Fire alarm detection and identification method and system based on Internet platform

Abstract

The invention discloses a fire alarm detection and identification method and system based on an Internet platform, and relates to the technical field of fire alarm identification. The method comprises the steps: determining an identification range, building an identification model based on the identification range, carrying out the spatial position division of the identification range, and correspondingly marking the spatial position in the identification model to obtain a plurality of position points; setting a plurality of detection points in the identification range, and constructing the plurality of detection points in an identification model; fire alarm information in the recognition range is collected according to the detection points, the fire alarm information comprises video information and parameter information, the fire alarm information is processed, the fire alarm information exceeding a preset condition is subjected to early warning, and the spatial position where the fire alarm information exceeding the preset condition is located is prompted. According to the invention, acquisition of fire data can be better integrated, data acquired at subsequent detection points can be better integrated and identified, the accuracy of fire alarm detection and identification is ensured, and the system has good data reference and analysis effects.

Description

Technical Field

[0001] The present invention relates to the technical field of fire detection and identification, and particularly relates to a fire detection and identification method and system based on an Internet platform. Background Art

[0002] With the continuous development of society, people's demand for public safety is increasing day by day. Disaster events such as forest fires and industrial fires occur frequently, posing a serious threat to the life and property safety of the people.

[0003] Currently, in the process of fire detection and identification, due to the large management scope, it is difficult to clearly provide the information collected to the analysis platform for identification during the information collection process, and it is impossible to clearly represent the detection of combustion products generated by fire, thereby affecting the accuracy of fire identification. Summary of the Invention

[0004] The purpose of the present invention is to provide a fire detection and identification method and system based on an Internet platform to solve the deficiencies in the background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A fire detection and identification method based on an Internet platform, comprising the following steps:

[0006] Determine the identification range, construct an identification model based on the identification range, divide the spatial positions of the identification range and mark them correspondingly in the identification model to obtain a plurality of position points;

[0007] Set a plurality of detection points within the identification range and construct the plurality of detection points in the identification model;

[0008] Collect fire alarm information within the identification range according to the detection points, wherein the fire alarm information includes video information and parameter information, process the fire alarm information and give an alarm for the fire alarm information exceeding the preset conditions and prompt the spatial position where the fire alarm information exceeding the preset conditions is located.

[0009] In a preferred embodiment, the step of determining the identification range, constructing an identification model based on the identification range, dividing the spatial positions of the identification range and marking them correspondingly in the identification model to obtain a plurality of position points includes:

[0010] Define the identification range and construct an identification model according to the spatial information within the identification range;

[0011] Divide the spatial positions within the identification range, and mark the divided spatial positions in the identification model;

[0012] Mark the divided spatial positions in the identification model to obtain a plurality of position points.

[0013] In a preferred embodiment, the step of setting a plurality of detection points within the recognition range and constructing the plurality of detection points in the recognition model includes:

[0014] Set a plurality of detection points within the recognition range and mark the detection types corresponding to the plurality of detection points;

[0015] Integrate the detections among the plurality of detection points and construct them in the recognition model.

[0016] In a preferred embodiment, the step of integrating the detections among the plurality of detection points and constructing them in the recognition model includes:

[0017] Respectively obtain the detection ranges of the plurality of detection points, mark the detection ranges of the plurality of detection points in the recognition model, respectively configure corresponding cloud servers for the detection ranges of the plurality of detection points, and connect the cloud servers with the corresponding detection points;

[0018] Based on the cloud server, set a plurality of marking points within the detection ranges of the plurality of detection points, and respectively connect the plurality of marking points within the detection ranges of the plurality of detection points to obtain a plurality of detection networks;

[0019] Determine the overlapping detection ranges of the plurality of detection points as the overlapping ranges, and based on the cloud server, connect the marking points corresponding to the positions within the overlapping ranges among the plurality of detection points;

[0020] Construct both the plurality of marking points and the overlapping ranges where the plurality of marking points are located in the recognition model.

