Fire detection method and device, program product and electronic equipment

Abstract

The invention provides a fire detection method and device, a program product and electronic equipment, and relates to the technical field of computers. The method comprises the steps of determining temperature data and humidity data of a target space in a preset time period, and processing the temperature data and the humidity data of the target space to obtain temperature change rate data and humidity change rate data; determining carbon monoxide concentration data and smoke concentration data of the target space in the preset time period; and fire detection information of the target space in the preset time period is determined according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data and the smoke concentration data. By integrating the temperature change rate, the humidity change rate, the carbon monoxide concentration data and the smoke concentration data, whether the fire exists in the target space within the preset time period or not can be accurately positioned, and the fire detection accuracy is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and in particular, to a fire detection method, apparatus, program product, and electronic device. Background Art

[0002] Fire detection is a process of predicting and judging the possibility of a fire, its development trend, and the degree of harm, etc., and is an essential part of business scenarios such as fire prevention, emergency response, and resource allocation.

[0003] However, in the related art, only simple temperature changes are used to determine whether there is a fire. Although such a method can achieve fire detection, the detection method of determining whether there is a fire only based on temperature changes may result in false detections.

[0004] Therefore, how to accurately detect a fire has become an urgent problem to be solved. Summary of the Invention

[0005] The present disclosure provides a fire detection method, a fire detection apparatus, a computer program product, and an electronic device, so as to at least to some extent improve the accuracy of fire detection.

[0006] According to a first aspect of the present disclosure, there is provided a fire detection method, the method including:

[0007] Determine the temperature data and humidity data of a target space within a preset time period, and respectively process the temperature data and humidity data of the target space to obtain temperature change rate data and humidity change rate data;

[0008] Determine the carbon monoxide concentration data and smoke concentration data of the target space within the preset time period;

[0009] According to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data, determine the fire detection information of the target space within the preset time period.

[0010] In a possible implementation manner, respectively processing the temperature data and humidity data of the target space to obtain temperature change rate data and humidity change rate data includes:

[0011] Establish a target linked list, and store the temperature data and humidity data of the target space based on the target linked list;

[0012] Perform screening processing on the temperature data and humidity data stored in the target linked list to obtain processed temperature data and processed humidity data;

[0013] Process the processed temperature data and the processed humidity data respectively to obtain temperature change rate data and humidity change rate data.

[0014] In a possible implementation manner, establish a target linked list, including:

[0015] Determine the temperature and humidity transfer information of the target space;

[0016] According to the temperature and humidity transfer information, determine the target length of the linked list, and establish a linked list with the target length as the target linked list.

[0017] In a possible implementation manner, process the processed temperature data and the processed humidity data respectively to obtain temperature change rate data and humidity change rate data, including:

[0018] Determine the first difference between the last temperature data and the first temperature data in the target linked list;

[0019] According to the first difference and the target length of the target linked list, obtain the temperature change rate data; and,

[0020] Determine the second difference between the last humidity data and the first humidity data in the target linked list;

[0021] According to the second difference and the target length of the target linked list, obtain the humidity change rate data.

[0022] In a possible implementation manner, determine the fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data, including:

[0023] Input the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data into a preset fuzzy inference system to obtain a predicted result value;

[0024] According to the predicted result value and the preset fuzzy rules, determine the fire detection information of the target space within the preset time period.

[0025] In a possible implementation manner, input the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data into a preset fuzzy inference system to obtain a predicted result value, including:

[0026] According to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, the smoke concentration data, and their respective membership functions, determine the first value, the second value, the third value, and the fourth value;

[0027] Obtain a target graph based on the first value, the second value, the third value, the fourth value, and the graph of the output membership degree;

[0028] Determine the predicted result value according to the centroid of the target graph.

[0029] In a possible implementation manner, determining the first value, the second value, the third value, and the fourth value according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, the smoke concentration data, and their respective corresponding membership functions includes:

[0030] Obtain the first value according to the temperature change rate data and the first membership function;

[0031] Obtain the second value according to the humidity change rate data and the second membership function;

[0032] Obtain the third value according to the carbon monoxide concentration data and the third membership function;

[0033] Obtain the fourth value according to the smoke concentration data and the fourth membership function;

[0034] Wherein, the first membership function, the second membership function, the third membership function, and the fourth membership function are all triangular membership functions.

[0035] According to a second aspect of the present disclosure, there is provided a fire detection device, the device includes:

[0036] An obtaining unit, configured to determine temperature data and humidity data of a target space within a preset time period, and respectively process the temperature data and humidity data of the target space to obtain temperature change rate data and humidity change rate data;

[0037] A determining unit, configured to determine carbon monoxide concentration data and smoke concentration data of the target space within the preset time period;

[0038] A detecting unit, configured to determine fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data.

[0039] In a possible implementation manner, the obtaining unit is specifically configured to:

[0040] Establish a target linked list, and store the temperature data and humidity data of the target space based on the target linked list;

[0041] Screen the temperature data and humidity data stored in the target linked list to obtain the processed temperature data and the processed humidity data;

[0042] Process the processed temperature data and the processed humidity data respectively to obtain the temperature change rate data and the humidity change rate data.

[0043] In a possible implementation manner, the obtaining unit is specifically configured to:

[0044] Determine the temperature and humidity transfer information of the target space;

[0045] According to the temperature and humidity transfer information, determine the target length of the linked list, and establish a linked list with the target length as the target linked list.

[0046] In a possible implementation manner, the obtaining unit is specifically configured to:

[0047] Determine the first difference between the last temperature data and the first temperature data in the target linked list;

[0048] According to the first difference and the target length of the target linked list, obtain the temperature change rate data; and,

[0049] Determine the second difference between the last humidity data and the first humidity data in the target linked list;

[0050] According to the second difference and the target length of the target linked list, obtain the humidity change rate data.

