Fire-fighting alarm receiving and handling digital management system

Abstract

The invention discloses a fire-fighting alarm receiving and processing digital management system, and the system obtains real-time environment parameter data through employing a distributed sensor, carries out the data preprocessing of the real-time environment parameter data, and obtains target environment parameter data. Inputting the target environment parameter data into a preset early warning identification model for identification to obtain an accident state type; analyzing the accident state type by using a path planning algorithm to obtain fire-fighting vehicle planning information; analyzing the accident state type by using a fire-fighting resource allocation model to obtain firefighter allocation information; and according to the fire-fighting vehicle planning information and the firefighter distribution information, unified scheduling of vehicles and persons is carried out, and real-time scheduling adjustment is carried out according to real-time conditions. The optimal path can be planned for the fire-fighting vehicle in a short time, resources are reasonably allocated, the police time is shortened, and the alarm response speed is increased.

Description

Technical Field

[0001] The invention relates to the technical field of fire management, in particular to a digital management system for fire alarm reception and handling. Background Art

[0002] In the traditional fire alarm response work, there are problems such as untimely and inaccurate information transmission, unreasonable resource scheduling, and lack of scientific and effective means for alarm analysis and processing. For example, during the alarm response process, key alarm information may be missed due to manual recording errors, and it is impossible to quickly and accurately obtain fire resource information around the accident site during the alarm response, making it difficult to achieve efficient command and dispatch. At the same time, there is a lack of in-depth analysis and utilization of a large amount of alarm response data, which cannot provide strong support for fire decision-making. With the development of information technology, digital management systems have become a key requirement for improving the efficiency and quality of fire alarm response. Therefore, how to use scientific means to record fire conditions and arrange appropriate firefighters and fire trucks is a technical problem that needs to be solved at this stage. Summary of the invention

[0003] The purpose of the present invention is to solve the above problems and to design a digital management system for fire alarm reception and handling.

[0004] To achieve the above-mentioned purpose, the technical solution of the present invention is that, further, in the above-mentioned digital management system for fire alarm reception and handling, the digital management system for fire alarm reception and handling includes a real-time monitoring module, an accident identification module, a fire vehicle planning module, a fire resource allocation module, and a resource deployment module:

[0005] A real-time monitoring module is used to obtain real-time environmental parameter data using distributed sensors, and perform data preprocessing on the real-time environmental parameter data to obtain target environmental parameter data;

[0006] An accident identification module is used to input the target environmental parameter data into a preset early warning identification model for identification to obtain the accident state type;

[0007] A firefighting vehicle planning module is used to analyze the accident state type using a path planning algorithm to obtain firefighting vehicle planning information;

[0008] A fire resource allocation module, used to analyze the accident state type using a fire resource allocation model to obtain firefighter allocation information;

[0009] The resource allocation module is used to uniformly dispatch vehicles and personnel according to the fire vehicle planning information and the fire personnel allocation information, and to make real-time dispatch adjustments according to real-time conditions.

[0010] Furthermore, in the above-mentioned digital management system for fire alarm reception and handling, the real-time monitoring module includes a data acquisition submodule, a data processing submodule, a data fusion submodule, and a standardization processing submodule:

[0011] A data acquisition submodule is used to acquire real-time environmental parameter data using distributed sensors, wherein the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data;

[0012] A data processing submodule is used to process the ambient temperature data by using a median filtering algorithm to remove abnormal fluctuation values ​​caused by a short-term sensor failure or environmental interference, and to remove unreasonable extremely high and extremely low values ​​in the ambient smoke data by using a threshold judgment method;

[0013] The data fusion submodule is used to fuse the data of multiple temperature sensors at similar locations by weighted average method, and to judge the environmental smoke data and environmental gas data by the data fusion method based on evidence theory to obtain initial environmental parameter data;

[0014] The standardization processing submodule is used to perform data standardization processing on the initial environmental parameter data to obtain target environmental parameter data.