[0021] In a preferred embodiment, the step of, based on the cloud server, setting a plurality of marking points within the detection ranges of the plurality of detection points, respectively connecting the plurality of marking points within the detection ranges of the plurality of detection points, and obtaining a plurality of detection networks includes:

[0022] Construct a data follicle corresponding to the detection range in the cloud server, where the data follicle is a data space in the shape of the corresponding detection range;

[0023] Set a plurality of marking points in the data follicle, the plurality of marking points are in a suspended state, set a plurality of wandering elements in the data follicle, and the wandering elements include a communication temporary end and a drill element, and the communication temporary end and the drill element are in an information binding state;

[0024] When a marking point is in the data follicle, obtain the position of the marking point in the data follicle, arbitrarily select a marking point as the starting point, attach any one of the wandering elements to the marking point where the starting point is located, and then split the communication temporary end and the drill element of the remaining wandering elements and maintain the binding state;

[0025] Connect all the marked points through the drill elements and find the shortest connection path as the optimal connection route;

[0026] Combine the communication temporary end with the bound drill element, make communication connections for adjacent communication temporary ends, and realize communication connections between multiple marked points based on the communication temporary ends;

[0027] Locate the positional relationship between the marked points to obtain a detection network.

[0028] In a preferred embodiment, the step of processing the fire alarm information, warning the fire alarm information exceeding the preset conditions, and prompting the spatial position where the fire alarm information exceeding the preset conditions is located includes:

[0029] Use the video information and parameter information within the acquisition and recognition range of the detection point as fire alarm information;

[0030] Transmit the fire alarm information through the detection point to the corresponding cloud server;

[0031] Distribute the data in the cloud server corresponding to the marked points and display it in the recognition model. Corresponding preset conditions are set for all the marked points in the recognition model, where the preset conditions include the threshold of the fire alarm information;

[0032] Integrate the fire alarm information corresponding to the marked points within the coincidence range to obtain the fire alarm integration information of all the marked points;

[0033] Compare the preset conditions corresponding to the fire alarm integration information of the marked points, warn the fire alarm information exceeding the preset conditions, and prompt the spatial position where the fire alarm information exceeding the preset conditions is located.

[0034] In a preferred embodiment, the step of using the video information and parameter information within the acquisition and recognition range of the detection point as fire alarm information includes:

[0035] Obtain the video information within the recognition range through the detection point;

[0036] The detection point analyzes the gas sample by infrared spectroscopy to obtain the parameter information of the gas;

[0037] The video information and parameter information are used as fire alarm information.

[0038] The present invention also provides a fire alarm detection and recognition system based on an Internet platform, including:

[0039] A determination module for determining the recognition range, constructing a recognition model based on the recognition range, dividing the spatial position of the recognition range, and correspondingly marking multiple position points in the recognition model;

[0040] A building module, connected to a determination module, is used to set multiple detection points within an identification range and construct the multiple detection points into an identification model;

[0041] An alarm module, connected to the building module, is used to collect fire alarm information within the identification range according to the detection points. Among them, the fire alarm information includes video information and parameter information, processes the fire alarm information, and warns of the fire alarm information that exceeds the preset conditions and indicates the spatial location where the fire alarm information that exceeds the preset conditions is located.

[0042] In the above technical solution, the technical effects and advantages provided by the present invention are as follows:

[0043] 1. The present invention can identify gas components by analyzing infrared spectrograms; the video information and parameter information are used as fire alarm information, and then the fire alarm information can be integrated, which can ensure the information integration ability of the collected information and greatly improve the accuracy of fire alarm identification.

[0044] 2. The present invention sets multiple marking points in the data follicle. Here, the marking points are separate data storage terminals. After the data storage terminals are in the data follicle, they can be located on the communication line for binding to fix the positions of the marking points. At the same time, the marking points can be connected through the interconnected communication lines, which can complete the positioning and communication of the markings in the data follicle, and finally obtain a detection network, which can better integrate the collection of fire data and better integrate and identify the data collected by the subsequent detection points, ensuring the accuracy of fire alarm detection and identification, and having a good role in data reference and analysis. Description of the Drawings

[0045] Figure 1 It is a flowchart of the method of the present invention.

[0046] Figure 2 It is a system block diagram of the present invention. Detailed Embodiment

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Embodiment 1. Please refer to Figure 1 As shown, the method for detecting and identifying a fire alarm based on an Internet platform in this embodiment includes the following steps:

[0049] S1. Determine the recognition range, construct a recognition model based on the recognition range, divide the spatial positions within the recognition range and mark them correspondingly in the recognition model to obtain multiple position points;

[0050] S2. Set multiple detection points within the recognition range and construct the multiple detection points in the recognition model;

[0051] S3. Collect fire alarm information within the recognition range according to the detection points. Among them, the fire alarm information includes video information and parameter information. Process the fire alarm information and give an alarm for the fire alarm information that exceeds the preset conditions and prompt the spatial position where the fire alarm information that exceeds the preset conditions is located;