[0051] In a possible implementation manner, the detection unit is specifically configured to:

[0052] Input the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data into a preset fuzzy inference system to obtain a predicted result value;

[0053] According to the predicted result value and the preset fuzzy rules, determine the fire detection information of the target space within the preset time period.

[0054] In a possible implementation manner, the detection unit is specifically configured to:

[0055] According to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data and their respective membership functions, determine the first value, the second value, the third value, and the fourth value;

[0056] According to the first value, the second value, the third value, the fourth value, and the graph of the output membership degree, obtain the target graph;

[0057] Determine the predicted result value according to the centroid of the target graph.

[0058] In a possible implementation manner, the detection unit is specifically configured to:

[0059] Obtain a first value according to the temperature change rate data and the first membership function;

[0060] Obtain a second value according to the humidity change rate data and the second membership function;

[0061] Obtain a third value according to the carbon monoxide concentration data and the third membership function;

[0062] Obtain a fourth value according to the smoke concentration data and the fourth membership function;

[0063] Wherein, the first membership function, the second membership function, the third membership function and the fourth membership function are all triangular membership functions.

[0064] According to a third aspect of the present disclosure, there is provided a computer program product, including a computer program, which when executed by a processor, implements the method of the first aspect and its possible implementation manners described above.

[0065] According to a fourth aspect of the present disclosure, there is provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein, the processor is configured to execute the executable instructions to execute the method of the first aspect and its possible implementation manners described above.

[0066] The technical solution of the present disclosure has the following beneficial effects:

[0067] In the embodiments of the present disclosure, the temperature data and humidity data of the target space within a preset time period can be determined, and the temperature data and humidity data of the target space are respectively processed to obtain temperature change rate data and humidity change rate data; and, the carbon monoxide concentration data and smoke concentration data of the target space within a preset time period are determined, and then according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data and smoke concentration data, the fire detection information of the target space within the preset time period is determined. It can be seen that the entire detection process of fire detection in the embodiments of the present disclosure is automated, thereby improving the fire detection efficiency to a certain extent. In addition, since the temperature change rate data, humidity change rate data, carbon monoxide concentration data and smoke concentration data are combined, it is possible to accurately determine whether there is a fire in the target space within a preset time period, and avoid the false detection situation where a non-fire temperature anomaly or humidity anomaly is detected as a fire, thereby greatly improving the fire detection accuracy.

[0068] Other features and advantages of the present disclosure will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present disclosure. The objectives and other advantages of the present disclosure may be realized and attained by the structure particularly pointed out in the written description, claims, as well as the drawings. Description of the Drawings

[0069] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments of the present disclosure. Obviously, the following introduced drawings are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings may be obtained based on these drawings.

[0070] Figure 1 Shows a schematic diagram of an application scenario in this exemplary embodiment;

[0071] Figure 2 Shows a flowchart of a fire detection method in this exemplary embodiment;

[0072] Figure 3 Shows a schematic diagram of a first membership function in this exemplary embodiment;

[0073] Figure 4 Shows a schematic diagram of a second membership function in this exemplary embodiment;

[0074] Figure 5 Shows a schematic diagram of a third membership function in this exemplary embodiment;

[0075] Figure 6 Shows a schematic diagram of a fourth membership function in this exemplary embodiment;

[0076] Figure 7 Shows a schematic diagram of determining a prediction result value in this exemplary embodiment;

[0077] Figure 8 Shows a schematic diagram of a prediction membership function in this exemplary embodiment;

[0078] Figure 9 Shows a schematic diagram of a preset fuzzy rule in this exemplary embodiment;

[0079] Figure 10 Shows a schematic diagram of the structure of a fire detection device in this exemplary embodiment;

[0080] Figure 11 Shows a schematic diagram of the structure of an electronic device in this exemplary embodiment. Detailed implementation manners

[0081] To make the objectives, technical solutions and advantages of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are only a part rather than all of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts shall fall within the scope of protection of the present disclosure. Without conflict, the embodiments in the present disclosure and the features in the embodiments may be combined with each other arbitrarily. And although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a sequence different from that here.

[0082] The terms "including" and any variations thereof in the specification and claims of the present disclosure are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0083] One or more of the embodiments of the present disclosure, "more than one" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B may be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (item)" or its similar expression below refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c may represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, c may be single or multiple.

[0084] It should be noted that the terms "first", "second", "third", etc. in the specification, claims and the above-mentioned drawings of the present disclosure are used to distinguish similar objects and do not necessarily describe a specific order, sequence, size and priority. For example, the first difference value and the second difference value in the embodiments of the present disclosure are only used to distinguish different difference values. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present disclosure described here can be implemented in an order different from those illustrated or described here. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present disclosure. On the contrary, they are only examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0085] The exemplary embodiments of the present disclosure will be described below with reference to the accompanying drawings. The accompanying drawings are schematic diagrams of the present disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the accompanying drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, or in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. The embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in the present disclosure may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to give a full understanding of the embodiments of the present disclosure. However, those skilled in the art should be aware that one or more specific details may be omitted when implementing the technical solutions of the present disclosure, or other methods, components, devices, steps, etc. may be used to replace one or more specific details.

[0086] It should be noted that in the embodiments of the present disclosure, some industry-existing solutions such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present disclosure, but it does not mean that the applicant has already or necessarily used this solution. In the technical solutions of the present disclosure, the collection, transmission, use, etc. of temperature data, humidity data, carbon monoxide concentration data, and smoke concentration data all comply with relevant national laws and regulations.