[0015] Furthermore, in the above-mentioned digital management system for fire alarm reception and handling, the accident identification module includes an establishment submodule, an input submodule, an extraction submodule, and a processing submodule:

[0016] Establish a submodule to establish a warning recognition model based on the combination of CNN convolutional neural network and RNN loop neural network;

[0017] An input submodule, used for inputting the target environmental parameter data into a preset early warning recognition model for recognition;

[0018] An extraction submodule, used to extract spatial features in the target environment parameter data using the CNN convolutional neural network;

[0019] The processing submodule is used to use the RNN loop neural network to process the time series data in the target environmental parameter data to obtain the accident state type; the accident state type at least includes normal state, initial fire state, fire development state, and explosion danger state.

[0020] Furthermore, in the above-mentioned digital management system for fire alarm reception and handling, the fire vehicle planning module includes an acquisition submodule, an adjustment submodule, an optimization submodule, and a obtaining submodule:

[0021] The acquisition submodule uses the A* algorithm based on heuristic search as the core algorithm for path planning, introduces a real-time traffic data update mechanism, and acquires road congestion and traffic accident information in real time;

[0022] An adjustment submodule, used to dynamically adjust the cost function in the A* algorithm according to the real-time traffic conditions to obtain the first planned path information;

[0023] An optimization submodule, configured to constrain and optimize the first planned path information according to the size and turning radius of the fire truck to obtain second planned path information;

[0024] A submodule is obtained, which is used to obtain multiple candidate second planned path information from each fire station to the accident scene, evaluate and sort the path according to path length, estimated driving time, and traffic conditions, select the optimal path as the planned driving route of the fire truck, and obtain the fire truck planning information, which at least includes the fire station, driving path, and estimated arrival time.

[0025] Furthermore, in the above-mentioned digital management system for fire alarm reception and handling, the fire resource allocation module includes a building submodule, a training submodule, and an analysis submodule:

[0026] Establish a submodule for establishing a fire resource allocation model based on a linear programming algorithm, and set the objective function to maximize fire rescue efficiency and minimize accident losses;

[0027] A training submodule, used for training and adjusting parameters of the fire resource allocation model through historical fire rescue case data and relevant resource configuration information;

[0028] The analysis submodule is used to analyze the accident status type using a fire resource allocation model to obtain firefighter allocation information, which at least includes the number of personnel, the number of equipment, the number of people in the fire extinguishing team, the number of people in the rescue team, and the number of people in the logistics support team.

[0029] Furthermore, in the above-mentioned digital management system for fire alarm reception and handling, the resource allocation module includes an instruction submodule, an acquisition submodule, a calculation submodule, and a scheduling submodule:

[0030] The command submodule is used to send initial dispatching instructions to fire stations and firefighters according to the fire vehicle planning information and firefighter allocation information;

[0031] An acquisition submodule is used to acquire real-time fire conditions, which at least include sudden road congestion, expansion of the accident scene, and newly trapped persons;

[0032] The calculation submodule is used to calculate a new path for the scheduling plan according to the real-time feedback information and generate a target scheduling instruction according to the new path;

[0033] The dispatching submodule is used to perform target dispatching of fire trucks and firefighters according to the target dispatching instruction.

[0034] Furthermore, a method for implementing a digital management system for fire alarm reception and handling is characterized in that the method comprises the following steps:

[0035] Using distributed sensors to obtain real-time environmental parameter data, and performing data preprocessing on the real-time environmental parameter data to obtain target environmental parameter data;

[0036] Inputting the target environmental parameter data into a preset early warning recognition model for recognition to obtain the accident state type;

[0037] Analyze the accident state type using a path planning algorithm to obtain firefighting vehicle planning information;

[0038] Analyze the accident status type using a fire resource allocation model to obtain firefighter allocation information;

[0039] The vehicles and personnel are uniformly dispatched according to the firefighting vehicle planning information and the firefighting personnel allocation information, and real-time dispatching adjustments are made according to the real-time situation.

[0040] Furthermore, a method for implementing a digital management system for fire alarm reception and handling is characterized in that the method comprises the following steps:

[0041] Using distributed sensors to obtain real-time environmental parameter data, the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data;

[0042] The ambient temperature data is processed by a median filtering algorithm to remove abnormal fluctuation values ​​caused by a short-term sensor failure or environmental interference, and an unreasonable extremely high and extremely low values ​​in the ambient smoke data are removed by a threshold judgment method;

[0043] The data of multiple temperature sensors at similar locations are fused by weighted average method, and the environmental smoke data and environmental gas data are judged by the data fusion method based on evidence theory to obtain initial environmental parameter data;

[0044] The initial environmental parameter data is subjected to data standardization processing to obtain target environmental parameter data.

