CN114462974A

CN114462974A - Intelligent fire-fighting full-chain prevention and control system and multi-source information fusion decision-making method

Info

Publication number: CN114462974A
Application number: CN202210130524.7A
Authority: CN
Inventors: 陆新晓; 史国钰; 陈一鸣; 李亚彪; 张慧; 刘金娉; 宋思远; 幸运; 沈聪; 蒋晨璐
Original assignee: China University of Mining and Technology Beijing CUMTB
Current assignee: China University of Mining and Technology Beijing CUMTB
Priority date: 2021-10-28
Filing date: 2022-02-11
Publication date: 2022-05-10

Abstract

The embodiment of the application discloses an intelligent fire-fighting full-chain prevention and control system and a multi-source information fusion decision-making method, relates to the technical field of fire fighting, and aims to improve the effective starting rate of an alarm condition processing device of the fire-fighting prevention and control system. The system comprises: the system comprises detection equipment, a fire fighting decision platform, a fire fighting central control platform and alarm situation processing equipment; the fire-fighting decision platform comprises a multi-source information fusion decision module; the detection equipment is connected with the fire-fighting decision-making platform, the multi-source information fusion decision-making module is connected with the fire-fighting central control platform, and the fire-fighting central control platform is connected with the alarm situation processing equipment; the detection equipment detects a fire prevention and control area to obtain first detection information and second detection information, the multi-source information fusion decision module judges whether a fire exists according to the received first detection information and the second detection information, if the fire exists, the multi-source information fusion decision module sends fire information to the fire control center control platform, and the fire control center control platform sends a control signal to control the start of the alarm processing equipment in the fire area. The application is suitable for discovering and processing fire.

Description

Intelligent fire-fighting full-chain prevention and control system and multi-source information fusion decision-making method

Technical Field

The application relates to the technical field of fire fighting, in particular to an intelligent fire fighting full-chain prevention and control system and a multi-source information fusion decision-making method.

Background

In the modern society, along with the improvement of science and technology, the number of fire disasters rises rapidly, which is a common disastrous problem for people, can cause serious casualties and property loss, and can cause environmental pollution in most cases. The fire-fighting prevention and control system improves the phenomenon to a certain extent, but in the existing fire prevention and control system, when the detection values of two or more independent fire detectors in the same alarm area reach the threshold value or one detection value reaches the threshold value and one hand-operated alarm button alarms, the fire-fighting prevention and control system can start the alarm processing equipment to extinguish the fire. However, the fire disaster is limited by the complexity of the fire disaster, the generation time and the quantity of combustion products are different under different combustion scenes, and if only the threshold value is taken as a measurement index, the phenomenon of false alarm or missed alarm is easy to occur, so that the effective starting rate of the alarm condition processing equipment in the fire-fighting prevention and control system is reduced.

Disclosure of Invention

In view of this, the embodiment of the present application provides an intelligent fire-fighting full-chain prevention and control system and a multi-source information fusion decision method, which can improve the effective start-up rate of an alert processing device in a fire-fighting prevention and control system to a certain extent.

In a first aspect, an embodiment of the present application provides an intelligent fire-fighting full-chain prevention and control system, including: the system comprises detection equipment, a fire fighting decision platform, a fire fighting central control platform and alarm situation processing equipment; the fire-fighting decision platform comprises a multi-source information fusion decision module; the detection equipment is connected with a multi-source information fusion decision module in the fire-fighting decision platform, the fire-fighting decision platform is connected with the fire-fighting central control platform, and the fire-fighting central control platform is connected with the alarm situation processing equipment; wherein the number of the detection devices is at least two; the fire prevention and control system comprises a fire prevention and control area, a multi-source information fusion decision module, a fire prevention and control area and a fire prevention and control area, wherein the fire prevention and control area is detected by the detection equipment to obtain first detection information and second detection information, the multi-source information fusion decision module receives the first detection information and the second detection information and judges whether a fire exists according to the first detection information and the second detection information, if the fire exists, the fire prevention and control area sends fire information to the fire prevention and control area, and the fire prevention and control area sends a control signal to control the start of alarm processing equipment in the fire prevention and control area.

According to a concrete implementation mode of the embodiment of the application, the multi-source information fusion decision module is a module based on a multi-layer feedforward network and a fuzzy decision of error back propagation training, the multi-layer feedforward network and the fuzzy decision based on the error back propagation training receive the first detection information and the second detection information, and judge whether a fire exists according to the first detection information, the second detection information and the multi-layer feedforward network and the fuzzy decision based on the error back propagation training, and if the fire exists, the fire information is sent to the fire control center control platform.

According to a specific implementation manner of the embodiment of the application, the fire fighting decision platform further comprises an auxiliary decision module; the auxiliary decision-making module receives the fire information sent by the multi-source information fusion decision-making module, and generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information.

According to a specific implementation manner of the embodiment of the application, the fire-fighting decision platform further comprises an escape route determining module; the escape route determination module is connected with the auxiliary decision-making module and receives the visual map with the fire information generated by the auxiliary decision-making module; the escape route module determines an escape route based on the fire information, a visual map, preset initial parameters and an ant colony algorithm, and sends the information of the escape route to the fire-fighting central control platform; and the fire-fighting central control platform receives the information of the escape route and sends the information to the mobile terminal.

According to a specific implementation manner of the embodiment of the present application, the assistant decision module includes: a visual map generation submodule and an emergency management submodule; the visual map generation submodule receives the fire information sent by the multi-source information fusion decision module and generates a visual map based on a GIS technology; and the emergency management submodule receives the fire information sent by the multi-source information fusion decision module and generates an emergency scheme corresponding to the fire information.

According to a specific implementation manner of the embodiment of the application, the alarm condition processing equipment comprises a fixed fire extinguishing sub-equipment and a movable fire extinguishing sub-equipment, wherein the fixed fire extinguishing sub-equipment and the movable fire extinguishing sub-equipment are respectively connected with the fire-fighting central control platform, and the movable fire extinguishing sub-equipment is also connected with the multi-source information fusion decision-making module; the fire-fighting central control platform sends out a control signal to control the fixed fire-fighting sub-equipment to start; the mobile fire extinguishing sub-equipment sends out a control signal according to the received fire control center control platform to extinguish a fire in the fire prevention and control area, meanwhile, the detection equipment of the mobile fire extinguishing sub-equipment detects the fire prevention and control area to obtain third detection information, the third detection information is sent to the multi-source information fusion decision module, the multi-source information fusion decision module judges whether a fire still exists according to the received first detection information, the received second detection information and the received third detection information, and if the fire still exists, the updated fire information is sent to the fire control center control platform; and the auxiliary decision-making module updates a visual map and a pre-made emergency scheme corresponding to the updated fire information according to the processing result of the multi-source information fusion decision-making module.