[0087] In the related art, the presence of a fire is determined only based on simple temperature changes. Although such a method can achieve the detection of a fire, the detection method of determining the presence of a fire only based on temperature changes may result in false detections. Therefore, how to accurately detect a fire has become an urgent problem to be solved.

[0088] In view of this, an exemplary embodiment of the present disclosure provides a fire detection method. Through this method, temperature data and humidity data of a target space within a preset time period can be determined, and the temperature data and humidity data of the target space are respectively processed to obtain temperature change rate data and humidity change rate data; and, carbon monoxide concentration data and smoke concentration data of the target space within the preset time period are determined, and then fire detection information of the target space within the preset time period is determined according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data. It can be seen that the entire detection process of fire detection in the embodiments of the present disclosure is automated, thereby improving the fire detection efficiency to a certain extent. In addition, since the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data are combined, it is possible to more accurately determine whether there is a fire in the target space within the preset time period, avoiding the situation of misdetection of a fire due to abnormal temperature changes or abnormal humidity changes that are not caused by a fire, thereby greatly improving the fire detection accuracy.

[0089] To better understand the technical solutions provided by the embodiments of the present disclosure, the following briefly introduces the application scenarios applicable to the technical solutions provided by the embodiments of the present disclosure. It should be noted that the application scenarios described below are only used to illustrate the embodiments of the present disclosure and are not limiting. In specific implementation, the technical solutions provided by the embodiments of the present disclosure can be flexibly applied according to actual needs.

[0090] In the embodiments of the present disclosure, the fire detection technology can be applied to various business scenarios that require fire detection, such as classrooms, stations, factory areas, laboratories, etc. For example, it can be applied to the business scenario of fire detection in a laboratory. The embodiments of the present disclosure do not limit this.

[0091] Please refer to Figure 1 as shown Figure 1An application scenario applicable to the technical solution of the embodiments of the present disclosure. In this scenario schematic diagram, it includes multiple collection devices 101 and an electronic device 102. Among them, the multiple collection devices are respectively collection device 101-1, collection device 101-2, …, collection device 101-n, where n is a positive integer. For example, the multiple collection devices 101 can respectively collect temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data. For example, collection device 101-1 among the multiple collection devices can collect temperature data, collection device 101-2 can collect humidity data, collection device 101-3 can collect carbon monoxide concentration data, and collection device 101-4 can collect smoke concentration data. Of course, it is also possible that one collection device among the multiple collection devices collects two types of data, and the other collection devices respectively collect one type of data alone. For example, collection device 101-1 can collect temperature data and humidity data, collection device 101-2 can collect carbon monoxide concentration data, and collection device 101-3 can collect smoke concentration data. The embodiments of the present disclosure do not make any limitations in this regard.

[0092] Among them, between the collection device 101 and the electronic device 102, and between each of the collection devices 101, they can be directly or indirectly communicatively connected through one or more networks 103.

[0093] In the embodiments of the present disclosure, the collection device 101-1 sends the collected temperature data, humidity data, carbon monoxide concentration data, and smoke concentration data to the electronic device 102. The electronic device 102 receives the temperature data and humidity data of the target space within a preset time period, and respectively processes the temperature data and humidity data of the target space to obtain temperature change rate data and humidity change rate data. Then, based on the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data, it determines the fire detection information of the target space within the preset time period.

[0094] Among them, Figure 1 each of the collection devices 101 can be a sensor and / or a detector, but is not limited thereto. In other words, various devices with the function of supporting the collection of temperature data, humidity data, carbon monoxide concentration data, and smoke concentration data can be used as the collection device 101.

[0095] And, Figure 1The electronic device 102 can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms, but is not limited thereto.

[0096] Of course, the method provided by the embodiments of the present disclosure is not limited to Figure 1 the application scenarios shown, and can also be used in other possible application scenarios. For example, in an application scenario where only an electronic device implements a fire detection method, the embodiments of the present disclosure do not impose any restrictions.

[0097] To further illustrate the technical solutions provided by the embodiments of the present disclosure, the following will be described in detail in combination with the accompanying drawings and specific implementation manners. Although the embodiments of the present disclosure provide method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or non-creative labor. In steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiments of the present disclosure. When the method is actually processed or executed by a device, it can be executed in the method order shown in the embodiments or drawings or in parallel.

[0098] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of a fire detection method in the embodiments of the present disclosure. The process of the method can be executed by an electronic device, for example. The electronic device can be Figure 1 the electronic device 102 in

[0099] Step 201: Determine the temperature data and humidity data of the target space within a preset time period, and process the temperature data and humidity data of the target space respectively to obtain temperature change rate data and humidity change rate data.

[0100] In the embodiments of the present disclosure, the electronic device can receive the temperature data and humidity data of the target space within a preset time period sent by the acquisition device. Among them, the acquisition device can be a single temperature and humidity collector or temperature and humidity sensor. Of course, the acquisition device can also be a temperature collector and a humidity collector, and the acquisition device can also be a temperature sensor and a humidity sensor. The embodiments of the present disclosure do not make any limitations thereto.

[0101] In the embodiments of the present disclosure, the target space can be understood as the space that needs to be detected for fire, such as a classroom, a factory building, a hospital building, etc. The embodiments of the present disclosure do not make any limitations thereto.

[0102] In the embodiments of the present disclosure, in order to avoid waste of computing resources, fire detection can be performed on the target space at a preset period, and the preset period can be, for example, 60 seconds, 90 seconds, etc. The embodiments of the present disclosure do not limit this. Therefore, the electronic device can receive the temperature data and humidity data of the target space within a preset time period. Wherein, the preset time period can be understood as the aforementioned preset period.

[0103] That is to say, the acquisition device can periodically send temperature data and humidity data to the electronic device, or the electronic device can periodically receive the temperature data and humidity data sent by the acquisition device. The embodiments of the present disclosure do not limit this.