[0045] Furthermore, a method for implementing a digital management system for fire alarm reception and handling is characterized in that the method comprises the following steps:

[0046] A warning recognition model is established based on the combination of CNN convolutional neural network and RNN loop neural network;

[0047] Inputting the target environmental parameter data into a preset early warning recognition model for recognition;

[0048] Utilizing the CNN convolutional neural network to extract spatial features from the target environment parameter data;

[0049] The RNN loop neural network is used to process the time series data in the target environmental parameter data to obtain the accident state type; the accident state type at least includes a normal state, an initial fire state, a fire development state, and an explosion danger state.

[0050] The beneficial effect is that the real-time monitoring module is used to obtain real-time environmental parameter data by using distributed sensors, and the real-time environmental parameter data is preprocessed to obtain target environmental parameter data; the accident identification module is used to input the target environmental parameter data into a preset early warning identification model for identification to obtain the accident state type; the fire vehicle planning module is used to analyze the accident state type by using a path planning algorithm to obtain fire vehicle planning information; the fire resource allocation module is used to analyze the accident state type by using a fire resource allocation model to obtain fire personnel allocation information; the resource allocation module is used to uniformly dispatch vehicles and personnel according to the fire vehicle planning information and the fire personnel allocation information, and to make real-time scheduling adjustments according to real-time conditions. The best path can be planned for the fire vehicle in a short time and resources can be reasonably allocated, which shortens the alarm time and improves the alarm response speed. According to the data analysis results and the actual alarm needs, the fire resources are reasonably allocated to improve the utilization rate of resources and avoid waste and idleness of resources. When facing various sudden fire accidents, it can respond quickly and accurately, reasonably allocate resources, and improve emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the following detailed description of the preferred embodiment.The drawings are only for the purpose of illustrating the preferred embodiments and are not to be construed as limiting the invention.

[0052] Figure 1 This is a schematic diagram of a first embodiment of a digital management system for fire alarm reception and handling in an embodiment of the present invention;

[0053] Figure 2This is a schematic diagram of a second embodiment of a digital management system for fire alarm reception and handling in an embodiment of the present invention;

[0054] Figure 3 It is a schematic diagram of a third embodiment of a digital management system for fire alarm reception and handling in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0056] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0057] The present invention will be described in detail below in conjunction with the accompanying drawings. Figure 1 As shown, a digital management system for fire alarm reception and handling, the energy storage operation and maintenance plan formulation method includes a real-time monitoring module, an accident identification module, a fire vehicle planning module, a fire resource allocation module, and a resource deployment module:

[0058] A real-time monitoring module is used to obtain real-time environmental parameter data using distributed sensors, perform data preprocessing on the real-time environmental parameter data, and obtain target environmental parameter data;

[0059] Specifically, this embodiment also includes:

[0060] The data acquisition submodule is used to acquire real-time environmental parameter data using distributed sensors, where the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data;

[0061] The data processing submodule is used to process the ambient temperature data through the median filtering algorithm to remove abnormal fluctuation values ​​caused by short-term sensor failure or environmental interference, and to use the threshold judgment method to remove unreasonable extremely high and extremely low values ​​in the ambient smoke data;

[0062] The data fusion submodule is used to fuse the data of multiple temperature sensors at similar locations through the weighted average method, and to judge the environmental smoke data and environmental gas data based on the data fusion method of evidence theory to obtain the initial environmental parameter data;

[0063] The standardization processing submodule is used to perform data standardization processing on the initial environmental parameter data to obtain the target environmental parameter data.

