single risk warning factor is divided into four levels: I (high), II (medium), III (low), and IV (low), and each level corresponds to a threshold interval;

[0025] Determine C based on the company's historical warning index value and the preset risk acceptability. i The threshold value and the corresponding risk score D i ∈{d1,d2,d3,d4};

[0026] Comprehensive risk index C of each risk warning factor in the production area i And the corresponding risk score D i , calculate the risk score D of the overall environment of the production area;

[0027] According to the threshold range of the hazard score D, the risk level R of the fireworks and firecrackers enterprise is judged. If the risk level R is level I or level II, it means that the production area is a production risk area.

[0028] As a further solution of the present invention: the threshold interval is specifically:

[0029] If C i ≥l3, then C i The corresponding risk score D i =d1, the corresponding risk level is Level I;

[0030] If l2≤C i <l3, then C i The corresponding risk score D i =d2, the corresponding risk level is II;

[0031] If l1≤C i <l2, then C i The corresponding risk score D i =d3, the corresponding risk level is III;

[0032] If C i <l1, then C i The corresponding risk score D i =d4, the corresponding risk level is IV;

[0033] Among them, l1, l2, l3, and l4 are preset risk indicators, and d1, d2, d3, and d4 are preset risk scores.

[0034] As a further solution of the present invention: the risk score D is composed of the sub-factor risk score D i After comparing each sub-factor pairwise, the judgment matrix is ​​constructed using the 1-9 scaling method, and the weight w is calculated using the eigenvalue method. i , the risk score D can be calculated using the following formula:

[0035]

[0036] Among them, wi The weight of each risk factor determined by the system intelligent analysis.

[0037] As a further solution of the present invention: the specific process of the meteorological disaster warning subsystem analyzing the meteorological disaster warning data is as follows:

[0038] Step S1: extracting the scale and type of the meteorological disaster and the estimated arrival time point T1 of the meteorological disaster from the accessed meteorological disaster warning data;

[0039] Step S2: based on the scale and type of the extracted meteorological disaster, obtain the maximum advance response preparation time used in the past to respond to meteorological disasters of the same scale and type and mark it as t;

[0040] Step S3: Mark the current time point as T2. If (T1-T2)>t, continue to monitor the meteorological disaster warning data and return to step S1. If (T1-T2)≤t, push the warning information to the enterprise.

[0041] As a further solution of the present invention: when the drug dosage collection and monitoring subsystem detects the situation of excessive storage and issues an early warning, a corresponding personnel dispersal area is planned according to the current excessive information, specifically:

[0042] The preset drug dosage is marked as a, and the current real-time excess drug dosage is marked as A;

[0043] If A ≥ 3a, the planned personnel dispersal area is within a radius of 2 kilometers from the warehouse;

[0044] If 2a≤A<3a, the planned personnel dispersal area is within a radius of one kilometer from the warehouse;

[0045] If a≤A<2a, the planned personnel dispersal area is within a radius of 500 meters from the warehouse;

[0046] If A<a, the planned personnel dispersal area is within a radius of 200 meters centered on the warehouse.

[0047] As a further solution of the present invention: after analyzing the actual number of people in the warehouse currently exceeding the limit, the overcrowding monitoring and early warning subsystem notifies the personnel in the warehouse to evacuate in an orderly manner according to a preset priority list, specifically:

[0048] Mark the personnel in the current warehouse as Bi, i=1...k, where k is a positive integer, and then mark the stay time of personnel Bi in the warehouse as Gi;

[0049] Mark the straight-line distance from the person to the exit in the warehouse as Qi;

[0050] Calculate the priority weight value S of the evacuation of personnel Bi = 60%*(Gi / g)+40%*(q / Qi), where g is the preset stay time and q is the preset distance;

[0051] Sort the priority weight values ​​S of all personnel Bi from large to small to obtain a priority list;

[0052] Get the number of excess personnel X and send evacuation notices to the first X personnel in the priority list.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present application can comprehensively monitor various hidden dangers in the production process of fireworks and firecrackers, and issue early warnings in a timely manner after discovering abnormalities, fully meeting the needs of modern safety management. Among them, the present application calculates and analyzes the risk degree coefficient for the environmental parameters of each production area, determines whether there is a production risk area at the current moment, and obtains the optimal control solution under multiple environmental parameters by introducing intelligent algorithms and adaptive control technologies to adjust the environmental parameters of the environmental adjustment equipment located in the corresponding production risk area.