According to a specific implementation manner of the embodiment of the application, the detection device has a self-diagnosis function, and sends a self-diagnosis result to the fire-fighting central control platform so as to send a device fault alarm signal.

According to a specific implementation manner of the embodiment of the application, the system further comprises a database SQLite, an embedded web server and a mobile terminal, wherein the database SQLite is connected with detection equipment, the database SQLite is connected with the embedded web server, and the embedded web server is connected with the mobile terminal; the database SQLite receives and stores first detection information and second detection information of the detection equipment and fire information determined by the multi-source information fusion decision module, and sends the fire information to the embedded web server, so that the mobile terminal displays the fire information.

According to a specific implementation manner of the embodiment of the application, the system further comprises a customer service system and a mobile terminal, wherein the customer service system is connected with the mobile terminal; the customer service system receives a visualized map and an emergency scheme of the assistant decision module; and receiving a request of the mobile terminal, and performing field guidance by combining the visual map and the emergency scheme of the assistant decision module.

According to a specific implementation mode of the embodiment of the application, the mobile terminal further comprises a fire rescue system, and the mobile terminal is communicated with the fire rescue system and sends rescue signals and fire information to the fire rescue system.

In a second aspect, an embodiment of the present application provides a multi-source information fusion decision method, which is applied to the prevention and control system according to any one of the foregoing implementation manners of the foregoing claims, and includes: receiving first detection information and second detection information which are detected and sent by detection equipment; the first detection information and the second detection information are obtained by detecting a fire prevention and control area by a detection device; judging whether a fire condition exists according to the first detection information and the second detection information; and if the fire exists, fire information is sent to the fire-fighting central control platform.

According to a specific implementation manner of the embodiment of the present application, the receiving and detecting device detects the sent first detection information and the second detection information, including: a multi-layer feedforward network and fuzzy decision module based on error back propagation training receives the first detection information and the second detection information; the judging whether there is a fire condition according to the first detection information and the second detection information includes: and judging whether a fire exists according to the first detection information, the second detection information and the multilayer feedforward network based on the error back propagation training and fuzzy decision model.

According to a specific implementation manner of the embodiment of the present application, the method further includes: and sending the fire information to an auxiliary decision module so that the auxiliary decision module generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information.

According to a specific implementation manner of the embodiment of the present application, the assistant decision module includes: a visual map generation submodule and an emergency management submodule; the step of sending the fire information to an assistant decision-making module so that the assistant decision-making module generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information comprises the following steps: sending the fire information to the visual map generation submodule so that the visual map generation submodule generates a visual map according to the fire information and a GIS technology; and sending the fire information to the emergency management submodule so that the emergency management submodule generates an emergency scheme corresponding to the fire information according to the fire information.

According to a specific implementation manner of the embodiment of the present application, the method further includes: receiving third detection information; the third detection information is detection information obtained by detecting the fire prevention and control area by the detection equipment of the mobile fire extinguishing sub-equipment; and judging whether a fire still exists or not according to the received first detection information, second detection information and third detection information, and if the fire still exists, sending updated fire information to the fire control central control platform.

The intelligent fire-fighting full-chain prevention and control system and the multi-source information fusion decision method provided by the embodiment of the application connect the detection equipment with the multi-source information fusion decision module in the fire-fighting decision platform, the fire-fighting decision platform is connected with the fire-fighting central control platform, the fire-fighting central control platform is connected with the alarm processing equipment, at least two detection equipment detect a fire prevention and control area to obtain first detection information and second detection information, the multi-source information fusion decision module receives the first detection information and the second detection information, judges whether a fire exists according to the first detection information and the second detection information, sends the fire information to the fire-fighting central control platform if the fire exists, sends a control signal to the fire-fighting central control platform to control the start-up of the multi-source alarm processing equipment in the fire area, and because the multi-source information fusion decision module carries out comprehensive processing on the first detection information and the second detection information, the conclusion whether the fire exists is obtained, the effective starting rate of the alarm processing equipment is improved to a certain extent, and the condition that whether the fire exists or not is judged by depending on the detection information threshold value, so that the alarm processing equipment is prevented from being started in a missing mode or in a false mode.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a schematic structural diagram of an intelligent fire-fighting full-chain prevention and control system according to an embodiment of the present application;

FIG. 2 is a schematic diagram of an auxiliary decision system based on an event overall process;

FIG. 3 is a schematic structural diagram of a fire-fighting trolley provided in an embodiment of the present application;

FIG. 4 is a schematic view of a fire suppression cart according to yet another embodiment of the present application;

fig. 5 is a schematic flow chart of a multi-source information fusion decision method according to an embodiment of the present application.

Detailed Description

The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

It should be understood that the embodiments described are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Fig. 1 is a schematic structural diagram of an intelligent fire-fighting full-chain prevention and control system according to an embodiment of the present application, including: the system comprises detection equipment, a fire fighting decision platform, a fire fighting central control platform and alarm situation processing equipment; the fire-fighting decision platform comprises a multi-source information fusion decision module; wherein the number of detection devices is at least two.

The detection equipment is connected with a multi-source information fusion decision module in a fire-fighting decision platform, the fire-fighting decision platform is connected with a fire-fighting central control platform, and the fire-fighting central control platform is connected with the alarm situation processing equipment; the detection equipment detects a fire prevention and control area to obtain first detection information and second detection information, the multi-source information fusion decision module receives the first detection information and the second detection information and judges whether fire exists according to the first detection information and the second detection information, if the fire exists, the fire information is sent to the fire control center control platform, and the fire control center control platform sends out a control signal to control the start of the alarm processing equipment in the fire area.

The detection device can be a temperature-sensitive detector, a smoke-sensitive detector, a flame detector, a carbon monoxide detector, a combustible gas detector, a photosensitive detector and the like, and correspondingly detects data such as temperature, smoke, flame, carbon monoxide, combustible gas data, light intensity and the like related to fire. The number of detection devices is at least two.

Smoke fire detectors can be divided into point-type ionic smoke detectors, photoelectric smoke detectors and linear infrared beam smoke detectors. The temperature-sensing fire detector is divided into a constant temperature type, a differential temperature type and a differential constant temperature type, and the temperature-sensing fire detector has a point type and a linear type. The flame detector is a fire detector for detecting the illumination intensity of flame combustion and the flicker frequency of flame, and can be divided into three types of ultraviolet, infrared and ultraviolet-infrared mixed. The carbon monoxide detector is used in the places where carbon monoxide is generated in the early stage of fire and multiple signals are needed for composite alarm. The first detection information and/or the second detection information can be the magnitude of a certain physical quantity value and can also be other information capable of representing the fire disaster characteristic; the first detection information and the second detection information can be detected by two detection devices at different positions, and can also be detected by two different types of detection devices at the same position.

