Intelligent fire-fighting monitoring system and method based on cloud computing

Abstract

The invention relates to an intelligent fire-fighting monitoring system and method based on cloud computing. The system comprises an infrared thermal imaging module which is used for collecting a current infrared thermal imaging image of at least part of a scene, judging whether an abnormal heating area exists in the current infrared thermal imaging image or not, if yes, sending a preset first identity identification code of the infrared thermal imaging module and temperature abnormity warning information, and if not, sending a preset second identity identification code of the infrared thermal imaging module to the infrared thermal imaging module; the infrared thermal imaging module is also used for switching to a working state of a patrol mode or a staring mode according to the received patrol instruction or staring instruction; the cloud server module is used for receiving the preset first identity identification code and the temperature abnormity alarm information, obtaining position information of an abnormal heating area according to the preset first identity identification code and the alarm information, and outputting the position information; and the low-altitude unmanned fire-fighting module is used for acquiring the position information, flying to a position in a scene corresponding to the position information, acquiring a real-time overlook thermal imaging image and outputting the real-time overlook thermal imaging image to the cloud service module.

Description

Technical Field

[0001] This application relates to the field of intelligent fire protection technology, and particularly to a cloud computing-based intelligent fire protection monitoring system and method. Background Art

[0002] As the first-generation power batteries of new energy vehicles are approaching the battery replacement deadline, how to utilize or properly dispose of a large number of old batteries has become a hot issue in the new energy industry. One existing use is to use old batteries in lithium battery energy storage stations to store electrical energy during off-peak hours for dispatching and use during peak hours.

[0003] Chinese Patent No. CN202616885U discloses a large-capacity lithium battery energy storage station, which includes a container, a battery rack, a battery box, lithium batteries, wire pipes, an integrated electrical cabinet, and a monitoring console. Among them, the battery racks are installed back-to-back on both sides inside the container through self-locking sliding rails, leaving a wire routing area between the two battery racks. The battery boxes are installed on the battery racks through self-locking sliding rails, and the lithium batteries are installed inside the battery boxes. The integrated electrical cabinet is installed on the right side of the battery rack inside the container, and the wire pipes are installed in the wire routing area. One end of the wire pipe is connected to the battery box, and the other end is connected to the integrated electrical cabinet. There is a door on the right side wall of the container, and the monitoring console is installed opposite the door inside the container.

[0004] However, for this type of lithium battery energy storage station, due to the high density of battery laying, if a fire occurs, it will cause devastating losses. Therefore, how to effectively prevent fires has become an urgent problem to be solved. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a cloud computing-based intelligent fire protection monitoring system and method that can reduce the fire incidence rate of lithium battery energy storage stations.

[0006] In a first aspect, this application provides a cloud computing-based intelligent fire protection monitoring system, which includes: An infrared thermal imaging module, configured to collect the current infrared thermal imaging image of at least part of the scene, and determine whether there is an abnormally heated area in the current infrared thermal imaging image. If so, send the preset first identification code of the infrared thermal imaging module and the temperature anomaly warning information. In addition, the infrared thermal imaging module is further configured to switch to the patrol mode or the staring mode working state after receiving the patrol instruction or the staring instruction; A cloud server module, configured to receive the preset first identification code and the temperature anomaly warning information, obtain the location information of the abnormally heated area according to the preset first identification code and the warning information, and output the location information; The low-altitude unmanned fire-fighting module is used to obtain location information and fly to the location corresponding to the location information in the scene, obtain a real-time top-down thermal imaging image and output it to the cloud service module.

[0007] Based on the first aspect, in an optional implementation, the system further includes: The second identification code of the monitored object set in the scene; The low-altitude unmanned fire-fighting module includes a thermal imaging unit for collecting real-time top-down thermal imaging images and a live image acquisition unit for collecting live images of the scene. The low-altitude unmanned fire-fighting module obtains the live image of the scene containing the second identification code through the live image acquisition unit and outputs it to the cloud server module; The cloud service module includes a data storage unit for storing location information, the first identification code, the second identification code and their corresponding relationships. After the cloud service module obtains the live image of the scene containing the second identification code, it extracts and identifies the second identification code, and determines whether the second identification code matches the first identification code. If so, it outputs a patrol instruction indicating to control the device corresponding to the first identification code to resume the patrol mode.