[0052] As described in the above steps S1 - S3, the gas components can be identified by analyzing the infrared spectrogram; the video information and parameter information are used as the fire alarm information, and then the fire alarm information can be integrated, which can ensure the information integration ability of the collected information and greatly improve the accuracy of fire alarm recognition; multiple marking points are set in the data follicle. Here, the marking points are separate data storage terminals. After the data storage terminals are in the data follicle, they can be located on the communication line for binding to fix the positions of the marking points. At the same time, the marking points can be connected to each other through the interconnected communication lines, which can complete the positioning and communication of the markings in the data follicle, and finally obtain a detection network, which can better integrate the collection of fire data and better integrate and identify the data collected by the subsequent detection points, ensure the accuracy of fire alarm detection and recognition, and have a good role in data reference and analysis.

[0053] In one embodiment, the step S1 of determining the recognition range, constructing a recognition model based on the recognition range, dividing the spatial positions within the recognition range and marking them correspondingly in the recognition model to obtain multiple position points includes:

[0054] S11. Delimit the recognition range and construct a recognition model according to the spatial information within the recognition range;

[0055] S12. Divide the spatial positions within the recognition range and mark the divided spatial positions in the recognition model;

[0056] S13. Mark the divided spatial positions in the recognition model to obtain multiple position points;

[0057] As described in the above steps S11 - S13, determine the range that needs to be detected and identified for a fire alarm as the identification range. Then, perform three - dimensional construction based on the spatial information within the identification range to obtain an identification model presented in three - dimensions. Divide the spatial positions within the identification range, which can divide a large - scale spatial range into multiple small - scale spatial ranges. Then, mark the divided spatial positions within the identification range in the identification model. The division result of the actual identification range can also be reflected in the identification model, enabling the identification model to completely correspond to the spatial positions within the actual identification range and the divided spatial positions. Since the identification model can completely correspond to the actual identification range and the divided spatial positions, position marks are made for the divided spatial positions in the identification model to obtain multiple position points. Here, the position marks are made through coding. The position points represent the multiple divided spatial positions, and each spatial position corresponds to a spatial range, which can better assist in the subsequent positioning of fire alarm detection for the range that needs to be detected and identified for a fire alarm;

[0058] In one embodiment, step S2 of setting multiple detection points within the identification range and constructing the multiple detection points in the identification model includes:

[0059] S21. Set multiple detection points within the identification range and mark the detection types corresponding to the multiple detection points;

[0060] S22. Integrate the detections among the multiple detection points and construct them in the identification model;

[0061] As described in the above steps S21 and S22, multiple detection points are set within the identification range. Here, the detection points are used to collect data regarding fire alarm identification. For example, videos within the identification range and various gas parameter data generated when a fire occurs. Therefore, the corresponding detection types at the detection points are different, used to collect different fire data. Then, the detections among the multiple detection points are integrated and constructed in the identification model for display, which can integrate various types of data to jointly identify fires and improve the accuracy of fire identification.

[0062] In one embodiment, step S22 of integrating the detections among the multiple detection points and constructing them in the identification model includes:

[0063] S221. Respectively obtain the detection ranges of the multiple detection points, mark the detection ranges of the multiple detection points in the identification model, configure corresponding cloud servers for the detection ranges of the multiple detection points respectively, and connect the cloud servers with the corresponding detection points;

[0064] S222. Set multiple marker points within the detection ranges of multiple detection points based on the cloud server, and connect the multiple marker points within the detection ranges of the multiple detection points respectively to obtain multiple detection networks;

[0065] S223. Determine the detection ranges where multiple detection points overlap as the overlapping ranges, and connect the marker points corresponding to the positions within the overlapping ranges among the multiple detection points based on the cloud server;

[0066] S224. Construct both the multiple marker points and the overlapping ranges where the multiple marker points are located in the recognition model;