In order to improve the reliability of the detection equipment and improve the precision of the detection signal, the detection equipment can carry out self-diagnosis. Wherein, the self-diagnosis of the detection equipment comprises preheating self-diagnosis and regular self-diagnosis; the self-diagnosis comprises open circuit inspection, short circuit inspection and signal precision inspection; the preheating self-diagnosis is that after the detection equipment is started, the preheating self-diagnosis is automatically started, after the preheating self-diagnosis is finished and the detection is normal, the detection equipment starts to work, and when a fault is detected, an alarm signal is sent to the fire-fighting central control platform. The regular self-diagnosis is a self-diagnosis process carried out by the detection equipment regularly, the signal detection precision can be optimized regularly, and an alarm signal is sent to the fire-fighting central control platform when the equipment fault is detected.

In one example, a detection device includes a signal identification module and an information preprocessing module.

And the signal identification module can identify the environmental parameters to obtain signals corresponding to the required collection types. The detection equipment can process the detection information and make a preliminary decision through the information preprocessing module, and the signal preprocessing process comprises the following steps: and after the detection equipment collects the detection information, storing the detection information and starting to perform pre-decision processing. And in the pre-decision processing process, a median average filtering method is adopted, the signal average value is taken to process data, and the detection information is transmitted to a fire-fighting decision platform to carry out comprehensive processing decision.

The multi-source information fusion decision module in the fire-fighting decision platform can comprehensively judge more than two pieces of detection information to obtain whether fire exists or not.

The alarm processing equipment can be fixed fire extinguishing sub-equipment and movable fire extinguishing sub-equipment; the fire prevention and control area is an area needing fire prevention; and judging whether the fire occurs or not, and performing comprehensive judgment according to the first detection information and the second detection information.

The fire information may include fire area information, fire time information, fire type, detection information according to which a fire is determined, and information of a corresponding detection device.

The fire control central control platform receives the fire information and sends a starting signal to start the alarm processing equipment in the fire area, and the starting signal is sent to automatically send the starting signal for the fire control central control platform to receive the fire information.

In this embodiment, the detection device is connected to the multi-source information fusion decision module in the fire-fighting decision platform, the fire-fighting decision platform is connected to the fire-fighting central control platform, the fire-fighting central control platform is connected to the fire-fighting processing device, at least two detection devices detect the fire prevention and control area to obtain first detection information and second detection information, the multi-source information fusion decision module receives the first detection information and the second detection information, and judges whether there is a fire according to the first detection information and the second detection information, if there is a fire, the fire information is sent to the fire-fighting central control platform, the fire-fighting central control platform sends out a control signal to control the start of the fire-fighting processing device in the fire-starting area, because the multi-source information fusion decision module comprehensively processes the first detection information and the second detection information to obtain a conclusion whether there is a fire, and to a certain extent, the effective start rate of the fire-handling device is improved, the starting missing or false starting of the warning condition processing equipment caused by judging whether the fire condition exists or not depending on the detection information threshold is avoided.

The present application further provides an embodiment, which is different from the above embodiments in that the multi-source information fusion decision module in the fire protection and control system of the present embodiment is a module based on a multi-layer feedforward network and a fuzzy decision of error back propagation training, the multi-layer feedforward network and the fuzzy decision based on the error back propagation training receive the first detection information and the second detection information, and determine whether there is a fire according to the first detection information, the second detection information, the multi-layer feedforward network and the fuzzy decision based on the error back propagation training, and if there is a fire, send fire information to the fire control center control platform.

The error back propagation training multilayer feedforward network is provided with an input layer, a hidden layer and an output layer; in essence, the multi-layer feedforward network algorithm for error back propagation training uses the square of the network error as the objective function and adopts a gradient descent method to calculate the minimum value of the objective function. It is to be understood that the error back propagation trained multi-layer feedforward network model of the present application is a trained network model.

The training process of the multilayer feedforward network for error back propagation training is mainly divided into two stages, wherein the first stage is signal forward propagation, and the signal passes through a hidden layer from an input layer and finally reaches an output layer; the second stage is the back propagation of error, from the output layer to the hidden layer and finally to the input layer, and the weights from the hidden layer to the output layer and the weights from the input layer to the hidden layer are adjusted in sequence. The number of network layers, the number of nodes in each layer, a transfer function, an initial weight coefficient, a learning algorithm and the like are determined, and the multi-layer feedforward network for error back propagation training is also determined.

The selection of the initial weight coefficient plays a key role in the grid training speed, and the selection of the initial weight coefficient is to satisfy that the final output energy of the weighted input value is close to 0 and is generally selected to be any number between (-1, 1). In order to reduce network errors, the hidden layer transfer function is a tansig function, and the output layer transfer function is a purelin function. The mean square error MSE is reasonably selected in the neural network training process, so that the global error in the same network can be reduced, and the performances of different grids can be compared.

The purpose of using the neural network in the embodiment is to realize the fusion of data of a plurality of detectors and comprehensively judge whether a fire occurs. The number of input nodes of the multilayer feedforward network for error back propagation training is two or more n (n is more than or equal to 2) of detection parameters of a fire place detector, such as temperature, smoke, combustible gas, flame and images, and the number of output nodes is three of a no-fire probability, a smoldering probability and an open fire probability (a primary alarm probability, a secondary alarm probability and a tertiary alarm probability), namely an electric signal for judging whether a fire occurs.

Under the condition of simultaneously arranging a plurality of fire detectors, if the fire parameters of the detectors are changed, even if the fire parameters do not reach the alarm value, the fire can be considered to be in fire, and the response speed and the alarm accuracy of the automatic fire alarm system are greatly improved.

In some examples, a multi-source information fusion decision algorithm is adopted, and whether a fire disaster occurs and the danger level after the fire disaster occurs are determined after fusion analysis is carried out on different types of measurement parameters (such as temperature, smoke, combustible gas, flame and images), so that the accuracy of fire disaster early warning and the effectiveness of fire disaster rescue are improved. The multi-source information fusion decision module adopts a mode of combining a multi-layer feedforward network for error back propagation training with fuzzy decision.

