Hazardous chemical substance storage risk artificial intelligence identification method, equipment and medium

Abstract

The invention discloses a hazardous chemical substance storage risk artificial intelligence identification method and device and a medium, and relates to the technical field of hazardous chemical substance management. The method comprises the following steps: acquiring product information, operation time and access frequency of hazardous chemicals, and respectively acquiring three-dimensional images of a warehouse and a preset distance outside the warehouse; stacking the hazardous chemical substances according to the product information, the operation time and the access frequency to obtain a stack of the hazardous chemical substances, and obtaining a three-dimensional image of the stack; environment data of a warehouse and a preset distance outside the warehouse are collected, three-dimensional modeling is carried out according to the three-dimensional image, product information is integrated, and a digital twinborn model of hazardous chemical substance storage is obtained to reflect dynamic changes of the warehouse environment; and according to the dynamic change, identifying whether the stacking height of the hazardous chemical substances, the adjacent stacking distance and the environmental data exceed preset thresholds or not. According to the method, artificial intelligence, three-dimensional modeling and digital twinning are comprehensively applied, and intelligent identification and management of hazardous chemical substance storage risks are realized.

Description

Technical Field

[0001] The present application relates to the technical field of hazardous chemicals management, and in particular to an artificial intelligence identification method, device and medium for hazardous chemicals storage risk. Background Art

[0002] Hazardous chemicals refer to highly toxic chemicals and other chemicals that have properties such as toxicity, corrosion, explosion, combustion, and combustion-supporting properties, and are harmful to the human body, facilities, and the environment.

[0003] Dangerous chemicals pose extremely high safety risks during storage, including fire, explosion, leakage, poisoning and other possible accident types. Traditional manual monitoring methods are limited by human energy, experience and reaction speed, and it is difficult to monitor and effectively prevent risks in a comprehensive and real-time manner. Therefore, it is particularly important to develop a system that can automatically and accurately identify hazardous chemical storage risks.

[0004] Through the above analysis, the problems and defects of the prior art are as follows:

[0005] The existing technology cannot perform integrated risk identification of hazardous chemicals during the storage process from the beginning of storage, making it difficult to comprehensively and real-time monitor and effectively prevent risks. Summary of the invention

[0006] The embodiments of the present application provide a method, a device and a medium that can solve the problem in the prior art that during the storage process of hazardous chemicals, integrated risk identification cannot be performed from the beginning of storage, and it is difficult to comprehensively and real-time monitor and effectively prevent risks.

[0007] In the first aspect, an embodiment of the present application provides an artificial intelligence identification method for hazardous chemicals storage risks, the method comprising: obtaining product information, operation time and access frequency of hazardous chemicals, and respectively obtaining three-dimensional images of the warehouse and a preset distance outside the warehouse; stacking hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of hazardous chemicals, and obtaining a three-dimensional image of the stack; collecting environmental data at a preset distance between the warehouse and the outside of the warehouse, performing three-dimensional modeling based on the three-dimensional image, and integrating product information to obtain a digital twin model of the hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; according to the dynamic changes, identifying the stacking height of hazardous chemicals, the adjacent distance of the stack, and whether the environmental data exceeds a preset threshold.

[0008] In one implementation of the present application, before obtaining the product information, operation time and access frequency of hazardous chemicals, the method also includes: deploying terminal detection equipment within a preset distance outside the warehouse, the terminal detection equipment including sensors, sound recognition equipment and monitoring equipment, and deploying edge computing equipment at the storage site, wherein the sensors include temperature sensors, humidity sensors, and gas concentration sensors; obtaining product information of hazardous chemicals, and establishing a hazardous chemical product information database, wherein the product information includes chemical properties, storage conditions and operating procedures.

[0009] In one implementation of the present application, after stacking hazardous chemicals according to product information, operation time and access frequency to obtain a stack of hazardous chemicals and a three-dimensional image of the stack, the method also includes: deploying terminal detection equipment in the warehouse and the stack, and connecting the terminal detection equipment wirelessly.

[0010] In one implementation of the present application, after integrating the product information of hazardous chemicals, the method also includes: setting the stacking height and adjacent distance of hazardous chemicals according to chemical properties, storage conditions, and operating procedures, as well as whether the chemical properties of adjacent hazardous chemicals are compatible and the safety thresholds corresponding to environmental parameters; when any parameter in the environmental parameters exceeds a preset threshold, a warning signal is triggered and a corresponding environmental control strategy is executed, the control strategy including adjusting the temperature and humidity control system in the warehouse and starting ventilation equipment.