[0008] Based on the first aspect, in an optional implementation, the system further includes an over-temperature protection module, which is set at the monitored object in the scene; the cloud server module is also used to output a temperature sampling signal to the over-temperature protection module in the area corresponding to the location information after outputting the location information. After the over-temperature protection module obtains the temperature sampling signal, it measures the temperature of the detected object and feeds back the temperature measurement result and the third identification code of the over-temperature protection module to the cloud server.

[0009] Based on the first aspect, in an optional implementation, the system further includes an over-temperature protection module, which includes a temperature detection unit for detecting the temperature of the detected object, and also includes a relay unit for cutting off the power supply of the monitored object when the temperature value corresponding to the temperature measurement result is higher than the preset temperature upper limit.

[0010] In the second aspect, the present application also provides a smart fire-fighting monitoring method based on cloud computing. The method includes: Wait for and obtain the alarm information indicating the existence of an abnormally heated area and the first identification code of the infrared thermal imaging module that issues the alarm information, and output a staring instruction indicating to control the device corresponding to the first identification code to switch to the staring mode; Obtain the location information of the abnormally heated area according to the preset first identification code and the temperature anomaly alarm information, and output the location information; Output a flight instruction indicating to control the low-altitude unmanned fire-fighting module to fly to the location corresponding to the location information, and wait for the real-time top-down thermal imaging image obtained and transmitted back after the flight fire-fighting module arrives.

[0011] Based on the second aspect, in an optional implementation, the method further includes: Wait for and obtain the on-site real-time image transmitted back after the flight fire-fighting module arrives, and identify the second identity recognition code corresponding to the monitored object included in the on-site real-time image; Determine whether the second identity recognition code matches the first identity recognition code. If so, output a patrol instruction indicating to control the device corresponding to the first identity recognition code to resume the patrol mode.

[0012] Based on the second aspect, in an optional implementation, the method further includes: Output a temperature sampling signal to the over-temperature protection module arranged on the monitored object in the area corresponding to the location information. After obtaining the temperature sampling signal, the over-temperature protection module measures the temperature of the detected object, and feeds back the temperature measurement result and the third identity recognition code of the over-temperature protection module; After waiting for and obtaining the temperature measurement result and the third identity recognition code of the over-temperature protection module, analyze the temperature measurement result to obtain the abnormal temperature measurement result and its corresponding third identity recognition code.

[0013] Based on the second aspect, in an optional implementation, the method further includes: After extracting the second identity recognition code, match the third identity recognition code with the second identity recognition code. If the match is successful, output a patrol instruction indicating to control the device corresponding to the first identity recognition code to resume the patrol mode.

[0014] In a third aspect, the present application further provides a cloud computing-based intelligent fire-fighting monitoring method for application to an infrared thermal imaging module, including: Collect the current infrared thermal imaging images of at least part of the scene, and determine whether there is an abnormal heating area in the current infrared thermal imaging images; If so, send the preset first identity recognition code of the infrared thermal imaging module and the temperature anomaly warning information; Switch to the working state of the patrol mode or the staring mode according to the received patrol instruction or staring instruction.

[0015] In a fourth aspect, the present application further provides a cloud computing-based intelligent fire-fighting monitoring method for application to a low-altitude unmanned fire-fighting module, including: Wait for and obtain the location information, and generate a flight path according to the location information; Determine whether it has flown to the position in the scene corresponding to the location information; If so, send a in-place prompt message, and obtain the real-time overhead thermal imaging image and output it to the cloud service module.