Firstly, a multi-layer feedforward network trained by error back propagation is adopted, and the multi-layer feedforward network consists of two processes of signal forward propagation and error back propagation. The forward propagation of the signal is that the sample is transmitted from the input layer, processed layer by layer through the hidden layers and transmitted to the output layer. In the embodiment, the input signals are temperature, smoke, combustible gas, flame and images; the output signals are the probability of no fire, the probability of smoldering and the probability of open fire. The open fire probability is divided into a first-level alarm probability, a second-level alarm probability and a third-level alarm probability. If the actual output of the output layer does not match the desired output, the error is diverted to the back propagation stage. The back propagation of the error is to pass the output error back to the input layer by layer through the hidden layer in a certain form and distribute the error to all units of each layer, thereby obtaining the error signal of each layer of units, and the error signal is used as the basis for correcting the weight of each unit. And carrying out error analysis according to the result obtained by training and the expected result every time, further modifying the weight and the threshold value, and obtaining a model with the output consistent with the expected result in one step. An iteration termination condition needs to be set, and iteration is terminated or the number of iterations is set when the error is less than a certain value. The basic idea of the network is a gradient descent method, which uses a gradient search technique in order to minimize the mean square error of the actual output value and the expected output value of the network.

If a certain probability value in the flameless probability, the smoldering probability, the primary alarm probability, the secondary alarm probability and the tertiary alarm probability output by the multi-layer feedforward network model of the error back propagation training is much higher than other values, the probability can be judged to be the current fire state. However, if two or more fire-fighting apparatuses have similar numerical values, the fire disaster cannot be accurately judged, and a fuzzy decision should be adopted for further judgment.

In fuzzy control, firstly, input quantity of the system is limited within a specified range in a normalized mode, then input and output data are converted into fuzzy quantity from precise quantity, the system determines a distribution function of output quantity through fuzzy logic reasoning according to the fuzzy input quantity and a language control rule, and finally, the fuzzy quantity output by the fuzzy reasoning system is converted into a precise value with practical significance through a sharpening process. The input quantity of the fuzzy controller is the fire-free probability P1, smoldering probability P2, tertiary alarm probability P3, secondary alarm probability P4 and primary alarm probability P5 output by the neural network, and the output quantity is the fire probability P. Values for P1, P2, P3, P4, P5 and P are first limited to [0, 1] as domain of discourse U. According to actual conditions, the flameless probability P1, the smoldering probability P2, the tertiary alarm probability P3, the secondary alarm probability P4 and the primary alarm probability P5 output by the multi-layer feedforward network are fuzzified and graded as follows: the output fire level probability P is divided into two levels of fuzzification levels, namely a large level (L), a medium level (M) and a small level (S). Membership functions of the fuzzy sets are then established to determine whether a fire has occurred and the fire class.

The network mainly comprises the following application processes: in case of fire, the result detected by the detector is used as the first and second detection information, and the information is subjected to a multi-layer feedforward network for error back propagation training and fuzzy decision to determine whether fire occurs or the fire danger level. If a fire disaster occurs, fire information is sent to the fire-fighting central control platform, the fire-fighting central control platform sends out a control signal, and the start of the alarm processing equipment in the fire-starting area is controlled. And the fire extinguishing trolley enters a fire area, the progress of the fire condition is monitored, the detection result is used as third detection information and is transmitted to the multilayer feedforward network and the fuzzy decision module for error back propagation training in real time, and the specific situation of the fire is comprehensively analyzed. The comprehensive analysis of the trolley can improve the accuracy of detection, and can avoid the situation that after the fire is extinguished and rescued, the fire in certain hidden corners is small and can not reach the critical value of common detection equipment, so that the fire cannot be completely extinguished, and the hidden danger of secondary combustion is caused.

When the detection data of the detection equipment is transmitted into a multi-layer feedforward network and a fuzzy decision model for error back propagation training in a fire-fighting decision platform, a processing result is obtained through the multi-layer feedforward network and the fuzzy decision algorithm for the trained error back propagation training, and the processing result is output; when a fire occurs, the output result comprises fire area information, fire time information, fire type, detection information according to which the fire occurs and information of corresponding detection equipment.

Fig. 2 is a schematic structural diagram of an auxiliary decision-making system based on an entire event process, and a difference between the embodiment and the above embodiment is that the fire-fighting decision-making platform of the embodiment further includes an auxiliary decision-making module; the auxiliary decision-making module receives the fire information sent by the multi-source information fusion decision-making module, and generates and stores a visual map and an emergency scheme corresponding to the fire information according to the received fire information.

And the auxiliary decision-making module receives the fire information sent by the multi-source information fusion decision-making module, generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information, and stores the visual map and the emergency scheme corresponding to the fire information.

The visual map can be visually displayed by integrating various information such as fire places, key targets and the like by utilizing a GIS technology, and after a fire incident occurs, efficient emergency command can be realized by utilizing the assistance of the GIS map, so that visual and effective monitoring and management can be realized on the fire safety and emergency conditions of the whole area. And a corresponding emergency scheme can be formulated according to the fire information.

The emergency scheme comprises a rescue scheme, an evacuation scheme, equipment allocation and the like.

The present application further provides a different embodiment from the above embodiments, in that the fire fighting decision platform of the present embodiment further includes an escape route determining module; the escape route determination module is connected with the auxiliary decision-making module and receives the visual map with the fire information generated by the auxiliary decision-making module; the escape route determining module determines an escape route based on the fire information, a visual map, preset initial parameters and an ant colony algorithm, and sends the information of the escape route to the fire control center control platform; and the fire-fighting central control platform receives the information of the escape route and sends the information to the mobile terminal.

It is to be understood that the mobile terminal may be a mobile terminal corresponding to a trapped person.

The ant colony algorithm is a bionic algorithm obtained by simulating the foraging and path-finding modes of biological ants. Ants release pheromones during their search for food, and a range of other ants can perceive and thereby influence their subsequent behavior. Pheromones are gradually reduced along with the time, the more ants pass through a path, the higher the left pheromones are, the higher the probability that the ants select the path is, the higher the pheromone concentration of the path is, and a positive feedback mechanism is formed. The ant colony algorithm is a colony intelligent algorithm utilizing a distributed colony search strategy, and has excellent environment dynamic adaptability when large-scale path optimization is processed.

An escape route determination module comprising: an initial parameter determining submodule and an optimal route determining submodule.

And the initial parameter determining submodule is used for determining an area with fire and an area without fire, a position of a safety exit, an initial environment temperature of the position of the trapped person, the evacuation density of people in the escape channel, a CO gas concentration parameter, a dimming coefficient, the maximum iteration frequency, the preset number of target people, pheromone intensity, a pheromone elicitation factor, an expected elicitation factor, a pheromone volatilization factor and the like according to the visual map. Wherein the target persons are persons who may be in a fire zone and a non-fire zone.