[0104] In the embodiments of the present disclosure, the electronic device can obtain the temperature change rate data and humidity change rate data by, but not limited to, the following steps:

[0105] Step A: Establish a target linked list, and store the temperature data and humidity data of the target space based on the target linked list.

[0106] In the embodiments of the present disclosure, the electronic device can determine the temperature and humidity transfer information of the target space, and then determine the target length of the linked list according to the temperature and humidity transfer information, and establish a linked list with the target length as the target linked list.

[0107] In the embodiments of the present disclosure, the electronic device can determine the temperature and humidity transfer information of the target space according to at least one of the area information of the target space, the building type, and the material of the stored object. After determining the temperature and humidity transfer information of the target space, the target length of the linked list can be determined according to the temperature and humidity transfer information, and a linked list with the target length can be established as the target linked list.

[0108] For example, the electronic device can determine the temperature and humidity transfer information of the target space according to the area information of the target space; or, the electronic device can determine the temperature and humidity transfer information of the target space according to the building type information of the target space; or, the electronic device can determine the temperature and humidity transfer information of the target space according to the material of the object stored in the target space.

[0109] For example, the electronic device can determine the temperature and humidity transfer information of the target space according to the area information and building type information of the target space; or, the electronic device can determine the temperature and humidity transfer information of the target space according to the area information and the material of the stored object; or, the electronic device can determine the temperature and humidity transfer information of the target space according to the building type information and the material of the stored object.

[0110] For example, the electronic device can determine the temperature and humidity transfer information of the target space according to the area information, building type, and the material of the stored object of the target space.

[0111] It should be noted that in the embodiments of the present disclosure, if the temperature and humidity transfer information is an integral information, the target linked list obtained based on this is a single linked list; if the temperature and humidity transfer information includes two pieces of information, namely temperature transfer information and humidity transfer information, then the target linked list obtained based on this includes two linked lists, namely the first linked list and the second linked list. The embodiments of the present disclosure do not make any limitations in this regard.

[0112] To better understand the solution for determining the target linked list provided by the present disclosure, the following will be described with several specific examples.

[0113] In a possible implementation manner, considering the differences in the area information of the target space and / or the building type, the situations of temperature transfer and humidity transfer will be different. Therefore, the temperature and humidity transfer information can be determined based on the differences in the area information of the target space and / or the building type, and then based on the temperature and humidity transfer information, the length information of the linked list can be determined. Furthermore, based on the length information of the linked list, the target linked list can be established, so that the temperature change rate data and the humidity change rate data can be determined more accurately.

[0114] Optionally, if the temperature and humidity transfer information is an integral information, the target linked list obtained based on this is a single linked list.

[0115] For example, the electronic device can determine the area information of the target space, and then according to the area information of the target space, determine the first temperature and humidity transfer information. Based on the first temperature and humidity transfer information and the pre-set corresponding relationship between the temperature and humidity transfer information and the level information, determine the first level information. Then, based on the first level information and the pre-set matching table, determine the target length of the linked list, so that a linked list with the target length can be established as the target linked list.

[0116] For example, the electronic device can determine the building type information of the target space, and according to the building type information of the target space, determine the second temperature and humidity transfer information. Based on the second temperature and humidity transfer information and the pre-set corresponding relationship between the temperature and humidity transfer information and the level information, determine the second level information. Then, based on the second level information and the pre-set matching table, determine the target length of the linked list, so that a linked list with the target length can be established as the target linked list.

[0117] For example, the electronic device can determine the building type information and area information of the target space, determine the first temperature and humidity transfer information according to the area information of the target space, and determine the second temperature and humidity transfer information according to the building type information of the target space. Then, it can determine the comprehensive temperature and humidity transfer information according to the first temperature and humidity transfer information and the second temperature and humidity transfer information, so as to determine the third level information based on the comprehensive temperature and humidity transfer information and the corresponding relationship between the temperature and humidity transfer information and the level information set in advance. Then, based on the third level information and the preset matching table, it can determine the target length of the linked list and establish a linked list with the target length as the target linked list.

[0118] Among them, the aforementioned preset matching table includes multiple corresponding relationships, and each corresponding relationship includes level information and linked list length information. In this way, when the electronic device determines the level information, it can match and determine the linked list length information from the preset matching table.

[0119] Optionally, if the temperature and humidity transfer information includes two pieces of information, namely temperature transfer information and humidity transfer information, the target linked list obtained based on this includes two linked lists, namely the first linked list and the second linked list.

[0120] That is to say, the electronic device determines the temperature transfer information and humidity transfer information corresponding to the target space according to the area information and / or building type information of the target space, determines the first length information according to the temperature transfer information to establish the first linked list based on the first length information, and determines the second length information according to the humidity transfer information to establish the second linked list based on the second length information.

[0121] For example, the electronic device can determine the first temperature transfer information and the first humidity transfer information based on the area information of the target space, and there is a first corresponding relationship between the temperature transfer information and the level information and a second corresponding relationship between the humidity transfer information and the level information set in advance. Thus, it can determine the first level information corresponding to the first temperature transfer information according to the first corresponding relationship, and then can screen out the first length information that matches the first level information from the preset matching table, and use the linked list established based on the first length information as the first linked list. And it can determine the second level information corresponding to the first humidity transfer information according to the second corresponding relationship, and then can screen out the second length information that matches the second level information from the preset matching table, and use the linked list established based on the second length information as the second linked list.