[0016] The above-mentioned intelligent fire monitoring system and method based on cloud computing monitor the lithium battery energy storage units in the lithium battery energy storage station through an infrared thermal imaging module. When a temperature anomaly occurs, the infrared thermal imaging module sends a first identity code and a temperature anomaly warning message to the cloud server module. After receiving the first identity code and the temperature anomaly warning message, the cloud server module retrieves the location information corresponding to the first identity code from the database according to the first identity code, and sends the location information to the low-altitude unmanned fire module, so as to instruct the low-altitude unmanned fire module to find the lithium battery with abnormal heating in the specified area, so as to realize the timely investigation and handling of abnormal situations in a specific area. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a system topology diagram of an intelligent fire monitoring system based on cloud computing in an embodiment; Figure 2 It is a flowchart of an intelligent fire monitoring method based on cloud computing in an embodiment; Figure 3 It is a flowchart of an intelligent fire monitoring method based on cloud computing in another embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] In a first aspect, the present application provides an intelligent fire monitoring system based on cloud computing, as Figure 1 shown, the system includes an infrared thermal imaging module, a cloud server module and a low-altitude unmanned fire module, wherein: The infrared thermal imaging module is used to collect the current infrared thermal imaging image of at least part of the scene, and judge whether there is an abnormal heating area in the current infrared thermal imaging image. If so, it sends the preset first identity code of the infrared thermal imaging module and the temperature anomaly warning message. In addition, the infrared thermal imaging module is also used to switch to the working state of the patrol mode or the staring mode after receiving the patrol instruction or the staring instruction; The cloud server module is used to receive the preset first identity code and the temperature anomaly warning message, obtain the location information of the abnormal heating area according to the preset first identity code and the warning message, and output the location information; The low-altitude unmanned fire module is used to obtain the location information and fly to the location corresponding to the location information in the scene, obtain the real-time top-down thermal imaging image and output it to the cloud service module.

[0020] In the embodiment of the present application, the scenario is a lithium battery energy storage power station, and the object to be monitored is the lithium battery energy storage unit arranged in the lithium battery energy storage station; the infrared thermal imaging module is a hemispherical infrared thermal imaging camera that can be hoisted. This hemispherical infrared thermal imaging camera has two different working modes: the patrol mode and the staring mode. The patrol mode means that the hemispherical infrared thermal imaging camera completes the inspection of circular or annular areas in the scenario through periodic rotation, thereby reducing the number of installations. The staring mode is that when the hemispherical infrared thermal imaging module detects an area with abnormal temperature, it is controlled to pause the patrol mode, adjust the posture or orientation angle to face the area with abnormal temperature, so as to continuously monitor the abnormal heat source. In addition, according to the field of view of the hemispherical infrared thermal imaging camera, the circular or annular area covered by the same hemispherical infrared thermal imaging camera is evenly divided into several areas, and the several areas are preset with numbers, which is the first identity recognition code for each area. When an area with abnormal heat generation appears, the preset first identity recognition code of the infrared thermal imaging module and the temperature abnormal alarm information are sent to the cloud server module; the low-altitude unmanned fire-fighting module is a fire-fighting drone, which is used to fly to the sky above the area with abnormal temperature after receiving the dispatching instruction, collect images and monitor the area with abnormal temperature, and carry out emergency fire-fighting when necessary; the cloud server module is used to dispatch with the infrared thermal imaging module and the low-altitude unmanned fire-fighting module in the lithium battery energy storage power station through wired or wireless communication methods, so as to realize data processing and dispatching instruction sending. Based on this, the first identity recognition code can be a data code corresponding to the network address of the infrared thermal imaging module. The first identity recognition code is stored in the cloud server. Taking the circular or annular area covered by the same hemispherical infrared thermal imaging camera being evenly divided into 4 fan-shaped areas as an example, when storing data with the server, the network address of each hemispherical infrared thermal imaging camera corresponds to four first identity recognition codes. The four first identity recognition codes can be composed of the network address plus the four end letters A, B, C, and D. Each first identity recognition code corresponds to the position information of 4 fan-shaped areas. When the cloud server module receives the first identity recognition code and the temperature abnormal alarm information, it will retrieve the position information corresponding to the first identity recognition code from the database according to the first identity recognition code, and send the position information to the low-altitude unmanned fire-fighting module, so as to instruct the low-altitude unmanned fire-fighting module to find the lithium battery with abnormal heat generation in the specified area, thereby realizing timely fire control and handling of abnormal situations in a specific area.

[0021] In the embodiment of the present application, the lithium battery energy storage unit in the lithium battery energy storage power station is also preset with a second identification code, and the second identification code is a two-dimensional code or a bar code set on the surface of the lithium battery energy storage unit. The low-altitude unmanned fire-fighting module includes a thermal imaging unit for collecting real-time top-down thermal imaging images and a live image acquisition unit for collecting scene live images. The low-altitude unmanned fire-fighting module obtains the scene live image containing the second identification code through the live image acquisition unit and outputs it to the cloud server module.