And randomly placing each target person at different positions of the fire area and the non-fire area, wherein the position is used as a starting point, selecting the next node for each target person, and updating the pheromone table until ants visit all the nodes.

The optimal route determining submodule is used for obtaining the optimal escape route of each target person by utilizing an ant colony algorithm according to the visual map and the initial parameters; and determining the optimal escape route of the trapped people according to the optimal escape route of each target person.

Obtaining the optimal escape route of each target person by using an ant colony algorithm according to the visual map and the initial parameters, wherein the method comprises the following steps:

and obtaining the optimal escape sub-route of a target person and the pheromone concentration of each escape route to be selected under the current iteration number by utilizing an ant colony algorithm according to the visual map and the initial parameters, judging whether the current iteration number is the maximum iteration number, if so, ending the process, and if not, updating the pheromone concentration in the initial parameters. And repeating the process to obtain the optimal escape sub-routes corresponding to each iteration number, and selecting the optimal escape sub-route with the shortest distance from the optimal escape sub-routes corresponding to each iteration number as the optimal escape route.

According to the process, the optimal escape route corresponding to each target person can be obtained, the target person closest to the position of the trapped person is determined from each target person, and the optimal escape route corresponding to the target person is used as the optimal escape route of the trapped person.

It can be understood that the position of the trapped person can be determined by a position signal sent to the fire control central control platform through a mobile terminal carried by the trapped person, and the fire control central control platform sends the received position information of the trapped person to the escape route determining module.

The process of determining the optimal route of the embodiment: determining the position node of the trapped person and the position node of the safe exit, giving parameters such as maximum iteration times, ant number, pheromone strength, pheromone elicitation factors, expected elicitation factors, pheromone volatilization factors and the like, and then starting an algorithm program to judge whether the exit node is safely reached. If the safety is achieved, the length of the path and the passing time are recorded, the pheromone concentration is updated, whether the maximum iteration times are achieved is judged, if the maximum iteration times are achieved, the path with the shortest length and time is selected, a path graph is drawn and sent to a fire-fighting central control platform, and the fire-fighting central control platform sends a fire map and an optimal escape route to a mobile terminal carried by people to assist the evacuation of the trapped people. And if the data does not reach the safe exit safely, selecting the next node by adopting a random principle, and updating the data until the data reaches the safe exit.

In one example, an aid decision module, comprising: a visual map generation submodule and an emergency management submodule; the visual map generation submodule receives the fire information sent by the multi-source information fusion decision module and generates a visual map based on a GIS technology; and the emergency management submodule receives the fire information sent by the multi-source information fusion decision module and generates an emergency scheme corresponding to the fire information.

In one example, GIS-based resource visualization can achieve classified and graded retrieval and presentation according to danger levels and levels to which fire types belong, can query the position and the value of a certain device in a map system randomly, and can perform quantitative statistical analysis on a certain type or a specified resource type in a certain area.

And the emergency management submodule can generate and adjust a disposal scheme after a fire occurs, and can realize fire incident information input, fire related information calling and displaying, scheduling process recording, fire emergency summary evaluation and fire case generation after the fire occurs.

In one example, the assistant decision module further comprises: an auxiliary decision sub-module, a data analysis sub-module and/or a system management sub-module; the auxiliary decision sub-module is used for completing management tasks of decision support related information, and comprises fire emergency plan management, fire case management and key object management, wherein the fire emergency plan management organizes all levels of plans according to the grades, types and the like of the plans, so that the system can quickly position related plan contents in the emergency process; the fire case management organizes all levels of cases according to the case grades, types and the like, so that the system can quickly position the related case contents in the emergency process conveniently; the key object management can maintain various key objects related to the intelligent fire-fighting emergency of the home, such as key danger points (high-fire-risk houses and old buildings) and the like.

The data analysis submodule can be used for analyzing the fire related data in the system according to different dimensions such as time, place, objects and the like and displaying the data by using a diagram; and establishing models such as fire situation analysis and the like to realize identification of fire development rules and targeted prevention and control.

The system management submodule is used for realizing user group and authority control, data backup and recovery, personal information management and the like; the method can also be used for carrying out statistical analysis according to different dimensions such as the type and the grade of the fire disaster of the case, sensor information and the like, and can be used for carrying out statistical analysis according to different dimensions such as the type and the grade of a fire disaster plan. The research and development field is expanded to the analysis and research of fire-fighting big data. The fire-fighting big data analysis is to synthesize fire-fighting Internet of things collected data, fire case data and the like, and research and establish contents such as a fire development period sensing and judging model, a fire grade evaluation model and the like according to sensor data collected by the front end of the equipment when a fire occurs; the system management submodule mainly realizes user group and authority control, data backup and recovery, personal information management and the like.

When a fire occurs, the auxiliary decision module can quickly position related plan contents in an emergency process, and has the functions of fire plan classification tree management, fire plan query, fire emergency plan editing, fire plan review record management, fire plan version management and the like, and emergency management, and can perform emergency plan retrieval and matching, plan element matching and fire case retrieval according to fire data after the fire occurs; in daily life, the aid decision module has a case management function, can organize all levels of cases according to case grades, types and the like, and is convenient for the system to quickly position related case contents in an emergency process.

The position relationship between the warning situation processing device and the detection device can be as follows: the alarm processing equipment is arranged in the fire prevention and control area and can be correspondingly arranged with the detection equipment, namely the area provided with the detection equipment is correspondingly provided with the alarm processing equipment; the position relationship between the alarm processing equipment and the detection equipment can also be unfixed, in one example, the alarm processing equipment comprises fixed fire extinguishing sub-equipment and movable fire extinguishing sub-equipment, and the fixed fire extinguishing sub-equipment can be automatic water spraying fire extinguishing sub-equipment, gas fire extinguishing sub-equipment, foam fire extinguishing sub-equipment, dry powder fire extinguishing sub-equipment, water mist fire extinguishing sub-equipment, water spraying fire extinguishing sub-equipment and/or fire monitor fire extinguishing sub-equipment.

The fixed fire extinguishing sub-equipment and the movable fire extinguishing sub-equipment are respectively connected with the fire-fighting central control platform, and the movable fire extinguishing sub-equipment is also connected with the multi-source information fusion decision-making module; the fire-fighting central control platform sends out a control signal to control the fixed fire-fighting sub-equipment to start; the mobile fire extinguishing sub-equipment sends out a control signal according to the received fire control center control platform to extinguish a fire in the fire prevention and control area, meanwhile, the detection equipment of the mobile fire extinguishing sub-equipment detects the fire prevention and control area to obtain third detection information, the third detection information is sent to the multi-source information fusion decision module, the multi-source information fusion decision module judges whether a fire still exists according to the received first detection information, the received second detection information and the received third detection information, and if the fire still exists, the updated fire information is sent to the fire control center control platform; and the auxiliary decision-making module updates a visual map and a pre-made emergency scheme corresponding to the updated fire information according to the processing result of the multi-source information fusion decision-making module.