[0011] In one implementation of the present application, environmental data of the warehouse and a preset distance outside the warehouse are collected, specifically including: using sensors and infrared thermal imaging to monitor the temperature, gas and combustibles at a preset distance outside the warehouse; when the temperature or gas exceeds the corresponding preset threshold, or combustibles are found, issuing a warning to the staff; collecting and saving environmental data to obtain historical environmental data.

[0012] In one implementation of the present application, after identifying the stacking height of hazardous chemicals, the adjacent distance of stacks, and whether the environmental data exceeds a preset threshold based on dynamic changes, the method also includes: providing a visualization interface for displaying a three-dimensional image of the stack, environmental data, and risk identification results; and developing a mobile application to enable staff to monitor remotely.

[0013] In one implementation of the present application, the method also includes: performing real-time calculations on environmental data through edge computing devices; performing time series analysis on historical environmental data to obtain the gas release patterns of hazardous chemicals and predict environmental data within a preset time in the future; and using optimization algorithms to analyze the chemical properties, storage conditions and operating procedures of hazardous chemicals to optimize storage layout.

[0014] In one implementation of the present application, the method further includes updating the environmental data and three-dimensional images at a preset frequency when the staff does not actively collect the data; and verifying the identity of the staff when the staff collects the data.

[0015] In a second aspect, an embodiment of the present application also provides an artificial intelligence identification device for hazardous chemicals storage risks, the device comprising at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: obtain product information, operation time, and access frequency of hazardous chemicals, and respectively obtain three-dimensional images of the warehouse and a preset distance outside the warehouse; stack hazardous chemicals according to the product information, operation time, and access frequency to obtain a stack of hazardous chemicals, and obtain a three-dimensional image of the stack; collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate product information to obtain a digital twin model of the hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; based on dynamic changes, identify the stacking height of hazardous chemicals, the adjacent distance of the stacks, and whether the environmental data exceeds a preset threshold.

[0016] On the third aspect, the embodiment of the present application also provides a non-volatile computer storage medium for identifying artificial intelligence risks of hazardous chemicals storage, which stores computer executable instructions, and the computer executable instructions are set to: obtain product information, operation time and access frequency of hazardous chemicals, and obtain three-dimensional images of the warehouse and a preset distance outside the warehouse respectively; stack hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of hazardous chemicals, and obtain a three-dimensional image of the stack; collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate product information to obtain a digital twin model of hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; according to the dynamic changes, identify the stacking height of hazardous chemicals, the adjacent distance of the stack, and whether the environmental data exceeds a preset threshold.

[0017] The embodiment of the present application provides an artificial intelligence identification method, device and medium for hazardous chemical storage risk, which can start from the location arrangement, first reasonably arrange the stacking position, stacking height and adjacent distance of the hazardous chemicals, collect the environmental data (such as temperature, humidity, light, gas concentration, etc.) of the preset distance between the warehouse and the outside of the warehouse, and combine the three-dimensional image for three-dimensional modeling to build a digital twin model of hazardous chemical storage. This model can reflect the dynamic changes of the warehouse environment in real time. When the environmental data exceeds the preset threshold, it can trigger an early warning signal in time to remind the management personnel to take corresponding measures to prevent the occurrence of safety accidents; it not only pays attention to the environmental changes inside the warehouse, but also considers the environmental data of the preset distance outside the warehouse, which helps to discover external factors that may affect the safety of the warehouse in advance, such as fires, leaks and other accidents in the adjacent area. The comprehensive use of artificial intelligence, three-dimensional modeling and digital twins and other technical means realizes the intelligent identification and management of hazardous chemical storage risks, effectively improving the optimization degree of storage layout, the real-time and accuracy of environmental monitoring, and the intelligent level and safety of storage management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 A flow chart of an artificial intelligence identification method for hazardous chemicals storage risks provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of the internal structure of an artificial intelligence identification device for hazardous chemicals storage risks provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0022] The embodiments of the present application provide an artificial intelligence identification method, device and medium for hazardous chemicals storage risks, which solves the problem in the prior art that hazardous chemicals cannot be integratedly identified from the beginning of storage during the storage process, making it difficult to comprehensively and real-time monitor and effectively prevent risks.

[0023] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0024] Figure 1 A flowchart of an artificial intelligence identification method for hazardous chemicals storage risk provided in an embodiment of the present application. Figure 1 As shown, an artificial intelligence identification method for hazardous chemicals storage risk provided by an embodiment of the present application specifically includes the following steps:

[0025] Step 10: Obtain product information, operation time, and access frequency of hazardous chemicals, and obtain three-dimensional images of the warehouse and a preset distance outside the warehouse;

[0026] In this step, three-dimensional images of the warehouse and the preset distance outside the warehouse can be obtained through technologies such as high-definition cameras, drone oblique photography, or three-dimensional laser scanners, providing basic data for three-dimensional modeling and digital twins.