[0067] As described in the above steps S221 - S223, each detection point has a corresponding detection range. For example, a video acquisition point has a certain range for video acquisition, and the acquisition and detection of gases in the air also involve a certain range of acquisition. After obtaining the detection ranges, mark the detection ranges of the multiple detection points in the recognition model respectively. Then, configure corresponding cloud servers for the detection ranges of the multiple detection points respectively. The cloud server is connected to the detection point corresponding to the detection range. In subsequent use, the detection point can transmit the fire-related data collected to the corresponding cloud server. Through the cloud server, the data can be displayed at the marker points within the detection range. The marker points can capture the data to complete the comprehensive display of the data within the detection range. Then, determine the detection ranges where multiple detection points overlap as the overlapping ranges. For example, within a spatial range in the recognition range, the detection ranges of multiple detection points all cover it as the overlapping range. Then, for the marker points existing in the overlapping range of the detection ranges corresponding to the multiple detection points, the cloud server connects the corresponding positions within the overlapping ranges of the multiple detection points. For example, there is an overlapping range between the detection ranges of two detection points. There are two marker points A1 and A2 in the overlapping range of the first detection point, and two marker points B1 and B2 in the overlapping range of the other detection point. A1 and B1 are at the same position within the overlapping range and are connected between A1 and B1. A2 and B2 are at the same position within the overlapping range and are connected between A2 and B2. Connect the marker points corresponding to the positions within the overlapping ranges among the multiple detection points based on the cloud server. The connection of the marker points corresponding to the positions within the overlapping range here is the connection of the marker points among multiple cloud servers, which can realize the detection integration among multiple detection points, better restore the actual fire scene situation, better detect and identify fires, improve the accuracy of subsequent identification. Construct both the multiple marker points and the overlapping ranges where the multiple marker points are located in the recognition model, which can identify fires accurately in the subsequent process.

[0068] In one embodiment, step S222 of setting a plurality of marker points within the detection ranges of a plurality of detection points and respectively connecting the plurality of marker points within the detection ranges of the plurality of detection points to obtain a plurality of detection networks includes:

[0069] S2221. Construct a data follicle corresponding to the detection range in the cloud server, where the data follicle is a data space in the shape of the corresponding detection range;

[0070] S2222. Set a plurality of marker points in the data follicle. The plurality of marker points are in a suspended state. Set a plurality of roaming agents in the data follicle. The roaming agents include communication temporary ends and rehearsal elements, and there is an information binding state between the communication temporary ends and the rehearsal elements;

[0071] S2223. When a marker point is in the data follicle, obtain the position of the marker point in the data follicle. Arbitrarily select a marker point as the starting point, attach any one roaming agent to the marker point where the starting point is located, and then split the communication temporary ends and rehearsal elements of the remaining roaming agents and maintain the binding state;

[0072] S2224. Connect all the marker points through the rehearsal elements and find the shortest connection path as the optimal connection route;

[0073] S2225. Combine the communication temporary ends with the bound rehearsal elements, perform communication connections on adjacent communication temporary ends, and realize communication connections between a plurality of marker points based on the communication temporary ends;

[0074] S2226. Locate the positional relationship between the marker points to obtain the detection network;

[0075] As described in the above steps S2221 - S2226, data follicles corresponding to the detection range are constructed in the cloud server. The data follicle is a data space in the shape of the corresponding detection range, which can carry multiple marker points. The multiple marker points are evenly distributed in the data follicle and are in a suspended state. The multiple marker points are communicatively connected through the data follicle. (Multiple wanderers are set in the data follicle, and each wanderer includes a communication temporary end and an exercise element. The communication temporary end and the exercise element are in an information - binding state.) The data follicle is a data storage device with a communication network set. Multiple marker points are set in the data follicle. Here, the marker points are individual data storage ends. After the data storage end is in the data follicle, obtain the position of the marker point in the data follicle. Arbitrarily select a marker point as the starting point, attach any one wanderer to the marker point where the starting point is located, and then split the communication temporary ends and exercise elements of the remaining wanderers and keep them in a binding state. Connect all the marker points through the exercise element and find the shortest connection path as the optimal connection route. Then, the communication temporary end combines with the bound exercise element, and communicatively connects the adjacent communication temporary ends, which can realize the connection between multiple marker points. Here, the exercise element is a signal point, and there is a signal connection relationship between the exercise elements of all wanderers. Finally, the communication connection between multiple marker points through the data follicle is completed. Here, the connection line connecting multiple marker points formed by the wanderers is used as the communication network. Then, fix the positions of the marker points, and at the same time, the connection between multiple marker points can be realized through the interconnected communication lines, which can complete the positioning and communication of the markers in the data follicle, and finally obtain the detection network, which can better integrate the collection of fire data and better integrate and identify the data collected by subsequent detection points, ensuring the accuracy of fire alarm detection and identification, and having a good role in data reference and analysis.