[0064] The accident identification module is used to input the target environmental parameter data into the preset early warning identification model for identification to obtain the accident status type;

[0065] Specifically, this embodiment also includes:

[0066] Establish a submodule to establish a warning recognition model based on the combination of CNN convolutional neural network and RNN loop neural network;

[0067] An input submodule is used to input the target environmental parameter data into a preset early warning recognition model for recognition;

[0068] The extraction submodule is used to extract spatial features from the target environment parameter data using a CNN convolutional neural network;

[0069] The processing submodule is used to use the RNN loop neural network to process the time series data in the target environmental parameter data to obtain the accident state type; the accident state type at least includes normal state, initial fire state, fire development state, and explosion danger state.

[0070] The fire vehicle planning module is used to analyze the accident status type using the path planning algorithm to obtain the fire vehicle planning information;

[0071] Specifically, this embodiment also includes:

[0072] The acquisition submodule uses the A* algorithm based on heuristic search as the core algorithm for path planning, introduces a real-time traffic data update mechanism, and acquires road congestion and traffic accident information in real time;

[0073] An adjustment submodule, used to dynamically adjust the cost function in the A* algorithm according to the real-time traffic conditions to obtain the first planned path information;

[0074] An optimization submodule, used for constraining and optimizing the first planned path information according to the size and turning radius of the fire truck to obtain the second planned path information;

[0075] A submodule is obtained, which is used to obtain multiple candidate second planned path information from each fire station to the accident scene, evaluate and sort the path according to path length, estimated driving time, and traffic conditions, select the optimal path as the planned driving route of the fire truck, and obtain the fire truck planning information. The fire truck planning information at least includes the fire station, driving path, and estimated arrival time.

[0076] Specifically, this embodiment also includes: path planning algorithm selection and optimization

[0077] The A* algorithm based on heuristic search is selected as the core algorithm for path planning. This algorithm combines the topological structure of the map with real-time traffic information and can quickly find the optimal path from the fire station to the accident site. In terms of map representation, raster maps or vector maps are used to model the urban road network and digitally store road node and section information.

[0078] Introduce a real-time traffic data update mechanism, connect with the information system of the transportation department, and obtain real-time information such as road congestion and traffic accidents. According to the real-time traffic conditions, dynamically adjust the cost function in the A* algorithm. For example, when the road is congested, increase the cost weight of the congested section so that the algorithm gives priority to relatively unobstructed roads. At the same time, consider the special driving requirements of fire trucks, such as the size of the vehicle, the turning radius, etc., constrain and optimize the path to ensure that the planned path is both fast and suitable for fire trucks.

[0079] Firefighting vehicle planning information generation process

[0080] After receiving the accident status type and accident location information output by the accident identification module, the fire vehicle planning module first determines the location of the accident scene and the surrounding fire stations on the map. Then, using each fire station as the starting point, the optimized A* algorithm is used to search for the optimal path to the accident scene.

[0081] For each candidate path from the fire station to the accident site, factors such as path length, estimated travel time, and traffic conditions are comprehensively considered for evaluation and ranking. The optimal path is selected as the planned driving route for the fire truck, and fire truck planning information is generated, including the departure fire station, driving path, and estimated arrival time.

[0082] For example, during the planning process, if a route is found to be shorter but has a longer estimated travel time due to traffic congestion, while another route is slightly longer but has smoother traffic, the algorithm will select the latter as the optimal route based on a comprehensive evaluation and include the relevant information in the fire truck planning information.

[0083] The fire resource allocation module is used to analyze the accident status type using the fire resource allocation model to obtain the fire personnel allocation information;

[0084] Specifically, this embodiment also includes:

[0085] Establish a submodule for establishing a fire resource allocation model based on a linear programming algorithm, and set the objective function to maximize fire rescue efficiency and minimize accident losses;

[0086] The training submodule is used to train and adjust the parameters of the fire resource allocation model through historical fire rescue case data and related resource configuration information;

[0087] The analysis submodule is used to analyze the accident status type using the fire resource allocation model to obtain firefighter allocation information, which at least includes the number of personnel, the number of equipment, the number of people in the fire extinguishing team, the number of people in the rescue team, and the number of people in the logistics support team.

[0088] Specifically, this embodiment also includes:

[0089] Construction of fire resource allocation model

[0090] A fire resource allocation model based on linear programming was constructed. The model takes the severity and type of the accident (such as fire, explosion, etc.), the surrounding environment of the accident site (such as building structure, density of people, etc.), and the available fire resources (including the number and skill level of firefighters, the type and number of fire trucks, the type and number of fire equipment, etc.) as input variables.