[0027] Step 20: stacking hazardous chemicals according to product information, operation time and access frequency, obtaining a stack of hazardous chemicals and a three-dimensional image of the stack;

[0028] Step 30: Collect environmental data of the warehouse and a preset distance outside the warehouse, perform 3D modeling based on the 3D image, and integrate product information to obtain a digital twin model of hazardous chemicals storage to reflect the dynamic changes of the warehouse environment. The environmental data includes temperature, humidity, light, and gas concentration.

[0029] In this step, the digital twin model provides a data interface or API for receiving and processing data from the sensor network.

[0030] As an optional embodiment, collecting environmental data of the warehouse and a preset distance outside the warehouse may specifically include: Step 301: using sensors and infrared thermal imaging to monitor the temperature, gas and combustibles at a preset distance outside the warehouse; Step 302: when the temperature or gas exceeds the corresponding preset threshold, or combustibles are found, issuing a warning prompt to the staff; Step 303: collecting and saving environmental data to obtain historical environmental data.

[0031] In this step, changes in the status outside the warehouse may also affect the warehouse. High temperature weather may cause the temperature inside the warehouse to rise, affecting the stability of hazardous chemicals. The existence of pollution sources outside the warehouse may cause harmful gases, dust and other pollutants to enter the warehouse, causing contamination to hazardous chemicals or triggering chemical reactions.

[0032] Step 40: Based on dynamic changes, identify whether the stacking height of hazardous chemicals, the adjacent distance between stacks, and environmental data exceed preset thresholds.

[0033] As an optional embodiment, before obtaining the product information, operation time and access frequency of hazardous chemicals, the method may also include: Step 01: deploying terminal detection equipment within a preset distance outside the warehouse, the terminal detection equipment including sensors, sound recognition equipment and monitoring equipment, and deploying edge computing equipment at the storage site, wherein the sensors include temperature sensors, humidity sensors, and gas concentration sensors; Step 02: obtaining the product information of hazardous chemicals and establishing a hazardous chemical product information database, wherein the product information includes chemical properties, storage conditions and operating procedures.

[0034] As an optional embodiment, after stacking hazardous chemicals according to product information, operation time and access frequency, obtaining a stack of hazardous chemicals, and obtaining a three-dimensional image of the stack, the method may also include: deploying terminal detection equipment in the warehouse and the stack, and connecting the terminal detection equipment wirelessly.

[0035] In this step, terminal detection equipment is deployed at the entrance, exit, passages, shelves, etc. of the warehouse and around or on the top of the stacks. The terminal detection equipment is regularly maintained and inspected to ensure that it can work normally and transmit data accurately.

[0036] As an optional embodiment, after integrating the product information of hazardous chemicals, the method may also include: setting the stacking height and adjacent distance of hazardous chemicals according to chemical properties, storage conditions, and operating procedures, as well as whether the chemical properties of adjacent hazardous chemicals are compatible and safety thresholds corresponding to environmental parameters; when any parameter in the environmental parameters exceeds a preset threshold, triggering a warning signal and executing a corresponding environmental control strategy, which includes adjusting the temperature and humidity control system in the warehouse and starting ventilation equipment.

[0037] In this step, the temperature and humidity control system in the warehouse is automatically adjusted according to the early warning signal. For example, when the temperature is too high, the refrigeration equipment is started; when the humidity is too high, the dehumidification equipment is started; when the gas concentration in the warehouse exceeds the standard, the ventilation equipment is started to discharge the harmful gas out of the warehouse. Special attention is paid to avoid the accumulation of harmful gases in the warehouse, which may lead to the risk of fire or explosion. When the automatic adjustment system cannot effectively control the environmental parameters, the management personnel should immediately intervene manually and take necessary measures according to the emergency plan, such as evacuating personnel, cutting off power supply, using fire-fighting equipment, etc., to prevent accidents.

[0038] As an optional embodiment, after identifying the stacking height of hazardous chemicals, the adjacent distance of stacks, and whether the environmental data exceeds a preset threshold based on dynamic changes, the method may also include: Step 50: Providing a visualization interface for displaying a three-dimensional image of the stack, environmental data, and risk identification results; Step 60: Developing a mobile application to enable staff to monitor remotely.