[0122] For example, the electronic device can determine the second temperature transfer information and the second humidity transfer information based on the building type information of the target space, and has a pre-set first correspondence between the temperature transfer information and the level information and a second correspondence between the humidity transfer information and the level information. Thus, the first level information corresponding to the second temperature transfer information can be determined according to the first correspondence, and then the first length information matching the first level information can be filtered out from the pre-set matching table, and the linked list established based on the first length information is used as the first linked list. Moreover, the second level information corresponding to the second humidity transfer information can be determined according to the second correspondence, and then the second length information matching the second level information can be filtered out from the pre-set matching table, and the linked list established based on the second length information is used as the second linked list.

[0123] For example, the electronic device can determine the first temperature transfer information and the first humidity transfer information based on the area information of the target space and determine the second temperature transfer information and the second humidity transfer information based on the building type information of the target space, and determine the first weight corresponding to the first temperature transfer information, the second weight corresponding to the first humidity transfer information, the third weight corresponding to the second temperature transfer information, and the fourth weight corresponding to the second humidity transfer information. Thus, the comprehensive temperature transfer information corresponding to the target space can be comprehensively determined according to the first temperature transfer information, the second temperature transfer information, the first weight, and the third weight. Moreover, the comprehensive humidity transfer information corresponding to the target space can be comprehensively determined according to the first humidity transfer information, the second humidity transfer information, the second weight, and the fourth weight. Further, the third level information corresponding to the comprehensive temperature transfer information can be determined according to the pre-set first correspondence between the temperature transfer information and the level information, and then the first length information matching the third level information can be filtered out from the pre-set matching table, and the linked list established based on the first length information is used as the first linked list. Moreover, the second level information corresponding to the comprehensive humidity transfer information can be determined according to the pre-set second correspondence between the humidity transfer information and the level information, and then the second length information matching the second level information can be filtered out from the pre-set matching table, and the linked list established based on the second length information is used as the second linked list.

[0124] In a possible implementation, considering the differences in the objects stored in the target space, the temperature transfer and humidity transfer situations will vary. Therefore, the temperature and humidity transfer information can be determined based on the materials of the objects stored in the target space, and then the length information of the linked list can be determined based on the temperature and humidity transfer information. Furthermore, the target linked list can be established based on the length information of the linked list, so that the temperature change rate data and the humidity change rate data can be determined more accurately.

[0125] In a possible implementation, the electronic device can determine humidity transfer information based on the area information of the target space, the building type, and the material of the stored object, so as to determine the length information of the linked list based on the temperature and humidity transfer information, and then establish a target linked list based on the length information of the linked list, thereby enabling more accurate determination of the temperature change rate data and the humidity change rate data.

[0126] It can be seen that in the embodiments of the present disclosure, when determining the temperature change rate and the humidity change rate, not only the area information and the building type of the target space are considered, but also the characteristic information of the material of the object stored in the target space for transmitting temperature and humidity information is considered to comprehensively determine the length information of the linked list, so that the temperature change rate and the humidity change rate can be determined more accurately, and thus the accuracy of fire detection can be improved.

[0127] Step B: Screen and process the temperature data and humidity data stored in the target linked list to obtain the processed temperature data and the processed humidity data.

[0128] In the embodiments of the present disclosure, the electronic device can inspect the temperature data and humidity data stored in the target linked list, screen out the non-standard data, and obtain the processed temperature data and the processed humidity data. Among them, the non-standard data is, for example, a negative value, or an unconventional temperature value (such as 2000 degrees) or humidity value, etc., which are not limited in the embodiments of the present disclosure.

[0129] Step C: Process the processed temperature data and the processed humidity data respectively to obtain the temperature change rate data and the humidity change rate data.

[0130] In the embodiments of the present disclosure, the electronic device can determine the first difference between the last temperature data and the first temperature data in the target linked list; obtain the temperature change rate data according to the first difference and the target length of the target linked list; and determine the second difference between the last humidity data and the first humidity data in the target linked list; obtain the humidity change rate data according to the second difference and the target length of the target linked list.

[0131] For example, if the last temperature data in the target linked list is 151 and the first temperature data is 156, the first difference of 5 can be determined, and the target length of the target linked list is 60, then the temperature change rate data of 0.083 can be obtained. And if the last humidity data in the target linked list is 530 and the first humidity data is 536, the second difference of -6 can be determined, taking its absolute value, and the target length of the target linked list is 60, then the humidity change rate data of 0.1 can be obtained.

[0132] In an embodiment of the present disclosure, when the target linked list includes a first linked list and a second linked list, the electronic device may determine a first difference between the last temperature data and the first temperature data in the first linked list; obtain temperature change rate data according to the first difference and the target length of the first linked list; and determine a second difference between the last humidity data and the first humidity data in the second linked list; obtain humidity change rate data according to the second difference and the target length of the second linked list.

[0133] For example, if the last temperature data in the first linked list is 143 and the first temperature data is 147, the first difference of 4 can be determined. If the target length of the target linked list is 60, the temperature change rate data of 0.067 can be obtained. Also, if the last humidity data in the target linked list is 430 and the first humidity data is 436, the second difference of -6 can be determined. Taking the absolute value and with the target length of the target linked list being 60, the humidity change rate data of 0.1 can be obtained.

[0134] Step 202: Determine the carbon monoxide concentration data and the smoke concentration data of the target space within a preset time period.

[0135] In an embodiment of the present disclosure, the electronic device may also receive the carbon monoxide concentration data and the smoke concentration data of the target space within a preset time period sent by the acquisition device.

[0136] Optionally, the acquisition device for collecting carbon monoxide concentration data may be, for example, a carbon monoxide detector, an intelligent fixed carbon monoxide detector, etc., which are not limited in this embodiment of the present disclosure. For example, the electronic device may receive the carbon monoxide concentration data of the target space within a preset time period collected by the carbon monoxide detector, or may receive the carbon monoxide concentration data of the target space within a preset time period collected by the intelligent fixed carbon monoxide detector.