[0022] The cloud service module includes a data storage unit and an image storage unit. The data storage unit is used to store location information, the first identification code, the second identification code, the third identification code and their corresponding relationships. After the cloud service module obtains the scene live image containing the second identification code, it extracts and identifies the second identification code, and judges whether the second identification code matches the first identification code. If so, it outputs a patrol instruction indicating to control the device corresponding to the first identification code to resume the patrol mode.

[0023] In the embodiment of the present application, the system further includes an over-temperature protection module. The over-temperature protection module is set at the monitored object in the scene. Specifically, the over-temperature protection module is set on the surface of the lithium battery energy storage unit. If a lithium battery energy storage unit includes several battery packs, a separate over-temperature protection module can be set for each battery pack. Each over-temperature protection module is set with a corresponding third identification code, and the data storage unit of the cloud server also stores a fixed corresponding relationship between the third identification code and the second identification code; the cloud server module is also used to output a temperature sampling signal to the over-temperature protection module in the area corresponding to the location information after outputting the location information. After obtaining the temperature sampling signal, the over-temperature protection module measures the temperature of the detected object and feeds back the temperature measurement result and the third identification code of the over-temperature protection module to the cloud server.

[0024] Through the temperature module, the specific lithium battery energy storage unit or battery pack with abnormal temperature can be accurately determined. After the low-altitude unmanned fire-fighting module reaches the area corresponding to the position information, the thermal imaging unit can be used to locate the position of the lithium battery energy storage unit or battery pack with abnormal temperature, and the second identification code on the surface of the lithium battery energy storage unit or battery pack with abnormal temperature can be collected through the live image acquisition unit and transmitted back to the cloud server module. The cloud server module identifies through the second identification code in the scene live image and determines whether it corresponds and matches the third identification code transmitted back by the over-temperature protection module. If it corresponds and matches, the identification is completed. At this time, the cloud server module sends a patrol instruction to the infrared thermal imaging module to switch the infrared thermal imaging module to the patrol mode, so that the infrared thermal imaging module resumes the patrol monitoring of other lithium battery energy storage units or battery packs in the area. The monitoring work for the abnormally heated lithium battery energy storage unit or battery pack will be taken over by the low-altitude unmanned fire-fighting module. The real-time top-down thermal imaging image and the scene live image collected and transmitted back to the cloud server module by the low-altitude unmanned fire-fighting module after taking over will be stored in the image storage unit for subsequent troubleshooting use.

[0025] In the embodiment of the present application, the over-temperature protection module includes a temperature detection unit for detecting the temperature of the object to be detected, and also includes a relay unit for cutting off the power supply of the monitored object when the temperature value corresponding to the temperature measurement result is higher than the preset temperature upper limit.

[0026] The on-off state of the power supply circuit of the lithium battery energy storage unit or battery pack is controlled by the relay unit. When the temperature of the monitored object exceeds the preset temperature upper limit, the over-temperature protection module directly cuts off the power supply circuit through the relay unit and stops supplying power to the battery pack or the lithium battery energy storage unit, thereby reducing the energy supply to the battery pack or the lithium battery energy storage unit, enabling it to cool down in the power-off state and reducing the probability of fire occurrence.

[0027] Each module in the above cloud computing-based intelligent fire-fighting monitoring system can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0028] Based on the same inventive concept, the embodiment of the present application also provides a cloud computing-based intelligent fire-fighting monitoring method applied to the above-mentioned cloud computing-based intelligent fire-fighting monitoring system. The implementation solutions provided by this method to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the cloud computing-based intelligent fire-fighting monitoring method provided below can refer to the limitations on the cloud computing-based intelligent fire-fighting monitoring system in the above text, and will not be repeated here.

[0029] In a second aspect, the present application also provides a smart fire monitoring method based on cloud computing, which is applied to the cloud server terminal in Figure 1 . The method includes: Step S100: Wait for and obtain an alarm message indicating an abnormally heated area and the first identification code of the infrared thermal imaging module that sends the alarm message, and output a gaze instruction indicating controlling the device corresponding to the first identification code to switch to the gaze mode.

[0030] Among them, the gaze instruction is a control instruction indicating controlling the infrared thermal imaging module to face the abnormal heat source in the image and remain stationary. By sending this instruction, the infrared thermal imaging module is transformed from the patrol mode to the stationary gaze mode, so as to continuously monitor the abnormal heat source.