[0039] As an optional embodiment, the method may also include: Step 70: Real-time calculation of environmental data through edge computing devices; in this step, edge computing devices are deployed at key locations in the warehouse. These devices should have powerful data processing and computing capabilities, and the environmental data collected by sensors, cameras and other IoT devices: temperature, humidity, gas concentration, etc., are transmitted to the edge computing devices in real time, and pre-processing is immediately performed, such as data cleaning, denoising, etc. Then, the processed data is analyzed in real time to calculate various parameter indicators of the current environment, such as whether it exceeds the safety threshold, etc.; the warehouse edge computing equipment can collect and process warehouse logistics data in real time, thereby improving the response speed of logistics and the accuracy of decision-making.

[0040] Step 80: Perform time series analysis on historical environmental data to obtain the gas release pattern of hazardous chemicals and predict environmental data within a preset time in the future;

[0041] In this step, the time series analysis technology LSTM is used to model and analyze historical data to reveal the laws and trends of hazardous chemical gas release, analyze the correlation between different environmental parameters, and their impact on the storage safety of hazardous chemicals. Based on the analysis results, a prediction model is constructed to predict environmental data within a preset time in the future.

[0042] Step 90: Use optimization algorithms to analyze the chemical properties, storage conditions, and operating procedures of hazardous chemicals to optimize storage layout.

[0043] In this step, historical warehouse data are sorted out, including the stacking location, stacking height, adjacent distance, etc. of hazardous chemicals. According to the specific needs and goals of warehouse management, appropriate optimization algorithms, genetic algorithms, particle swarm algorithms, etc. are selected to build a warehouse layout optimization model. The chemical properties, storage conditions and operating procedures of hazardous chemicals are used as constraints to obtain the optimal warehouse layout plan. The optimized warehouse layout plan is implemented, and the implementation process is continuously monitored and evaluated to ensure the effective implementation and continuous improvement of the plan.

[0044] As an optional embodiment, the method may further include: updating the environmental data and the three-dimensional image at a preset frequency when the staff does not actively collect the data; and verifying the identity of the staff when the staff collects the data.

[0045] In this step, authorized staff can remotely collect current environmental data in real time; they can also continuously feed back the real-time collected data to the digital twin model to update the model status; they can also preset a frequency, such as 30 seconds, which can be achieved through data streaming to ensure that the digital twin model can reflect the real state of the physical world in real time.

[0046] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, this application embodiment also provides an artificial intelligence identification device for hazardous chemicals storage risks, the structure of which is as follows: Figure 2 shown.

[0047] Figure 2 A schematic diagram of the internal structure of an artificial intelligence identification device for hazardous chemicals storage risk provided in an embodiment of the present application. Figure 2 As shown, the device includes:

[0048] at least one processor 201;

[0049] and, a memory 202 communicatively connected to the at least one processor;

[0050] Among them, the memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 201 so that at least one processor 201 can: obtain product information, operation time and access frequency of hazardous chemicals, and obtain three-dimensional images of the warehouse and the preset distance outside the warehouse respectively; stack hazardous chemicals according to the product information, operation time and access frequency to obtain the stack of hazardous chemicals, and obtain a three-dimensional image of the stack; collect environmental data of the warehouse and the preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate product information to obtain a digital twin model of the hazardous chemical storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; according to the dynamic changes, identify the stacking height of hazardous chemicals, the adjacent distance of the stack, and whether the environmental data exceeds the preset threshold.

[0051] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium for artificial intelligence identification of hazardous chemicals storage risks, storing computer executable instructions, wherein the computer executable instructions are configured to: obtain product information, operation time, and access frequency of hazardous chemicals, and respectively obtain three-dimensional images of the warehouse and a preset distance outside the warehouse; stack hazardous chemicals according to the product information, operation time, and access frequency to obtain a stack of hazardous chemicals and a three-dimensional image of the stack; collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate product information to obtain a digital twin model of hazardous chemicals storage to reflect dynamic changes in the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; based on dynamic changes, identify the stacking height of hazardous chemicals, the adjacent distance of stacks, and whether the environmental data exceeds a preset threshold.

[0052] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0053] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0054] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0055] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0056] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0057] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0058] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0059] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0060] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0061] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0062] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for identifying hazardous chemicals storage risks using artificial intelligence, characterized in that: The method comprises: Obtain product information, operation time and access frequency of hazardous chemicals, as well as obtain three-dimensional images of the warehouse and the preset distance outside the warehouse; Stacking the hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of the hazardous chemicals and a three-dimensional image of the stack; Collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate the product information to obtain a digital twin model of the hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; According to the dynamic changes, the stacking height of the hazardous chemicals, the adjacent distance of the stacks, and whether the environmental data exceeds a preset threshold are identified.