[0091] The objective function is set to maximize the efficiency of firefighting and rescue or minimize the loss of accidents. For example, the corresponding objective function is constructed with the goal of controlling the fire and rescuing trapped people in the shortest time. At the same time, various constraints are considered, such as the working time limit of firefighters, the water carrying capacity and fire extinguishing agent capacity limit of fire trucks, and the adaptability of different types of firefighting equipment.

[0092] By collecting a large amount of historical fire rescue case data and related resource allocation information, the model is trained and parameters are adjusted so that the model can reasonably allocate fire resources according to different accident situations.

[0093] Firefighter allocation information generation process

[0094] After the accident status type is input, the fire resource allocation model first evaluates the accident and determines the type and quantity of fire resources required. For example, for a fire accident, the number of firefighters required and the skill requirements are calculated based on factors such as the size of the fire, the type of burning material, and the area of ​​the building, such as whether firefighters are required to have high-altitude rescue skills and fire-fighting skill levels.

[0095] Then, combined with the currently available firefighter information, including the staffing of each fire station, the professional skills of the personnel, and the current task status, resource allocation optimization is performed through the model's solution algorithm.

[0096] Generate firefighter allocation information, including how many firefighters with what skills are deployed from which fire stations to the accident scene, as well as the specific task division of each firefighter (such as fire extinguishing team, rescue team, logistics support team, etc.).

[0097] For example, if the accident scene is a high-rise building fire and people are trapped, the model will assign firefighters with high-altitude rescue skills and rich firefighting experience to the scene, and clarify the tasks and responsibilities of each team to ensure the efficient implementation of the rescue work.

[0098] The resource allocation module is used to uniformly dispatch vehicles and personnel based on fire vehicle planning information and fire personnel allocation information, and to make real-time scheduling adjustments based on real-time conditions.

[0099] Specifically, this embodiment also includes:

[0100] The command submodule is used to send initial dispatching instructions to fire stations and firefighters according to the fire vehicle planning information and firefighter allocation information;

[0101] The acquisition submodule is used to obtain the real-time fire situation, which at least includes sudden road congestion, expansion of the accident scene, and newly trapped persons;

[0102] The calculation submodule is used to calculate a new path for the scheduling plan according to the real-time feedback information and generate a target scheduling instruction according to the new path;

[0103] The dispatch submodule is used to dispatch fire trucks and firefighters according to the target dispatch instructions.

[0104] The beneficial effect is that the real-time monitoring module is used to obtain real-time environmental parameter data by using distributed sensors, and the real-time environmental parameter data is preprocessed to obtain target environmental parameter data; the accident identification module is used to input the target environmental parameter data into the preset early warning identification model for identification to obtain the accident state type; the fire vehicle planning module is used to analyze the accident state type by using the path planning algorithm to obtain the fire vehicle planning information; the fire resource allocation module is used to analyze the accident state type by using the fire resource allocation model to obtain the fire personnel allocation information; the resource allocation module is used to uniformly dispatch vehicles and personnel according to the fire vehicle planning information and the fire personnel allocation information, and to make real-time scheduling adjustments according to the real-time situation. The best path can be planned for the fire vehicle in a short time and resources can be reasonably allocated, which shortens the alarm time and improves the alarm response speed. According to the data analysis results and the actual alarm needs, the fire resources are reasonably allocated to improve the utilization rate of resources and avoid waste and idleness of resources. In the face of various sudden fire accidents, it can respond quickly and accurately, reasonably allocate resources, and improve emergency response capabilities.

[0105] See also Figure 2 In a digital management system for fire alarm reception and handling, the real-time monitoring module includes a data acquisition submodule, a data processing submodule, a data fusion submodule, and a standardization processing submodule:

[0106] The data acquisition submodule is used to acquire real-time environmental parameter data using distributed sensors, where the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data;

[0107] The data processing submodule is used to process the ambient temperature data through the median filtering algorithm to remove abnormal fluctuation values ​​caused by short-term sensor failure or environmental interference, and to use the threshold judgment method to remove unreasonable extremely high and extremely low values ​​in the ambient smoke data;

[0108] The data fusion submodule is used to fuse the data of multiple temperature sensors at similar locations through the weighted average method, and to judge the environmental smoke data and environmental gas data based on the data fusion method of evidence theory to obtain the initial environmental parameter data;

[0109] The standardization processing submodule is used to perform data standardization processing on the initial environmental parameter data to obtain the target environmental parameter data.