[0055] 2. Since weather forecasts have certain errors, in order to avoid false alarms, the meteorological disaster warning subsystem of this application monitors the dynamics of meteorological disasters in real time under the premise of sufficient prevention and preparation time, and then makes adaptive adjustments, which has higher applicability.

[0056] 3. In order to avoid casualties caused by the explosion of excessively stored fireworks and firecrackers, this application plans personnel dispersal areas of different sizes based on the current excessive amount of stored fireworks and firecrackers. While improving safety, it reduces the workload of personnel dispersal as much as possible for ease of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a structural diagram of a fireworks and firecrackers safety production risk monitoring and early warning system based on the Internet of Things;

[0058] Figure 2 This is a schematic diagram of the threshold range of a fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] As mentioned in the background technology of this application, research has found that existing security monitoring methods based on the Internet of Things often have problems such as incomplete monitoring and untimely early warning, which are difficult to meet the needs of modern security management and have certain defects.

[0061] In order to solve the above-mentioned defects, the present application discloses a fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things, which can comprehensively monitor various hidden dangers in the fireworks and firecrackers production process, and issue early warnings in time after discovering abnormalities, fully meeting the needs of modern safety management.

[0062] The following will describe in detail how the solution of the present application solves the above technical problems in conjunction with the accompanying drawings.

[0063] See also Figure 1In an embodiment of the present invention, a fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things includes a comprehensive information supervision subsystem, a risk monitoring and early warning subsystem, a meteorological disaster early warning subsystem, a drug quantity collection and monitoring subsystem, an overcrowding monitoring and early warning subsystem, and an intelligent analysis and display subsystem; the comprehensive information supervision subsystem provides management functions including basic enterprise information, warehouse information, information of the main person in charge, equipment and facility information, high-definition location map information, fireworks and firecrackers experts, and surrounding emergency resources, providing data support for remote supervision of fireworks and firecrackers storage enterprises and emergency disposal in the event of emergencies; the risk monitoring and early warning subsystem collects and accesses the enterprise's existing on-site real-time monitoring video, environmental parameters, smoke alarms, and real-time monitoring and alarm data of perimeter intrusions, analyzes whether anomalies occur, and provides early warning functions when anomalies occur, while providing remote video inspections, video patrols, and historical video review functions; the meteorological disaster early warning subsystem connects to the meteorological department's meteorological disaster early warning data and analyzes it to prevent heavy snow and thunder. In case of disasters caused by bad weather, early warning information can be automatically pushed to enterprises before the bad weather arrives, reminding enterprises to take precautions; the drug quantity collection and monitoring subsystem is used to collect the in-and-out information of fireworks and firecrackers in enterprises in real time, set the alarm threshold through the background, and compare the real-time data with the alarm threshold in real time in the background, and issue an early warning once overstorage occurs; the overcrowding monitoring and early warning subsystem adds intelligent recognition cameras to the front and back doors of the enterprise warehouse, and uses the AI ​​intelligent analysis function to analyze and calculate the number of people entering and leaving the warehouse in the same time period in real time, so as to determine whether the actual number of people in the warehouse is overcrowded, and issue an early warning once overcrowding occurs; the intelligent analysis and display subsystem uses the display mode combined with EGIS maps and big data analysis charts to display fireworks and firecracker storage enterprises, warehouses of various types / levels, surrounding emergency resources, real-time monitoring videos, existing drug capacity of each enterprise, overcrowding / overquantity early warning data, environmental alarm data, intrusion alarm data and meteorological data based on large models. This application can comprehensively monitor various hidden dangers in the production process of fireworks and firecrackers, and issue early warnings in time after abnormalities are found, fully meeting the needs of modern safety management. It should be noted that the EGIS map is the output of the Environmental Geographic Information System (EGIS), which combines GIS technology, remote sensing technology and information technology to comprehensively process and analyze environmental data and ultimately present environmental information in the form of a map.