[0076] In one embodiment, step S3 of processing the fire alarm information, warning the fire alarm information exceeding the preset conditions, and prompting the spatial position where the fire alarm information exceeding the preset conditions is located includes:

[0077] S31. Use the video information and parameter information within the acquisition and recognition range of the detection point as the fire alarm information;

[0078] S32. Transmit the fire alarm information to the corresponding cloud server through the detection point;

[0079] S33. Display the data distribution in the cloud server corresponding to the marker points in the recognition model. Corresponding preset conditions are set for all the marker points in the recognition model. Among them, the preset conditions include the threshold of the fire alarm information;

[0080] S34. Integrate the fire alarm information corresponding to the marker points within the coincidence range to obtain the fire alarm integration information of all the marker points;

[0081] S35. Compare the preset conditions corresponding to the integrated fire alarm information of the marked points, and give an alarm for the fire alarm information that exceeds the preset conditions and prompt the spatial location where the fire alarm information that exceeds the preset conditions is located;

[0082] In one embodiment, the step S31 of using the video information and parameter information collected by the detection point within the recognition range as fire alarm information includes:

[0083] S311. Obtain the video information within the recognition range through the detection point;

[0084] S312. The detection point analyzes the gas sample by infrared spectroscopy to obtain the parameter information of the gas;

[0085] S313. The video information and parameter information are used as fire alarm information;

[0086] As described in the above steps S31 - S35, integrate the fire alarm information corresponding to the marked points within the overlapping range. Since the marked points within the overlapping range in multiple cloud servers are in a communication state, all the fire alarm information on the same location point can be obtained. It is possible to identify and judge whether the fire alarm information needs to be alarmed with the marked point as the unit, improving the accuracy and fineness of fire alarm identification. It can use the point as the identification unit, obtain the video information within the recognition range through the detection point, and obtain the status within the recognition range through the video information. Based on the video acquisition and through the flame recognition algorithm and deep learning model, identify the flames in the images and video streams. Its working process includes data acquisition and preprocessing, deep learning model construction, model training and optimization, and practical application. By collecting a large number of video data with flames and annotating them, the characteristic information of the flames can be learned, and then the presence and status of the flames can be accurately identified in real-time monitoring. Then the detection point analyzes the gas sample by infrared spectroscopy to obtain the parameter information of the gas; Infrared spectroscopy uses an infrared spectrometer to detect the gas sample, and the gas components can be identified by analyzing the infrared spectrogram; The video information and parameter information are used as fire alarm information, and then the fire alarm information can be integrated, which can ensure the information integration ability of the acquisition and greatly improve the accuracy of fire alarm identification;

[0087] Embodiment 2, please refer to Figure 2 As shown, the fire alarm detection and identification system based on the Internet platform in this embodiment includes:

[0088] A determination module, configured to determine the recognition range, construct a recognition model based on the recognition range, divide the spatial position of the recognition range and mark it correspondingly in the recognition model to obtain a plurality of position points;

[0089] The building module is connected to the determination module and is used to set multiple detection points within the recognition range and build the multiple detection points into the recognition model;

[0090] The alarm module is connected to the building module and is used to collect fire alarm information within the recognition range according to the detection points. Among them, the fire alarm information includes video information and parameter information, process the fire alarm information, and give an early warning to the fire alarm information that exceeds the preset conditions and prompt the spatial position where the fire alarm information that exceeds the preset conditions is located.

[0091] As mentioned above, it is only a preferred embodiment of the present invention and does not impose any limitation on the present invention. Any simple modification, change, and equivalent structural change made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A fire detection and identification method based on an Internet platform, characterized in that: The following steps are involved: Determine the recognition range, build a recognition model based on the recognition range, divide the recognition range into spatial positions and mark corresponding positions in the recognition model to obtain multiple position points; Set multiple detection points within the recognition range and build the multiple detection points into the recognition model; Fire alarm information within the identification range is collected according to the detection points, wherein the fire alarm information includes video information and parameter information, the fire alarm information is processed, and the fire alarm information exceeding the preset conditions is warned and the spatial location of the fire alarm information exceeding the preset conditions is indicated.

2. The method for fire detection and identification based on an Internet platform according to claim 1, characterized in that: The steps of determining the recognition range, building a recognition model based on the recognition range, dividing the recognition range into spatial positions and correspondingly marking a plurality of position points in the recognition model include: Define the recognition range and build a recognition model based on the spatial information within the recognition range; Divide the spatial positions within the recognition range, and mark the divided spatial positions within the recognition range in the recognition model; In the recognition model, the divided spatial positions are marked to obtain multiple position points.