[0110] See also Figure 3 In a digital management system for fire alarm reception and handling, the fire vehicle planning module includes an acquisition submodule, an adjustment submodule, an optimization submodule, and a obtaining submodule:

[0111] The acquisition submodule uses the A* algorithm based on heuristic search as the core algorithm for path planning, introduces a real-time traffic data update mechanism, and acquires road congestion and traffic accident information in real time;

[0112] An adjustment submodule, used to dynamically adjust the cost function in the A* algorithm according to the real-time traffic conditions to obtain the first planned path information;

[0113] An optimization submodule, used for constraining and optimizing the first planned path information according to the size and turning radius of the fire truck to obtain the second planned path information;

[0114] A submodule is obtained, which is used to obtain multiple candidate second planned path information from each fire station to the accident scene, evaluate and sort the path according to path length, estimated driving time, and traffic conditions, select the optimal path as the planned driving route of the fire truck, and obtain the fire truck planning information. The fire truck planning information at least includes the fire station, driving path, and estimated arrival time.

[0115] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A digital management system for fire alarm reception and handling, characterized in that: The fire alarm digital management system includes a real-time monitoring module, an accident identification module, a fire vehicle planning module, a fire resource allocation module, and a resource deployment module: A real-time monitoring module is used to obtain real-time environmental parameter data using distributed sensors, and perform data preprocessing on the real-time environmental parameter data to obtain target environmental parameter data; An accident identification module is used to input the target environmental parameter data into a preset early warning identification model for identification to obtain the accident state type; A firefighting vehicle planning module is used to analyze the accident state type using a path planning algorithm to obtain firefighting vehicle planning information; A fire resource allocation module, used to analyze the accident state type using a fire resource allocation model to obtain firefighter allocation information; The resource allocation module is used to uniformly dispatch vehicles and personnel according to the fire vehicle planning information and the fire personnel allocation information, and to make real-time dispatch adjustments according to real-time conditions.

2. A digital fire alarm management system as claimed in claim 1, characterized in that: The real-time monitoring module includes a data acquisition submodule, a data processing submodule, a data fusion submodule, and a standardization processing submodule: A data acquisition submodule is used to acquire real-time environmental parameter data using distributed sensors, wherein the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data; A data processing submodule is used to process the ambient temperature data by using a median filtering algorithm to remove abnormal fluctuation values ​​caused by a short-term sensor failure or environmental interference, and to remove unreasonable extremely high and extremely low values ​​in the ambient smoke data by using a threshold judgment method; The data fusion submodule is used to fuse the data of multiple temperature sensors at similar locations by weighted average method, and to judge the environmental smoke data and environmental gas data by the data fusion method based on evidence theory to obtain initial environmental parameter data; The standardization processing submodule is used to perform data standardization processing on the initial environmental parameter data to obtain target environmental parameter data.

3. A digital fire alarm management system as claimed in claim 1, characterized in that: The accident identification module includes a creation submodule, an input submodule, an extraction submodule, and a processing submodule: Establish a submodule to establish a warning recognition model based on the combination of CNN convolutional neural network and RNN loop neural network; An input submodule, used for inputting the target environmental parameter data into a preset early warning recognition model for recognition; An extraction submodule, used to extract spatial features in the target environment parameter data using the CNN convolutional neural network; The processing submodule is used to use the RNN loop neural network to process the time series data in the target environmental parameter data to obtain the accident state type; the accident state type at least includes normal state, initial fire state, fire development state, and explosion danger state.