2. According to claim 1, a method for identifying hazardous chemicals storage risk using artificial intelligence is characterized in that: Before obtaining product information, operation time, and access frequency of hazardous chemicals, the method further includes: Deploy terminal detection equipment within a preset distance outside the warehouse, the terminal detection equipment includes sensors, sound recognition equipment and monitoring equipment, and deploy edge computing equipment at the storage site, wherein the sensors include temperature sensors, humidity sensors and gas concentration sensors; Obtain product information of the hazardous chemicals and establish a hazardous chemical product information database, wherein the product information includes chemical properties, storage conditions and operating procedures.

3. The method for identifying hazardous chemicals storage risk using artificial intelligence according to claim 1, characterized in that: After stacking the hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of the hazardous chemicals and a three-dimensional image of the stack, the method further includes: Terminal detection equipment is deployed on the warehouse and the stack, and the terminal detection equipment is connected wirelessly.

4. The method for identifying the risk of hazardous chemicals storage by artificial intelligence according to claim 2 is characterized in that: After integrating the product information of hazardous chemicals, the method further includes: According to the chemical properties, storage conditions, and operating procedures, set the stacking height of hazardous chemicals and the adjacent distance between stacks, as well as whether the chemical properties of adjacent hazardous chemicals are compatible and the corresponding safety thresholds of environmental parameters; When any of the environmental parameters exceeds a preset threshold, an early warning signal is triggered and a corresponding environmental control strategy is executed, which includes adjusting the temperature and humidity control system in the warehouse and starting ventilation equipment.

5. The method for identifying the risk of hazardous chemicals storage by artificial intelligence according to claim 2 is characterized in that: The collecting of environmental data of the warehouse and a preset distance outside the warehouse specifically includes: Use sensors and infrared thermal imaging to monitor temperature, gas and combustibles at a preset distance outside the warehouse; When the temperature or gas exceeds the corresponding preset threshold or combustibles are found, an early warning is issued to the staff; Collect and save environmental data to obtain historical environmental data.

6. The method for identifying hazardous chemicals storage risk using artificial intelligence according to claim 1, characterized in that: After identifying the stacking height of the hazardous chemicals, the adjacent distance of the stacks, and whether the environmental data exceeds a preset threshold value according to the dynamic changes, the method further includes: Providing a visualization interface for displaying a three-dimensional image of the stack, environmental data, and risk identification results; Develop mobile applications to enable remote monitoring by staff.

7. The method for identifying hazardous chemicals storage risk using artificial intelligence according to claim 5, characterized in that: The method further comprises: Performing real-time calculation on the environmental data by the edge computing device; Perform time series analysis on the historical environmental data to obtain the gas release pattern of the hazardous chemicals and predict environmental data within a preset time in the future; The optimization algorithm is used to analyze the chemical properties, storage conditions and operating procedures of the hazardous chemicals to optimize the storage layout.

8. The method for identifying hazardous chemicals storage risk using artificial intelligence according to claim 1, characterized in that: The method further comprises: In the case where the staff does not actively collect the data, the environmental data and the three-dimensional image are updated at a preset frequency; When the data is collected by staff, their identity is verified.

9. An artificial intelligence identification device for hazardous chemicals storage risks, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Obtain product information, operation time and access frequency of hazardous chemicals, as well as obtain three-dimensional images of the warehouse and the preset distance outside the warehouse; Stacking the hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of the hazardous chemicals and a three-dimensional image of the stack; Collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate the product information to obtain a digital twin model of the hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; According to the dynamic changes, the stacking height of the hazardous chemicals, the adjacent distance of the stacks, and whether the environmental data exceeds a preset threshold are identified.

10. A non-volatile computer storage medium for artificial intelligence identification of hazardous chemicals storage risks, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Obtain product information, operation time and access frequency of hazardous chemicals, as well as obtain three-dimensional images of the warehouse and the preset distance outside the warehouse; Stacking the hazardous chemicals according to the product information, operation time and access frequency to obtain a stack of the hazardous chemicals and a three-dimensional image of the stack; Collect environmental data of the warehouse and a preset distance outside the warehouse, perform three-dimensional modeling based on the three-dimensional image, and integrate the product information to obtain a digital twin model of the hazardous chemicals storage to reflect the dynamic changes of the warehouse environment, wherein the environmental data includes temperature, humidity, light, and gas concentration; According to the dynamic changes, the stacking height of the hazardous chemicals, the adjacent distance of the stacks, and Whether the environmental data exceeds a preset threshold.

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