[0064] In this embodiment, the risk monitoring and early warning subsystem combines the collected real-time monitoring video with AI intelligent analysis technology to achieve all-round monitoring of the fireworks warehouse; the preset areas, equipment and channels are demarcated, and equipped with fireworks recognition algorithms to perform real-time detection and analysis of the monitoring video. Once flames or smoke are detected, the system will automatically trigger an alarm; at the same time, real-time detection and analysis of video images are performed. Once someone smokes in the factory area, it can be immediately captured and an alarm can be issued to stop them. Voice linkage can also be performed to conduct real-time voice alarms with the scene; the risk monitoring and early warning subsystem uses face recognition technology to authenticate and register employees entering the fireworks factory; at the same time, unauthorized personnel are warned and alarmed to reduce illegal entry, and the behavior of employees can be monitored for abnormal behavior analysis; no-entry areas are set around the factory area and at each entrance and exit. Once someone enters the restricted area, an alarm will be issued immediately to drive away the warning, and the intruder image will be automatically saved to retain evidence for later tracing. This setting can accurately identify various dangerous hidden dangers of fireworks enterprises through video monitoring, and timely discover and stop them.

[0065] In this embodiment, the specific process of abnormal behavior analysis is: by collecting and analyzing monitoring video data, combined with artificial intelligence technology, an abnormal behavior detection model is established; then the abnormal behavior detection model is used to detect whether the employee's current behavior shows that he or she has left the work post without authorization or does not comply with any of the factory rules and regulations. If so, an alarm is issued and relevant personnel are notified in a timely manner to discover potential safety risks and illegal behaviors, and take timely measures to deal with them.

[0066] In this embodiment, the specific process of the risk monitoring and early warning subsystem for analyzing whether an abnormality occurs in the environmental parameters is as follows: obtaining the production environment monitoring data of each production area, that is, the environmental parameters; calculating and analyzing the risk degree coefficient of the production environment monitoring data to determine whether there is a production risk area at the current moment; extracting the abnormal type of the production risk area, analyzing the corresponding production risk area of ​​the environmental abnormal type, and obtaining the optimal control solution under multiple environmental parameters by introducing intelligent algorithms and adaptive control technology; based on the optimal control solution, controlling the environmental adjustment equipment located in the corresponding production risk area to adjust the environmental parameters; controlling the alarm device located in the corresponding production risk area to issue a risk alarm until the risk degree coefficient is less than the risk degree threshold, then stopping the environmental parameter adjustment and risk alarm. This setting can quickly determine whether there are risks in each production area within the enterprise, and then timely discover and warn. It should be noted that intelligent algorithms refer to algorithms that use computer technology to analyze, process and make decisions on data by simulating human intelligent behavior. These algorithms can learn from a large amount of data and optimize their own performance to achieve specific goals. The core of intelligent algorithms lies in their learning ability and adaptability, which enables them to continuously improve in a dynamic environment. Adaptive control is a method that automatically adjusts control parameters according to system status or environmental changes to improve system performance. The core idea is to enable the control system to automatically adjust its control strategy or parameters according to the dynamic changes of the controlled object or environment to achieve better control effect.