[0137] Optionally, the acquisition device for collecting smoke concentration data may be, for example, a smoke detector, a flue gas and dust particulate concentration tester, etc., which are not limited in this embodiment of the present disclosure. For example, the electronic device may receive the smoke concentration data of the target space within a preset time period collected by the smoke detector. Among them, the smoke detector may be, for example, an ionization smoke detector, an optoelectronic smoke detector, an infrared beam smoke detector, etc., which are not limited in this embodiment of the present disclosure.

[0138] Step 203: Determine the fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data.

[0139] In the embodiments of the present disclosure, the electronic device may input the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data into a preset fuzzy inference system to obtain a predicted result value, and then determine the fire detection information of the target space within the first time period according to the predicted result value and the preset fuzzy rules.

[0140] In the embodiments of the present disclosure, the membership functions and preset fuzzy rules of the preset fuzzy inference system may be set correspondingly based on actual implementation. Among them, the membership function is a function used to describe the degree to which an element in a fuzzy set belongs to the set. It maps each element in the domain of discourse to a real number between 0 and 1, and this real number represents the membership degree of the element to the fuzzy set. For example, the membership function is a triangular membership function. The preset fuzzy rules are used to describe the fuzzy relationship between the input variables and the output variables.

[0141] In the embodiments of the present disclosure, the electronic device may determine the first value, second value, third value, and fourth value according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, smoke concentration data, and their respective membership functions; then, according to the first value, second value, third value, fourth value, and the graph of the output membership degree, obtain the target graph, and thus determine the predicted result value according to the centroid of the target graph.

[0142] Optionally, the electronic device may obtain the first value according to the temperature change rate data and the first membership function; obtain the second value according to the humidity change rate data and the second membership function; obtain the third value according to the carbon monoxide concentration data and the third membership function, and obtain the fourth value according to the smoke concentration data and the fourth membership function; wherein, the first membership function, second membership function, third membership function, and fourth membership function are all triangular membership functions.

[0143] In the specific implementation process, the electronic device may substitute the carbon monoxide concentration data, smoke concentration data, temperature change rate data, and humidity change rate data into their respective membership functions to obtain the first value, second value, third value, and fourth value. Since it is an "and" relationship in the preset fuzzy rules, the smaller membership degree is taken to cut the graph of the output membership degree to obtain the output of this rule, and so on. Finally, the graphs of the outputs of 12 rules are obtained, and finally the 12 graphs are stacked together to obtain a final graph, that is, the target graph. Finally, an anti-fuzzy operation is performed to calculate the centroid of the graph to obtain the final predicted result information.

[0144] For example, assume that the temperature change rate data is 0.05, and refer to Figure 3As shown in the schematic diagram of the first membership function, it can be determined that 0.05 is within the triangular membership function region corresponding to the small risk of the temperature change rate. Assuming that the humidity change rate is 0.06, and referring to Figure 4 As shown in the schematic diagram of the second membership function, it is determined that 0.06 is within the triangular membership function region corresponding to the large risk of the humidity change rate. Assuming that the carbon monoxide concentration is 25, and referring to Figure 5 As shown in the schematic diagram of the third membership function, it can be determined that 25 is within the triangular membership function region corresponding to the large risk of the carbon monoxide concentration. Assuming that the smoke concentration is 250, and referring to Figure 6 As shown in the schematic diagram of the fourth membership function, it can be determined that 250 is within the triangular membership function region corresponding to the large risk of the smoke concentration. And inputting 0.05, 0.06, 25, and 250 into the preset fuzzy inference system, the preset fuzzy inference system can refer to Figure 7 the process shown in Figure 8 the schematic diagram of the prediction membership function described above, and determine that it is within the triangular membership function region corresponding to the large risk of the fire detection information. In this way, according to Figure 9 the preset fuzzy rules shown, where the preset fuzzy rules are, for example, that the temperature change rate corresponds to a small risk, the humidity change rate corresponds to a large risk, the carbon monoxide concentration corresponds to a large risk, and the smoke concentration corresponds to a large risk, then it is determined that the prediction result information is a large risk, so that it can be determined that the fire detection information in the target space within the preset time period is a large risk.

[0145] It can be seen that the entire detection process of fire detection in the embodiments of the present disclosure is automated, thereby improving the fire detection efficiency to a certain extent. In addition, since the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data are combined, it is possible to more accurately determine whether there is a fire in the target space within the preset time period, avoiding the situation of false detection of fire caused by abnormal temperature changes or abnormal humidity changes that are not caused by fire (such as abnormal temperature and humidity changes caused by seasons or weather changes), thereby greatly improving the fire detection accuracy.

[0146] An exemplary embodiment of the present disclosure also provides a fire detection device. Referring to Figure 10 as shown, the fire detection device 1000 includes the following program units:

[0147] An obtaining unit 1001, configured to determine the temperature data and humidity data of the target space within a preset time period, and respectively process the temperature data and humidity data of the target space to obtain temperature change rate data and humidity change rate data;

[0148] A determination unit 1002, configured to determine carbon monoxide concentration data and smoke concentration data of a target space within the preset time period;

[0149] A detection unit 1003, configured to determine fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data.

[0150] In a possible implementation manner, the obtaining unit 1001 is specifically configured to:

[0151] Establish a target linked list, and store the temperature data and humidity data of the target space based on the target linked list;

[0152] Perform screening processing on the temperature data and humidity data stored in the target linked list to obtain processed temperature data and processed humidity data;

[0153] Process the processed temperature data and the processed humidity data respectively to obtain temperature change rate data and humidity change rate data.

[0154] In a possible implementation manner, the obtaining unit 1001 is specifically configured to:

[0155] Determine the temperature and humidity transfer information of the target space;

[0156] Determine the target length of the linked list according to the temperature and humidity transfer information, and establish a linked list with the target length as the target linked list.