Referring to fig. 3, the mobile fire extinguishing sub-equipment is an active fire extinguishing device with real-time monitoring capability, and the mobile fire extinguishing sub-equipment can be a fire extinguishing trolley, which comprises a trolley main body, a control module, a fire detection module, a driving module, a fire extinguishing module, an obstacle avoidance module, a self-checking module, a wireless communication module and an alarm module.

The trolley main body adopts a four-wheel driving mode, and the outer surface and wheels of the trolley are made of fireproof materials. The control module, the direct current motor and the fire extinguishing facility are all connected to a 12V lithium power supply.

The control module comprises a fire detection control submodule, a drive control submodule, a wireless communication control submodule, a fire extinguishing control submodule, an obstacle avoidance control submodule, a self-checking control submodule and an alarm control submodule.

The fire detection module comprises a flame detector, a temperature detector and a smoke detector which are all connected with a fire detection control submodule of the control module. The flame detector can be arranged at the front end of the trolley main body, the temperature detector and the smoke detector are arranged at two ends of the trolley main body, and the number of each detector is at least two. The fire detector can judge the occurrence of fire in time, and the fire spreading direction can be judged by 3 flame detectors in front of the fire.

The driving module is a direct current motor and is connected with a driving control submodule of the control module.

The fire extinguishing module comprises a water tank, a water pipe, a conversion head, a telescopic arm, a supercharging device and a water gun, and is connected with a fire extinguishing control submodule of the control module.

The obstacle avoidance module comprises a photoelectric sensor. In one example, 3 photoelectric sensors are respectively arranged in the left front direction, the front direction and the right front direction of the trolley main body. After the transmitting end of the photoelectric sensor transmits, the obstacle can be reflected back when encountering the obstacle, and the obstacle is received by the receiving end (the infrared receiving tube) and sends a signal to the obstacle avoidance control submodule of the control module, the control module controls the rotating speed of the motor after receiving the signal, and the steering of the trolley is changed by the differential speed of the motor, so that the obstacle is effectively avoided.

The self-checking module comprises a pressure sensor and an electric quantity detector. The pressure sensor is placed below the water tank, if the pressure is insufficient due to water leakage or other reasons, the weight of the water tank can be reduced, the data measured by the pressure sensor is lower than a set threshold value, the information is transmitted to the self-checking control submodule of the control module, and the self-checking control submodule transmits information to the audible and visual alarm to give an alarm. The electric quantity detector monitors the electric quantity of the battery in real time, and transmits signals to the remote monitoring equipment, so that monitoring personnel can quickly judge the working condition of the trolley, and the standby trolley is arranged to enter a fire scene.

The wireless communication module is connected with the fire-fighting central control platform and transmits fire information mutually. The fire extinguishing trolley further comprises a spherical camera, can shoot data, transmits the data to the fire fighting central control platform through the wireless communication unit, and transmits the specific situation of a fire scene and whether trapped personnel exist.

The alarm unit comprises an audible and visual alarm and an alarm control submodule connected with the control module, and can give out alarm sound when the water tank is insufficient in pressure, abnormal in temperature and abnormal in air component content and detects flame or receives fire information transmitted by wireless communication.

Referring to fig. 4, in some examples, a mobile fire suppression sub-assembly includes: the trolley comprises a trolley body 1, wherein wheels 2, a battery 3, an electric quantity detection module 4, a water tank 5, a pressure sensor 6, a water pipe 7, a pressurizing device 8, an electronic valve 9, a rotating head 10, a telescopic arm 11, a water tank 12, a photoelectric sensor 13, a flame detector 14, a smoke detector 15, a temperature detector 16, a spray head 17, a one-way valve 18, an audible and visual alarm 19 and a camera 20 are arranged on the trolley body 1.

The battery 3 is connected with the electric quantity detection module 4, and the pressure sensor 6 is placed below the water tank 5.

The water tank 12 is connected with one end of the rotating head 10 through a telescopic arm 11, the other end of the water tank is connected with one end of an electronic valve 9, and the other end of the electronic valve 9 is connected with the water pool 5 through a pressurizing device 8; the spray head is connected with the water tank 5 through a water pipe 7, and an electronic valve is arranged on the water pipe 7.

The photoelectric sensor 13 and the flame detector 14 are arranged in front of the trolley main body; the smoke detector 15, the temperature detector 16 and the audible and visual alarm 19 are arranged on the side of the trolley main body; the one-way valve 18 is arranged on the trolley main body, and the pressurizing device 8, the electronic valve 9, the rotating head 10, the telescopic arm 11, the pressure sensor 6, the photoelectric sensor 13, the flame detector 14, the smoke detector 15, the temperature detector 16 and the audible and visual alarm 19 are connected with the control module.

The check valve 18 can be opened when water passes through the wheels under the condition that the lower part of the trolley is cooled by the spray head, so that the redundant water overflows from the valve, and further residual flame behind the trolley can be extinguished.

In the embodiment, the interlayer is arranged at the wheel at the bottom of the trolley to realize the cooling of the bottom of the trolley and the wheels, and the drain valve (one-way valve) is arranged at the rear part of the trolley to realize the release of the accumulated water in the interlayer and the maintenance of the flow of the water on the one hand and further extinguish the flame which is not extinguished at the rear end of the trolley on the other hand.

When a fire occurs, the fire-fighting central control platform sends a control signal to the mobile fire-fighting sub-equipment through a wireless technology, so that the mobile fire-fighting sub-equipment moves to a corresponding position, the control signal of the fire-fighting central control platform is continuously received in the process that the mobile fire-fighting module moves to the fire occurrence position, real-time fire information (such as data detected by a flame detector, a smoke detector and a temperature detector) detected by a fire detection module loaded on the mobile fire-fighting sub-equipment is also sent to the fire-fighting decision platform, the multi-source information fusion decision module in the fire-fighting decision platform comprehensively processes detection information (first detection information and second detection information) of the detection equipment and real-time fire information (third detection information) detected by a fire-fighting trolley, the fire condition, the fire type, the fire state and the fire position are re-determined, and the fire-fighting scheme is continuously adjusted and optimized, the decision accuracy is ensured by multiple judgments, and the wrong decisions are reduced and avoided. The portable dolly of putting out a fire puts out a fire and lasts the monitoring of condition of a fire state in the in-process, and the scheme of putting out a fire is improved in real time adjustment, and until putting out a fire and accomplishing, the image of shooting through the camera after putting out a fire is sent to accuse platform in the fire control to realize continuing monitoring a period, ensure not to reburn. The fire-fighting decision platform can also be combined with a GIS fire map, detection information of detection equipment and real-time fire information detected by the mobile fire-fighting sub-equipment to carry out optimization decision comprehensive treatment. The portable sub-equipment of putting out a fire can closely real-time supervision extinguishing process in-process condition of a fire state, and detection information is more accurate, avoids the condition of a fire misjudgement to lead to put out a fire not enough and put out a fire failure, can continue to monitor the condition of a fire after putting out a fire and accomplishing, prevents the after-combustion. The fire protection and control system further comprises a database SQLite, an embedded web server and a mobile terminal, wherein the database SQLite is connected with the detection equipment, the database SQLite is connected with the embedded web server, and the embedded web server is connected with the mobile terminal;