[0067] In this embodiment, the risk degree coefficient involves the weighted sum calculation of multiple environmental parameters, including temperature, humidity and smoke concentration parameters. Each environmental parameter corresponds to a risk warning factor. When calculating and analyzing the risk degree coefficient, the predicted value of each risk warning factor is converted into a risk level evaluation of the fireworks and firecrackers site. In order to comprehensively consider the contribution of all risk warning factors to the risk level, the hazard index C of each risk warning factor is first determined. i , the calculation formula is as follows:

[0068]

[0069] Among them, y is the predicted value of the risk warning factor; m is the lower limit warning value set by the system; n is the upper limit warning value set by the system;

[0070] According to the preset rules, the risk level of a single risk warning factor is divided into four levels: I (high), II (medium), III (low), and IV (low), and each level corresponds to a threshold interval;

[0071] Determine C based on the company's historical warning index value and the preset risk acceptability. i The threshold value and the corresponding risk score D i ∈{d1,d2,d3,d4};

[0072] Comprehensive risk index C of each risk warning factor in the production area i And the corresponding risk score D i , calculate the risk score D of the overall environment of the production area;

[0073] According to the threshold range of the hazard score D, the risk level R of the fireworks and firecrackers enterprise is determined. If the risk level R is level I or II, it means that the production area is a production risk area. This setting can comprehensively determine whether the production area is a production risk area from multiple angles based on multiple environmental parameters.

[0074] In this embodiment, if Figure 2 As shown, the threshold interval is specifically: if C i ≥l3, then C i The corresponding risk score D i =d1, the corresponding risk level is level I; if l2≤C i <l3, then C i The corresponding risk score D i =d2, the corresponding risk level is II; if l1≤C i <l2, then C i The corresponding risk score D i =d3, the corresponding risk level is III; if C i <l1, then C i The corresponding risk score D i =d4, the corresponding risk level is Level IV; among them, l1, l2, l3, l4 are all preset risk indicators, and d1, d2, d3, d4 are all preset risk scores.

[0075] In this embodiment, the risk score D is composed of the sub-factor risk score D i After comparing each sub-factor pairwise, the judgment matrix is ​​constructed using the 1-9 scaling method, and the weight w is calculated using the eigenvalue method. i , the risk score D can be calculated using the following formula:

[0076]

[0077] Among them, w iis the weight of each risk factor determined by the intelligent analysis of the system. It should be noted that the 1-9 scaling method to construct the judgment matrix is ​​an effective solution to the multi-attribute decision-making problem. It can convert subjective judgments into specific values, thereby realizing the quantitative analysis of each attribute. More specifically, the 1-9 scaling method, also known as the nine-level scaling method, is a method for quantitatively evaluating the importance difference between two factors. In this method, 1 means that the two factors are equally important, 3 means that one factor is slightly more important than the other, 5 means that one factor is obviously more important than the other, 7 means that one factor is more strongly important than the other, and 9 means that one factor is absolutely more important than the other. 2, 4, 6, and 8 represent the intermediate values ​​of the above two adjacent judgments. The judgment matrix is ​​the core component of the nine-level scaling method, which is used to express the evaluator's preference for each attribute of the evaluation object. It is a square matrix whose elements represent the relative importance scores between the factors.

[0078] In this embodiment, the specific process of the meteorological disaster warning subsystem analyzing the meteorological disaster warning data is as follows: Step S1: extracting the scale and type of the meteorological disaster and the estimated arrival time point T1 of the meteorological disaster from the accessed meteorological disaster warning data; Step S2: based on the scale and type of the extracted meteorological disaster, obtaining the maximum advance response preparation time used in the past to deal with meteorological disasters of the same scale and type and marking it as t; Step S3: marking the current time point as T2, if (T1-T2)>t, continue to monitor the meteorological disaster warning data and return to step S1, if (T1-T2)≤t, push warning information to the enterprise. Since weather forecasts have certain errors, in order to avoid false alarms, this application monitors the dynamics of meteorological disasters in real time under the premise of sufficient preparation time, and then makes adaptive adjustments, which has higher applicability.