[0031] Step S200: Obtain the location information of the abnormally heated area according to the preset first identification code and the temperature anomaly alarm message, and output the location information.

[0032] Among them, the location information is stored in the cloud server terminal and corresponds to the information of the first identification code. The location information is the coordinate data of the area where the device corresponding to the first identification code is located. Through the location information, the low-altitude unmanned fire fighting module can be controlled to execute the position instruction to fly to the corresponding area.

[0033] Step S300: Output a flight instruction indicating controlling the low-altitude unmanned fire fighting module to fly to the position corresponding to the location information, and wait for the real-time overhead thermal imaging image obtained and transmitted back after the flight fire fighting module arrives.

[0034] Step S400: Wait for and obtain the scene live image transmitted back after the low-altitude unmanned fire fighting module arrives, and identify the second identification code corresponding to the monitored object included in the scene live image.

[0035] Step S500: Determine whether the second identification code matches the first identification code. If so, output a patrol instruction indicating controlling the device corresponding to the first identification code to resume the patrol mode.

[0036] Through steps S300-S500, the low-altitude unmanned fire fighting module can be controlled to fly to the lithium-ion energy storage unit or battery pack with abnormal heat generation, and take over the infrared thermal imaging module to monitor the lithium-ion energy storage unit or battery pack, so that the infrared thermal imaging module resumes the patrol mode to monitor other lithium-ion energy storage units in the area corresponding to the location information.

[0037] In another embodiment, as Figure 3 shown, the method further includes: Step S600: Output a temperature sampling signal to the over-temperature protection module disposed on the monitored object within the area corresponding to the location information. After obtaining the temperature sampling signal, the over-temperature protection module measures the temperature of the detected object, and feeds back the temperature measurement result and the third identification code of the over-temperature protection module.

[0038] Step S700: After waiting for and obtaining the temperature measurement result and the third identification code of the over-temperature protection module, analyze the temperature measurement result to obtain the abnormal temperature measurement result and its corresponding third identification code.

[0039] Step S800: After extracting the second identification code, match the third identification code with the second identification code. If the match is successful, output a patrol instruction indicating to control the device corresponding to the first identification code to resume the patrol mode.

[0040] Thirdly, the present application also provides a cloud computing-based intelligent fire monitoring method, which is applied to the Figure 1 infrared thermal imaging module therein. The method includes: A100: Collect the current infrared thermal imaging image of at least part of the scene, and determine whether there is an abnormal heating area in the current infrared thermal imaging image; A200: If so, send the preset first identification code of the infrared thermal imaging module and the temperature anomaly warning information; A300: Switch to the working state of the patrol mode or the staring mode according to the received patrol instruction or staring instruction.

[0041] Fourthly, the present application also provides a cloud computing-based intelligent fire monitoring method, which is applied to the Figure 1 low-altitude unmanned fire module therein. The method includes: B100: Wait for and obtain the location information, and generate a flight path according to the location information; B200: Determine whether it has flown to the position in the scene corresponding to the location information; B300: If so, send a in-place prompt message, and obtain the real-time top-down thermal imaging image and output it to the cloud service module.

[0042] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0043] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0044] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0045] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A cloud computing-based intelligent fire monitoring system, characterized in that: include: An infrared thermal imaging module, used to collect a current infrared thermal imaging image of at least part of the scene, and determine whether there is an abnormally hot area in the current infrared thermal imaging image, and if so, send a preset first identity recognition code of the infrared thermal imaging module and temperature abnormality alarm information, and the infrared thermal imaging module is also used to switch to a patrol mode or a gaze mode working state according to a received patrol command or a gaze command; A cloud server module, used to receive the preset first identity identification code and abnormal temperature alarm information, and obtain the location information of the abnormal heating area according to the preset first identity identification code and the alarm information, and output the location information; The low-altitude unmanned fire-fighting module is used to obtain the position information and fly to the position in the scene corresponding to the position information, obtain the real-time bird's-eye view thermal imaging image and output it to the cloud service module.