[0157] In a possible implementation manner, the obtaining unit 1001 is specifically configured to:

[0158] Determine a first difference between the last temperature data and the first temperature data in the target linked list;

[0159] Obtain the temperature change rate data according to the first difference and the target length of the target linked list; and,

[0160] Determine a second difference between the last humidity data and the first humidity data in the target linked list;

[0161] Obtain the humidity change rate data according to the second difference and the target length of the target linked list.

[0162] In a possible implementation manner, the detection unit 1003 is specifically configured to:

[0163] Input the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data into a preset fuzzy inference system to obtain a predicted result value;

[0164] Determine the fire detection information of the target space within the preset time period according to the predicted result value and the preset fuzzy rules.

[0165] In a possible implementation manner, the detection unit 1003 is specifically configured to:

[0166] Determine a first value, a second value, a third value, and a fourth value according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, the smoke concentration data, and their respective membership functions;

[0167] Obtain a target graph according to the first value, the second value, the third value, the fourth value, and the graph of the output membership degree;

[0168] Determine the predicted result value according to the centroid of the target graph.

[0169] In a possible implementation manner, the detection unit 1003 is specifically configured to:

[0170] Obtain a first value according to the temperature change rate data and the first membership function;

[0171] Obtain a second value according to the humidity change rate data and the second membership function;

[0172] Obtain a third value according to the carbon monoxide concentration data and the third membership function;

[0173] Obtain a fourth value according to the smoke concentration data and the fourth membership function;

[0174] Wherein, the first membership function, the second membership function, the third membership function, and the fourth membership function are all triangular membership functions.

[0175] The specific details of each part in the above device have been described in detail in the implementation manner of the method part. The details not disclosed can be seen in the implementation manner content of the method part, so they will not be repeated here.

[0176] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the exemplary implementation manner of the present disclosure, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0177] Exemplary embodiments of the present disclosure also provide a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned fire detection method is implemented.

[0178] In one embodiment, the computer program product may be a tangible product containing the computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium may be a storage medium based on signals such as electricity, magnetism, light, electromagnetic, infrared, etc., including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, mechanical hard disk (HDD), solid state drive (SSD), and so on. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing the computer program, such as read-only memory, Nand Flash, etc.

[0179] In one embodiment, the computer program product may be an intangible product containing the computer program. Exemplarily, the computer program product may be implemented as a virtual digital product, such as an executable file storing the computer program, an installation package and other digital files.

[0180] The code of the computer program can be written in one or more programming languages. Programming languages such as C, Java, C++, etc. The program code can be executed entirely on the user's computing device, or partially on the user's computing device, or executed as an independent software package, or partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (for example, through an Internet connection provided by an operator).

[0181] A computer program can be carried or transmitted by signals such as electricity, magnetism, light, electromagnetic, infrared, etc. An electronic device can convert the signal carrying the computer program into a digital signal and then run the computer program. When the computer program runs on the electronic device, its code is used to cause the electronic device to execute (more specifically, to cause the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure. For example, the above fire detection method can be executed, which includes the following steps: Step 201: Determine the temperature data and humidity data of the target space within a preset time period, and process the temperature data and humidity data of the target space respectively to obtain the temperature change rate data and humidity change rate data; Step 202: Determine the carbon monoxide concentration data and smoke concentration data of the target space within a preset time period; Step 203: Determine the fire detection information of the target space within the preset time period according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data.

[0182] By implementing the above method steps through a computer program, the temperature data and humidity data of the target space within a preset time period can be determined, and the temperature data and humidity data of the target space can be processed respectively to obtain the temperature change rate data and humidity change rate data; and, the carbon monoxide concentration data and smoke concentration data of the target space within a preset time period can be determined, and then according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data, the fire detection information of the target space within the preset time period can be determined. It can be seen that the entire detection process of fire detection in the embodiments of the present disclosure is automated, thereby improving the fire detection efficiency to a certain extent. In addition, since the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data are combined, it is possible to more accurately determine whether there is a fire in the target space within a preset time period, avoiding the false detection situation where a non-fire temperature anomaly or humidity anomaly is detected as a fire, thus greatly improving the fire detection accuracy.

[0183] An exemplary embodiment of the present disclosure further provides an electronic device, which may include a processor and a memory. The memory stores executable instructions of the processor, such as a computer program. The processor executes the executable instructions to execute the method steps of various exemplary embodiments of the present disclosure.

[0184] Next, refer to Figure 11 , and an electronic device will be exemplarily described in the form of a general computing device. It should be understood that Figure 11 the electronic device 1100 shown is only an example and should not impose limitations on the functions and usage scope of the embodiments of the present disclosure.

[0185] Such as Figure 11As shown, the electronic device 1100 may include: a processor 1110, a memory 1120, a bus 1130, an I / O (input / output) interface 1140, a network adapter 1150, and a display 1180.

[0186] The memory 1120 may include volatile memory, such as RAM 1121 and a cache unit 1122, and may also include non-volatile memory, such as ROM 1123. The memory 1120 may further include one or more program modules 1124. Such program modules 1124 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include the implementation of a network environment. For example, the program module 424 may include each unit in the above device.

[0187] The processor 1110 may include one or more processing units. For example, the processor 410 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit), etc.

[0188] The processor 1110 can be used to execute executable instructions stored in the memory 1120. For example, it can execute the above fire detection method, which includes the following steps: Step 201: Determine the temperature data and humidity data of the target space within a preset time period, and process the temperature data and humidity data of the target space respectively to obtain temperature change rate data and humidity change rate data; Step 202: Determine the carbon monoxide concentration data and smoke concentration data of the target space within a preset time period; Step 203: Determine the fire detection information of the target space within a preset time period according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data.