[0079] In this embodiment, when the drug quantity collection and monitoring subsystem detects the situation of excessive storage and issues an early warning, the corresponding personnel dispersal area is planned according to the current excess information, specifically: the preset drug quantity is marked as a, and the current real-time excess drug quantity is marked as A; if A≥3a, the planned personnel dispersal area is within a radius of two kilometers with the warehouse as the center; if 2a≤A<3a, the planned personnel dispersal area is within a radius of one kilometer with the warehouse as the center; if a≤A<2a, the planned personnel dispersal area is within a radius of five hundred meters with the warehouse as the center; if A<a, the planned personnel dispersal area is within a radius of two hundred meters with the warehouse as the center. In order to avoid casualties caused by the explosion of excessively stored fireworks and firecrackers, this application plans personnel dispersal areas of different sizes based on the currently stored excessive amount of fireworks and firecrackers, while improving safety, reducing the workload of personnel dispersal as much as possible, and facilitating use.

[0080] In this embodiment, after analyzing the actual number of people in the warehouse, the overcrowding monitoring and early warning subsystem notifies the personnel in the warehouse to evacuate in an orderly manner according to the preset priority list. Specifically, the personnel in the current warehouse are marked as Bi, i=1···k, where k is a positive integer, and then the residence time of personnel Bi in the warehouse is marked as Gi; the straight-line distance of personnel Bi from the warehouse to the exit is marked as Qi; the priority weight value S of personnel Bi's withdrawal is calculated as S=60%*(Gi / g)+40%*(q / Qi), where g is the preset residence time and q is the preset distance; the priority weight values ​​S of all personnel Bi are sorted from large to small to obtain a priority list; the number of overcrowding X is obtained, and an evacuation notice is issued to the personnel corresponding to the first X in the priority list. A large number of fireworks and firecrackers products are stored in the fireworks and firecrackers warehouse. The chemical substances in these products may volatilize or leak during storage, resulting in the presence of harmful substances in the air in the warehouse. The human body may experience the following adverse reactions if it is in such an environment for a long time. Therefore, when evacuating personnel, priority is given to those who have stayed in the warehouse for a long time. In addition, in order to improve the efficiency of personnel evacuation, this application also comprehensively considers the position of personnel in the warehouse. The closer to the warehouse exit, the more suitable it is to evacuate first. Therefore, this application comprehensively calculates the priority weight value of each employee based on the above two parameters.

[0081] The present invention can comprehensively monitor various hidden dangers in the production process of fireworks and firecrackers, and issue early warnings in time after discovering abnormalities, fully meeting the needs of modern safety management. Among them, the present application calculates and analyzes the risk degree coefficient for the environmental parameters of each production area, determines whether there is a production risk area at the current moment, and obtains the optimal control solution under multiple environmental parameters by introducing intelligent algorithms and adaptive control technologies to adjust the environmental parameters of the environmental adjustment equipment located in the corresponding production risk area. Since weather forecasts have certain errors, in order to avoid false alarms, the meteorological disaster early warning subsystem of the present application monitors the dynamics of meteorological disasters in real time under the premise of sufficient prevention and preparation time, and then makes adaptive adjustments, which has higher applicability. In order to avoid the explosion of excessively stored fireworks and firecrackers causing casualties, the present application plans personnel dispersal areas of different sizes based on the currently stored excessive amount of fireworks and firecrackers, while improving safety, reducing the workload of personnel dispersal as much as possible, and facilitating use.