3. The method for fire detection and identification based on an Internet platform according to claim 1, characterized in that: The step of setting a plurality of detection points within the recognition range and constructing the plurality of detection points into the recognition model comprises: Set multiple detection points within the recognition range, and mark the detection types corresponding to the multiple detection points; The detection between multiple detection points is integrated and built into the recognition model.

4. The method for fire detection and identification based on an Internet platform according to claim 3, characterized in that: The step of integrating detection between multiple detection points and building them into a recognition model includes: Respectively obtain the detection ranges of the multiple detection points, mark the detection ranges of the multiple detection points in the recognition model, configure corresponding cloud servers corresponding to the detection ranges of the multiple detection points, and connect the cloud servers to the corresponding detection points; Based on the cloud server, multiple marking points are set within the detection range of multiple detection points, and multiple marking points within the detection range of the multiple detection points are respectively connected to obtain multiple detection networks; Determine the detection range where multiple detection points overlap as the overlap range, and connect the marking points corresponding to the positions within the overlap range among the multiple detection points based on the cloud server; Multiple marking points and overlapping ranges of the multiple marking points are constructed in the recognition model.

5. The method for fire detection and identification based on an Internet platform according to claim 4, characterized in that: The step of setting a plurality of marking points within the detection range of the plurality of detection points based on the cloud server, and connecting the plurality of marking points within the detection range of the plurality of detection points respectively to obtain a plurality of detection networks comprises: Constructing a data follicle corresponding to the detection range in the cloud server, wherein the data follicle is a data space corresponding to the shape of the detection range; A plurality of marking points are set in the data follicle, and the plurality of marking points are in a suspended state. A plurality of wanderers are set in the data follicle, and the wanderers include a temporary communication terminal and a rehearsal element, and the temporary communication terminal and the rehearsal element are in an information binding state; When the mark point is in the data follicle, obtain the position of the mark point in the data follicle, select any mark point as the starting point, attach any wanderer to the mark point where the starting point is located, and then separate the communication temporary ends of the remaining wanderers from the exercise element and keep them bound; Connect all the marked points through drills and find the shortest connection path as the optimal connection route; Combine the temporary communication terminal with the bound drill element, connect the adjacent temporary communication terminals for communication, and realize the communication connection between multiple marking points based on the temporary communication terminal; The positional relationship between the positioning markers is determined to obtain the detection network.

6. The method for fire detection and identification based on an Internet platform according to claim 1, characterized in that: The step of processing the fire alarm information, issuing an early warning for the fire alarm information exceeding the preset conditions, and indicating the spatial location of the fire alarm information exceeding the preset conditions includes: According to the detection point, the video information and parameter information within the identification range are collected as fire alarm information; Transmit fire alarm information to the corresponding cloud server through the detection point; The data distribution in the cloud server is displayed in the recognition model in correspondence with the marking points, and corresponding preset conditions are formulated for all the marking points in the recognition model, wherein the preset conditions include the threshold value of the fire alarm information; Integrate the fire alarm information corresponding to the marked points within the overlapped range to obtain the fire alarm integrated information of all marked points; The preset conditions corresponding to the fire alarm integrated information of the marked point are compared, and the fire alarm information exceeding the preset conditions is warned and the spatial location of the fire alarm information exceeding the preset conditions is indicated.

7. The method for fire detection and identification based on an Internet platform according to claim 6, characterized in that: The step of collecting video information and parameter information within the identification range according to the detection point as fire alarm information includes: Obtain video information within the recognition range through detection points; The detection point analyzes the gas sample through infrared spectroscopy to obtain gas parameter information; The video information and parameter information are used as fire alarm information.

8. A fire detection and identification system based on an Internet platform, used to implement a fire detection and identification method based on an Internet platform as claimed in any one of claims 1 to 7, characterized in that: include: A determination module is used to determine the recognition range, build a recognition model based on the recognition range, divide the recognition range into spatial positions and mark corresponding positions in the recognition model to obtain multiple positions; A construction module, connected to the determination module, is used to set a plurality of detection points within the recognition range and construct the plurality of detection points in the recognition model; The alarm module is connected to the construction module and is used to collect fire alarm information within the identification range according to the detection point, wherein the fire alarm information includes video information and parameter information, process the fire alarm information, and issue an early warning for the fire alarm information that exceeds the preset conditions and prompt the spatial location of the fire alarm information that exceeds the preset conditions.

Images