[0189] By executing the above method steps through the processor 1110, the temperature data and humidity data of the target space within a preset time period can be determined, and the temperature data and humidity data of the target space are respectively processed to obtain the temperature change rate data and humidity change rate data; and, the carbon monoxide concentration data and smoke concentration data of the target space within the preset time period are determined, and then according to the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data, the fire detection information of the target space within the preset time period is determined. It can be seen that the entire detection process of fire detection in the embodiments of the present disclosure is automated, thereby improving the fire detection efficiency to a certain extent. In addition, since the temperature change rate data, humidity change rate data, carbon monoxide concentration data, and smoke concentration data are combined, it is possible to more accurately determine whether there is a fire in the target space within the preset time period, avoiding the situation of false detection of a fire due to abnormal temperature changes or abnormal humidity changes that are not caused by a fire, thereby greatly improving the fire detection accuracy. The bus 1130 is used to implement the connection between different components of the electronic device 1100, and may include a data bus, an address bus, and a control bus.

[0190] The electronic device 1100 can communicate with one or more external devices 1200 (such as a keyboard, a mouse, an external controller, etc.) through the I / O interface 1140.

[0191] The electronic device 1100 can communicate with one or more networks through the network adapter 1150. For example, the network adapter 1150 can provide mobile communication solutions such as 3G / 4G / 5G, or provide wireless communication solutions such as wireless local area network, Bluetooth, and near field communication. The network adapter 1150 can communicate with other modules of the electronic device 1100 through the bus 1130.

[0192] The electronic device 1100 can display a graphical user interface, such as a fire warning message, etc., through the display 1180.

[0193] Although Figure 11 not shown in the figure, other hardware and / or software modules can also be set in the electronic device 1100, including but not limited to: microcode, device driver, redundant processor, external disk drive array, RAID system, tape drive, and data backup storage system, etc.

[0194] As can be seen from the above, the technical solution of the present disclosure can be implemented as a method, a device, a system, a computer program product, a storage medium, an electronic device, etc. Those skilled in the art can understand that various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation manner, a complete software implementation manner (including firmware, microcode, etc.), or an implementation manner combining hardware and software aspects, such as can be respectively referred to as "circuit", "module", or "system".

[0195] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily think of other embodiments based on the specific embodiments provided by the present disclosure. Therefore, the specific embodiments provided by the present disclosure are only exemplary, and the scope and spirit of the present disclosure are pointed out by the claims, and should cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include the common general knowledge or conventional technical means in the technical field not disclosed by the present disclosure.

Claims

1. A fire detection method, characterized in that: The method comprises: Determine the temperature data and humidity data of the target space within a preset time period, and process the temperature data and humidity data of the target space respectively to obtain temperature change rate data and humidity change rate data; Determine carbon monoxide concentration data and smoke concentration data of the target space within the preset time period; Fire detection information of the target space within the preset time period is determined according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data.

2. The method according to claim 1, characterized in that The temperature data and humidity data of the target space are processed respectively to obtain temperature change rate data and humidity change rate data, including: Establishing a target linked list, and storing the temperature data and humidity data of the target space based on the target linked list; Screening the temperature data and humidity data stored in the target linked list to obtain processed temperature data and processed humidity data; The processed temperature data and the processed humidity data are processed respectively to obtain temperature change rate data and humidity change rate data.

3. The method according to claim 2, characterized in that Create a target list, including: Determining temperature and humidity transfer information of the target space; According to the temperature and humidity transmission information, the target length of the linked list is determined, and a linked list of the target length is established as the target linked list.

4. The method according to claim 3, characterized in that The processed temperature data and the processed humidity data are processed respectively to obtain temperature change rate data and humidity change rate data, including: Determine a first difference between the last temperature data and the first temperature data in the target linked list; According to the first difference and the target length of the target linked list, obtaining the temperature change rate data; and, Determine a second difference between the last humidity data and the first humidity data in the target linked list; The humidity change rate data is obtained according to the second difference and the target length of the target linked list.

5. The method according to any one of claims 1 to 4, characterized in that: Determining fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data, including: Inputting the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data and the smoke concentration data into a preset fuzzy inference system to obtain a prediction result value; The fire detection information of the target space within the preset time period is determined according to the prediction result value and the preset fuzzy rule.

6. The method according to claim 5, characterized in that Inputting the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data into a preset fuzzy inference system to obtain a prediction result value, including: Determine a first value, a second value, a third value, and a fourth value according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data and their corresponding membership functions; Obtain a target graph according to the first value, the second value, the third value, the fourth value and the graph of the output membership; The predicted result value is determined according to the center of gravity of the target graphic.

7. The method according to claim 6, characterized in that Determining a first value, a second value, a third value, and a fourth value according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data, and the smoke concentration data and their corresponding membership functions includes: Obtaining a first value according to the temperature change rate data and a first membership function; Obtain a second value according to the humidity change rate data and a second membership function; Obtaining a third value according to the carbon monoxide concentration data and a third membership function; Obtaining a fourth value according to the smoke concentration data and a fourth membership function; The first membership function, the second membership function, the third membership function and the fourth membership function are all triangular membership functions.

8. A fire detection device, characterized in that: The device comprises: an obtaining unit, used to determine the temperature data and humidity data of the target space within a preset time period, and process the temperature data and humidity data of the target space respectively to obtain temperature change rate data and humidity change rate data; A determination unit, used to determine carbon monoxide concentration data and smoke concentration data of the target space within the preset time period; The detection unit is used to determine the fire detection information of the target space within the preset time period according to the temperature change rate data, the humidity change rate data, the carbon monoxide concentration data and the smoke concentration data.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: processor; A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

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