4. A digital fire alarm management system as claimed in claim 1, characterized in that: The fire vehicle planning module includes an acquisition submodule, an adjustment submodule, an optimization submodule, and a obtaining submodule: The acquisition submodule uses the A* algorithm based on heuristic search as the core algorithm for path planning, introduces a real-time traffic data update mechanism, and acquires road congestion and traffic accident information in real time; An adjustment submodule, used to dynamically adjust the cost function in the A* algorithm according to the real-time traffic conditions to obtain the first planned path information; An optimization submodule, configured to constrain and optimize the first planned path information according to the size and turning radius of the fire truck to obtain second planned path information; A submodule is obtained, which is used to obtain multiple candidate second planned path information from each fire station to the accident scene, evaluate and sort the path according to path length, estimated driving time, and traffic conditions, select the optimal path as the planned driving route of the fire truck, and obtain the fire truck planning information, which at least includes the fire station, driving path, and estimated arrival time.

5. A digital fire alarm management system as claimed in claim 1, characterized in that: The fire resource allocation module includes a building submodule, a training submodule, and an analysis submodule: Establish a submodule for establishing a fire resource allocation model based on a linear programming algorithm, and set the objective function to maximize fire rescue efficiency and minimize accident losses; A training submodule, used for training and adjusting parameters of the fire resource allocation model through historical fire rescue case data and relevant resource configuration information; The analysis submodule is used to analyze the accident status type using a fire resource allocation model to obtain firefighter allocation information, which at least includes the number of personnel, the number of equipment, the number of people in the fire extinguishing team, the number of people in the rescue team, and the number of people in the logistics support team.

6. A digital fire alarm management system as claimed in claim 1, characterized in that: The resource allocation module includes an instruction submodule, an acquisition submodule, a calculation submodule, and a scheduling submodule: The command submodule is used to send initial dispatching instructions to fire stations and firefighters according to the fire vehicle planning information and firefighter allocation information; An acquisition submodule is used to acquire real-time fire conditions, which at least include sudden road congestion, expansion of the accident scene, and newly trapped persons; The calculation submodule is used to calculate a new path for the scheduling plan according to the real-time feedback information and generate a target scheduling instruction according to the new path; The dispatching submodule is used to perform target dispatching of fire trucks and firefighters according to the target dispatching instruction.

7. A method for implementing a digital management system for fire alarm reception and handling as claimed in claim 1, characterized in that: The method comprises the following steps: Using distributed sensors to obtain real-time environmental parameter data, performing data preprocessing on the real-time environmental parameter data, and obtaining target environmental parameter data; Inputting the target environmental parameter data into a preset early warning recognition model for recognition to obtain the accident state type; Analyze the accident state type using a path planning algorithm to obtain firefighting vehicle planning information; Analyze the accident status type using a fire resource allocation model to obtain firefighter allocation information; The vehicles and personnel are uniformly dispatched according to the firefighting vehicle planning information and the firefighting personnel allocation information, and real-time dispatching adjustments are made according to the real-time situation.

8. A method for implementing a digital management system for fire alarm reception and handling as claimed in claim 1, characterized in that: The method comprises the following steps: Using distributed sensors to obtain real-time environmental parameter data, the distributed sensors include at least a temperature sensor, a smoke sensor, and a gas sensor; the real-time environmental parameter data includes at least environmental temperature data, environmental smoke data, and environmental gas data; The ambient temperature data is processed by a median filtering algorithm to remove abnormal fluctuation values ​​caused by a short-term sensor failure or environmental interference, and an unreasonable extremely high and extremely low values ​​in the ambient smoke data are removed by a threshold judgment method; The data of multiple temperature sensors at similar locations are fused by weighted average method, and the environmental smoke data and environmental gas data are judged by the data fusion method based on evidence theory to obtain initial environmental parameter data; The initial environmental parameter data is subjected to data standardization processing to obtain target environmental parameter data.

9. A method for implementing a digital management system for fire alarm reception and handling as claimed in claim 1, characterized in that: The method comprises the following steps: A warning recognition model is established based on the combination of CNN convolutional neural network and RNN loop neural network; Inputting the target environmental parameter data into a preset early warning recognition model for recognition; Utilizing the CNN convolutional neural network to extract spatial features from the target environment parameter data; The RNN loop neural network is used to process the time series data in the target environmental parameter data to obtain the accident state type; the accident state type at least includes a normal state, an initial fire state, a fire development state, and an explosion danger state.

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