and the database SQLite receives and stores the first detection information and the second detection information of the detection equipment and the fire information of the fire-fighting decision platform, and if a fire exists, the database SQLite sends the fire information to the embedded web server so that the mobile terminal displays the fire information.

The embedded web server can be divided into two basic components: a daemon for HTTP and a server-side application. The functions realized by the HTTP daemon mainly comprise: establishing connection with the client, receiving request information of the client HTTP, feeding back HTTP response information after processing is finished, and closing the connection with the client.

The server side application program mainly realizes the mediation of a daemon program of the HTTP and an external system and completes the function expansion of the server; the CGI is used as an interface for information transfer between the web server and the server-side application program, and defines a manner in which the application program obtains user-submitted information from the daemon program and feeds back a processing result of the application program to the client. CGI is an interface standard between an external application (CGI program) and an embedded web server, a procedure for passing information between the CGI program and the web server. The CGI specification allows a web server to execute an external program and transmit the execution result to a web browser.

An embedded web server webpage is embedded in the mobile terminal app and used for receiving on-site fire information in real time; the mobile terminal app comprises a hidden danger module, a fault module, a monitoring module, an equipment module, a service module and a history module; the hidden danger module is used for displaying the number and the specific situation of the fire hidden dangers in a room, and the fault module is used for real-time fault information; the monitoring module is used for providing real-time detection service; the equipment module is used for feeding back the current operation parameters of the equipment; the service module is used for providing service for the user; the service module provides a common use problem solution for a user and provides a connection customer service; the history module is used for feeding back the change condition of the room parameters and simultaneously matching with the hidden danger module to enable the user to know the real-time condition of the family.

In one example, the CGI program transmits a processing result to the server, the server sends the result back to the user, and in our product, an embedded web server supporting the CGI function is installed in the existing embedded equipment for family fire fighting, so that a dynamic interface can be generated, the management and monitoring of the embedded equipment can be realized only by the web server at the user end, and the data management, the data updating and the prediction can be realized by uploading the data in the web server to a background database, so that a foundation is laid for our big data processing; a web server supporting script or CGI functions is operated on the embedded device through code migration, and can generate dynamic pages, and then the embedded device can be managed and monitored only through a web browser at a user end.

In another example, a fire-fighting user management system based on Qtopia Core and SQLite can be constructed, the actual parameters of each sensor installed in a fire-proof area can be displayed in real time on a mobile phone in a graphical interface mode, the parameters of the sensors can be inquired on a simple mobile phone, timely alarming is carried out when a fire disaster occurs, the alarm condition processing equipment can be controlled to work, and remote guidance information can be received in real time.

The present application further includes a customer service system and a mobile terminal, where the customer service system is connected to the mobile terminal.

The customer service system can receive an emergency assistance request sent by the mobile terminal, return a pre-established emergency scheme to the mobile terminal and provide field guidance. It is understood that in the customer service system, an emergency scenario corresponding to a fire is stored. In one example, the customer service system may be connected to an assistant decision system, receive a visual map and an emergency plan generated according to fire information in the assistant decision system, and use the visual map and the emergency plan as a pre-made visual map and emergency plan of the customer service system.

The embodiment of the application is different from the embodiment in that the mobile terminal further comprises a fire rescue system, and the mobile terminal is communicated with the fire rescue system and sends rescue signals and fire information to the fire rescue system.

The mobile terminal sends a rescue signal and fire information to the fire rescue system, and the fire information comprises: the information of the fire area, the information of the fire time, the detection information according to which the fire condition is judged, the information of the corresponding detection equipment and the address information of the fire area are obtained.

Fig. 5 is a schematic flow diagram of a multi-source information fusion decision method provided in an embodiment, where the method of this embodiment may be applied to the prevention and control system described in any of the above embodiments, and the method may include:

s101, receiving first detection information and second detection information which are detected and sent by detection equipment.

In the present embodiment, the first detection information and the second detection information are obtained by detecting the fire prevention and control area by the detection device.

The method of this embodiment may be applied to the prevention and control system described in any of the above embodiments, and specifically may be applied to a multi-source information fusion decision module.

In this embodiment, the specific description of the detection device, the first detection information and/or the second detection information can refer to the intelligent fire-fighting full-chain prevention and control system, which is not described herein again.

And S102, judging whether a fire occurs according to the first detection information and the second detection information.

In this embodiment, whether a fire is present or not can be determined based on two or more detection information.

S103, if fire exists, fire information is sent to the fire-fighting central control platform.

In this embodiment, the fire information may include fire area information, fire time information, a fire type, detection information according to which a fire is determined, and information of a corresponding detection device.

In the embodiment, the first detection information and the second detection information which are detected and sent by the detection equipment are received, wherein the first detection information and the second detection information are obtained by detecting a fire prevention and control area by the detection equipment, whether a fire occurs or not is judged according to the first detection information and the second detection information, if a fire occurs, the fire information is sent to the fire control center control platform, and whether a fire occurs or not is judged by comprehensively processing the first detection information and the second detection information.

In one example, the detecting the transmitted first detection information and second detection information by the receiving detection device (S101), may include:

s101a, the multi-layer feedforward network based on error back propagation training and fuzzy decision module receives the first detection information and the second detection information.

The multi-source information fusion decision module in the embodiment is a multi-layer feedforward network and fuzzy decision module based on error back propagation training.

In this embodiment, the multi-layer feedforward network and the fuzzy decision model based on the error back propagation training receive the first detection information and the second detection information.

Determining whether there is a fire according to the first detection information and the second detection information (S102), which may include:

s102a, judging whether a fire exists according to the first detection information, the second detection information and the multi-layer feedforward network and fuzzy decision model based on the error back propagation training.