[0082] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0083] What is described above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things, characterized in that: It includes comprehensive information supervision subsystem, risk monitoring and early warning subsystem, meteorological disaster early warning subsystem, drug quantity collection and monitoring subsystem, overcrowding monitoring and early warning subsystem and intelligent analysis and display subsystem; The comprehensive information supervision subsystem provides management functions including basic enterprise information, warehouse information, information of main responsible persons, equipment and facility information, high-definition location map information, fireworks and firecrackers experts, and surrounding emergency resources, providing data support for remote supervision of fireworks and firecrackers storage enterprises and emergency response in the event of emergencies; The risk monitoring and early warning subsystem collects and accesses the company's existing on-site real-time monitoring video, environmental parameters, smoke alarms, and real-time monitoring and alarm data of perimeter intrusions, analyzes whether there are any abnormalities, and provides early warning functions when abnormalities occur. It also provides remote video inspection, video patrol, and historical video review functions; The meteorological disaster warning subsystem is connected to the meteorological department's meteorological disaster warning data and analyzes it. In order to prevent disasters caused by severe weather such as heavy snow and thunderstorms, it can automatically push warning information to enterprises before severe weather arrives to remind them to take precautions. The drug quantity collection and monitoring subsystem is used to collect the in-and-out information of fireworks and firecrackers in real time, set the alarm threshold through the background, and compare the real-time data with the alarm threshold in real time in the background, and issue an early warning in case of excessive storage; The overcrowding monitoring and early warning subsystem adds intelligent recognition cameras to the front and rear doors of the enterprise warehouse, and uses the AI ​​intelligent analysis function to perform real-time analysis and calculation of the number of people entering and leaving the warehouse in the same period of time, so as to determine whether the actual number of people in the warehouse is overcrowded, and issue an early warning if overcrowding occurs; The intelligent analysis and display subsystem uses a display mode that combines EGIS maps and big data analysis charts to display fireworks and firecracker storage companies, warehouses of various types / levels, surrounding emergency resources, real-time monitoring videos, each company's existing drug capacity, overcrowding / overquantity warning data, environmental alarm data, intrusion alarm data and meteorological data based on a large model.

2. According to the Internet of Things-based fireworks and firecrackers production safety risk monitoring and early warning system according to claim 1, it is characterized in that: The risk monitoring and early warning subsystem combines the collected real-time monitoring video on site with AI intelligent analysis technology to achieve all-round monitoring of the fireworks and firecrackers warehouse; it demarcates the area in preset areas, equipment and channels, and is equipped with a fireworks recognition algorithm to perform real-time detection and analysis of the monitoring video. Once flames or smoke are detected, the system will automatically trigger an alarm; at the same time, it performs real-time detection and analysis of video images. Once someone smokes in the factory, it can immediately capture and issue an alarm to stop them. It can also perform voice linkage and provide real-time voice alarms with the scene; the risk monitoring and early warning subsystem uses face recognition technology to authenticate and register employees entering the fireworks and firecrackers factory; at the same time, it warns and alarms unauthorized personnel to reduce illegal entry, and can monitor the behavior of employees for abnormal behavior analysis; set up prohibited intrusion areas around the factory and at each entrance and exit. Once someone enters the restricted area, an alarm will be issued immediately to drive them away, and the intruder image will be automatically saved to retain evidence for later tracing.

3. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 2 is characterized in that: The specific process of the abnormal behavior analysis is: by collecting and analyzing monitoring video data, combined with artificial intelligence technology, an abnormal behavior detection model is established; then the abnormal behavior detection model is used to detect whether the employee's current behavior shows that he or she has left the work post without authorization or violated any of the factory rules and regulations. If so, an alarm is issued and relevant personnel are notified in a timely manner to discover potential safety risks and illegal behaviors, and take timely measures to deal with them.

4. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 3 is characterized in that: The specific process of the risk monitoring and early warning subsystem to analyze whether there is an abnormality in environmental parameters is as follows: Obtain production environment monitoring data, i.e. environmental parameters, for each production area; Calculate and analyze the risk coefficient of production environment monitoring data to determine whether there is a production risk area at the current moment; Extract the abnormal types of production risk areas, analyze the corresponding production risk areas of environmental abnormal types, and obtain the optimal control solution under multiple environmental parameters by introducing intelligent algorithms and adaptive control technology; Based on the optimal control solution, environmental parameters of environmental conditioning equipment located in the corresponding production risk area are adjusted; The alarm device located in the corresponding production risk area is controlled to issue a risk alarm until the risk degree coefficient is less than the risk degree threshold, then the environmental parameter adjustment and risk alarm are stopped.

5. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 4 is characterized in that: The risk degree coefficient involves the weighted and calculated results of multiple environmental parameters, including temperature, humidity and smoke concentration parameters. Each environmental parameter corresponds to a risk warning factor. When calculating and analyzing the risk degree coefficient, the predicted value of each risk warning factor is converted into a risk level evaluation of the fireworks and firecrackers site. In order to comprehensively consider the contribution of all risk warning factors to the risk level, the hazard index C of each risk warning factor is first determined. i , the calculation formula is as follows: Among them, y is the predicted value of the risk warning factor; m is the lower limit warning value set by the system; n is the upper limit warning value set by the system; According to the preset rules, the risk level of a single risk warning factor is divided into four levels: I, II, III, and IV, and each level corresponds to a threshold interval; Determine C based on the company's historical warning index value and the preset risk acceptability. i The threshold value and the corresponding risk score D i ∈{d1,d2,d3,d4}; Comprehensive risk index C of each risk warning factor in the production area i And the corresponding risk score D i , calculate the risk score D of the overall environment of the production area; According to the threshold range of the hazard score D, the risk level R of the fireworks and firecrackers enterprise is judged. If the risk level R is level I or level II, it means that the production area is a production risk area.

6. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 5 is characterized in that: The threshold interval is specifically: If C i ≥l3, then C i The corresponding risk score D i =d1, the corresponding risk level is Level I; If l2≤C i <l3, then C i The corresponding risk score D i =d2, the corresponding risk level is II; If l1≤C i <l2, then C i The corresponding risk score D i =d3, the corresponding risk level is III; If C i <l1, then C i The corresponding risk score D i =d4, the corresponding risk level is IV; Among them, l1, l2, l3, and l4 are preset risk indicators, and d1, d2, d3, and d4 are preset risk scores.

7. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 6 is characterized in that: The risk score D is composed of the sub-factor risk score D i After comparing each sub-factor pairwise, the judgment matrix is ​​constructed using the 1-9 scaling method, and the weight w is calculated using the eigenvalue method. i , the risk score D can be calculated using the following formula: Among them, w i The weight of each risk factor determined by the system intelligent analysis.

8. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 7 is characterized in that: The specific process of the meteorological disaster warning subsystem analyzing the meteorological disaster warning data is as follows: Step S1: extracting the scale and type of the meteorological disaster and the estimated arrival time point T1 of the meteorological disaster from the accessed meteorological disaster warning data; Step S2: based on the scale and type of the extracted meteorological disaster, obtain the maximum advance response preparation time used in the past to respond to meteorological disasters of the same scale and type and mark it as t; Step S3: Mark the current time point as T2. If (T1-T2)>t, continue to monitor the meteorological disaster warning data and return to step S1. If (T1-T2)≤t, push the warning information to the enterprise.

9. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 8 is characterized in that: When the drug quantity collection and monitoring subsystem detects excessive storage and issues an early warning, it plans the corresponding personnel dispersal area according to the current excessive information, specifically: The preset drug dosage is marked as a, and the current real-time excess drug dosage is marked as A; If A ≥ 3a, the planned personnel dispersal area is within a radius of 2 kilometers from the warehouse; If 2a≤A<3a, the planned personnel dispersal area is within a radius of one kilometer from the warehouse; If a≤A<2a, the planned personnel dispersal area is within a radius of 500 meters from the warehouse; If A<a, the planned personnel dispersal area is within a radius of 200 meters centered on the warehouse.

10. The fireworks and firecrackers production safety risk monitoring and early warning system based on the Internet of Things according to claim 9, characterized in that: After analyzing the actual number of people in the warehouse, the overcrowding monitoring and early warning subsystem notifies the personnel in the warehouse to evacuate in an orderly manner according to the preset priority list, specifically: Mark the personnel in the current warehouse as Bi, i=1...k, where k is a positive integer, and then mark the stay time of personnel Bi in the warehouse as Gi; Mark the straight-line distance from the person to the exit in the warehouse as Qi; Calculate the priority weight value S of the evacuation of personnel Bi = 60%*(Gi / g)+40%*(q / Qi), where g is the preset stay time and q is the preset distance; Sort the priority weight values ​​S of all personnel Bi from large to small to obtain a priority list; Get the number of excess personnel X and send evacuation notices to the first X personnel in the priority list.

Images