2. According to the cloud computing-based intelligent fire monitoring system of claim 1, it is characterized in that: Also includes: A second identity code set for the monitored object in the scene; The low-altitude unmanned firefighting module includes a thermal imaging unit for acquiring the real-time overhead thermal imaging image, and a live image acquisition unit for acquiring a live scene image. The low-altitude unmanned firefighting module acquires the live scene image containing the second identity identification code through the live image acquisition unit and outputs it to the cloud server module; The cloud service module includes a data storage unit for storing the location information, a first identity identification code, a second identity identification code and their correspondence. After acquiring a live image of the scene containing the second identity identification code, the cloud service module extracts and identifies the second identity identification code, and determines whether the second identity identification code matches the first identity identification code. If so, the cloud service module outputs a patrol instruction indicating that the device corresponding to the first identity identification code is controlled to resume the patrol mode.

3. According to claim 2, a cloud computing-based intelligent fire monitoring system is characterized in that: It also includes an over-temperature protection module, which is arranged at the monitored object in the scene; the cloud server module is also used to output a temperature sampling signal to the over-temperature protection module in the area corresponding to the location information after outputting the location information; after obtaining the temperature sampling signal, the over-temperature protection module measures the temperature of the detected object, and feeds back the temperature measurement result and the third identity identification code of the over-temperature protection module to the cloud server.

4. According to claim 3, a cloud computing-based intelligent fire monitoring system is characterized in that: The over-temperature protection module includes a temperature detection unit for detecting the temperature of the detected object, and also includes a relay unit for cutting off the power supply of the monitored object when the temperature value corresponding to the temperature measurement result is higher than a preset temperature upper limit.

5. A cloud computing-based intelligent fire monitoring method, characterized in that: include: Waiting for and acquiring alarm information indicating the presence of an abnormally hot area and a first identification code of the infrared thermal imaging module that issues the alarm information, and outputting a gaze instruction indicating controlling a device corresponding to the first identification code to switch to a gaze mode; Acquire location information of an abnormally hot area according to a preset first identity identification code and abnormal temperature alarm information, and output the location information; The output represents the flight command for controlling the low-altitude unmanned fire-fighting module to fly to the position corresponding to the position information, and waits for the real-time overhead thermal imaging image to be acquired and transmitted back after the flying fire-fighting module is in place.

6. The cloud computing-based intelligent fire monitoring method according to claim 5, characterized in that: The method further comprises: Waiting for and acquiring the scene live image sent back by the flight fire fighting module after it is in place, and identifying the second identity identification code contained in the scene live image that corresponds one to one with the monitored object; It is determined whether the second identity identification code matches the first identity identification code. If so, a patrol instruction is outputted to control the device corresponding to the first identity identification code to resume the patrol mode.

7. A cloud computing-based intelligent fire monitoring method according to claim 5 or 6, characterized in that: The method further comprises: Outputting a temperature sampling signal to an over-temperature protection module disposed on the monitored object in the area corresponding to the location information, wherein the over-temperature protection module measures the temperature of the monitored object after acquiring the temperature sampling signal, and feeds back the temperature measurement result and a third identity identification code of the over-temperature protection module; After waiting for and obtaining the temperature measurement result and the third identity identification code of the over-temperature protection module, the temperature measurement result is analyzed to obtain the abnormal temperature measurement result and the corresponding third identity identification code.

8. The cloud computing-based intelligent fire monitoring method according to claim 7 is characterized in that: The method further comprises: After the second identity identification code is extracted, the third identity identification code is matched with the second identity identification code. If the match is successful, a patrol instruction indicating that the device corresponding to the first identity identification code is controlled to resume the patrol mode is output.

9. A cloud computing-based intelligent fire monitoring method, applied to the infrared thermal imaging module of claim 1, characterized in that: include: Collecting a current infrared thermal imaging image of at least part of the scene, and determining whether there is an abnormal heating area in the current infrared thermal imaging image; If yes, sending the preset first identity identification code of the infrared thermal imaging module and temperature abnormality alarm information; The working state switches to the patrol mode or gaze mode according to the received patrol command or gaze command.

10. A cloud computing-based intelligent fire monitoring method, applied to the low-altitude unmanned fire fighting module according to claim 1, characterized in that: include: Wait for and obtain location information, and generate a flight path based on the location information; Determine whether to fly to the location in the scene corresponding to the location information; If so, a prompt message is sent, and a real-time overhead thermal imaging image is obtained and output to the cloud service module.

Images