Correspondingly, the error back propagation training-based multi-layer feedforward network and fuzzy decision module judges whether a fire exists according to the first detection information, the second detection information and the error back propagation training-based multi-layer feedforward network and fuzzy decision model.

The training and calculating process of the multi-layer feedforward network and the fuzzy decision model based on the error back propagation training is described in the related description of the embodiment of the intelligent fire-fighting full-chain prevention and control system, and is not repeated herein.

The present application further provides a method, which is substantially the same as the above embodiments, except that the method further includes:

s104, sending the fire information to an assistant decision module so that the assistant decision module generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information.

For the working process of the assistant decision module, reference may be made to the description of the embodiment of the intelligent fire-fighting full-chain fire-fighting protection and control system, which is not described herein again.

In one example, the aid decision module includes: a visual map generation submodule and an emergency management submodule;

the sending the fire information to an assistant decision module to enable the assistant decision module to generate a visual map and an emergency plan corresponding to the fire information according to the received fire information (S104), which may include:

s104a, sending the fire information to the visualization map generation submodule so that the visualization map generation submodule generates a visualization map according to the fire information and a GIS technology.

The GIS-based resource visualization can realize classified and graded retrieval and presentation according to danger levels and fire type levels, can inquire the position and the numerical value of a random certain device in a map system, and can perform quantitative statistical analysis on a certain type or a specified resource type in a certain area.

S104b, sending the fire information to an emergency management submodule so that the emergency management submodule generates an emergency scheme corresponding to the fire information according to the fire information.

And after a fire occurs, the emergency management submodule generates and adjusts a disposal scheme, and after the fire occurs, the information input of fire events, the calling and displaying of fire related information, the recording of scheduling processes, the emergency summary evaluation of the fire and the generation of fire cases are realized.

Another embodiment of the present application is substantially the same as the above embodiments, except that the method of the present embodiment may further include:

s105, receiving third detection information; and the third detection information is detection information obtained by detecting the fire prevention and control area by the detection equipment of the mobile fire extinguishing sub-equipment.

And the movable fire extinguishing sub-equipment sends out a control signal according to the received fire control center control platform to extinguish the fire in the fire control area.

The structure of the mobile fire extinguishing sub-device can be referred to the related description of the embodiment of the intelligent fire fighting full-chain prevention and control system, and is not described herein again.

When a fire occurs, the fire control center control platform sends a control signal to the mobile fire extinguishing sub-equipment through a wireless technology, so that the mobile fire extinguishing sub-equipment moves to a corresponding position, and the control signal of the fire control center control platform is continuously received when the mobile fire extinguishing module moves to the fire occurrence position.

And detecting the fire prevention and control area by using detection equipment of the mobile fire extinguishing sub-equipment to obtain third detection information, and sending the third detection information to the multi-source information fusion decision-making module.

Real-time fire information detected by a fire detection module loaded on the mobile fire extinguishing sub-equipment can be sent to a fire fighting decision platform.

S106, judging whether a fire still exists according to the received first detection information, the second detection information and the third detection information, and if the fire still exists, sending updated fire information to the fire-fighting central control platform.

In some examples, the assistant decision module updates a visual map and a pre-made emergency plan corresponding to the updated fire information according to the processing result of the multi-source information fusion decision module.

The application relates to a fire-fighting early warning prevention and control method, which comprises the following steps:

step 1, the intelligent gateway controls and manages each detection device.

The detection device may also be referred to as a monitoring terminal.

And 2, monitoring the fire prevention and control area in the building by each detection device.

And 3, judging whether the monitoring information truly reflects the fire according to a multi-layer feedforward network data fusion method of error back propagation training.

And step 4, the analog-to-digital conversion circuit is connected with the alarm equipment and the network transmission Internet of things platform.

And 5, sending the current fire information to the mobile terminal, and starting the mobile fire extinguishing sub-equipment.

The mobile fire extinguishing sub-equipment can be a fire extinguishing trolley.

According to the intelligent fire-fighting full-chain prevention and control system and the multi-source information fusion decision-making method, through the application of technologies such as the Internet of things, big data and artificial intelligence, a data, supporting and storage and scientific and rigorous study and judgment mechanism for assisting decision-making is established, a multi-position integrated fire prevention and control system including hidden danger investigation, fire alarm, automatic fire extinguishing and remote guidance is established, and early fire discovery and extinguishment are scientifically and efficiently achieved. The attached many first information processing APP of product can convert the complicated information of traditional fire monitoring equipment into the animation and the literal information that the user of being convenient for understands to can provide long-range professional guidance, make the user make correct reply in the conflagration, avoid worsening of the condition of a fire because the scene personnel of conflagration reply improper, even lose the chance of fleing.

It should be noted that, in this document, relational terms such as first and second, and the like are used only for description

One entity or operation is distinguished from another entity or operation by no means requiring or implying any actual such relationship or order between such entities or operations. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. The utility model provides an wisdom fire control full chain prevention and control system which characterized in that includes: the system comprises detection equipment, a fire fighting decision platform, a fire fighting central control platform and alarm situation processing equipment; the fire-fighting decision platform comprises a multi-source information fusion decision module;

the detection equipment is connected with a multi-source information fusion decision module in the fire-fighting decision platform, the fire-fighting decision platform is connected with the fire-fighting central control platform, and the fire-fighting central control platform is connected with the alarm situation processing equipment; wherein the number of the detection devices is at least two;

the fire disaster prevention and control system comprises a fire disaster prevention and control area, a multi-source information fusion decision module, a fire disaster detection and control platform, a fire disaster detection and control area and a multi-source information fusion decision module, wherein the fire disaster prevention and control area is detected by the detection equipment to obtain first detection information and second detection information, the multi-source information fusion decision module receives the first detection information and the second detection information and judges whether a fire disaster exists or not according to the first detection information and the second detection information, if the fire disaster exists, the fire disaster information is sent to the fire disaster prevention and control platform, and the fire disaster prevention and control platform sends a control signal to control the start of the alarm disaster processing equipment in the fire disaster area.

2. The intelligent fire-fighting full-chain prevention and control system according to claim 1, wherein the multi-source information fusion decision module is a multi-layer feedforward network and fuzzy decision module based on error back propagation training, the multi-layer feedforward network and fuzzy decision module based on error back propagation training receives the first detection information and the second detection information, judges whether there is a fire according to the first detection information, the second detection information and the multi-layer feedforward network and fuzzy decision model based on error back propagation training, and sends fire information to the fire-fighting central control platform if there is a fire.

3. The intelligent fire-fighting full-chain prevention and control system according to claim 1, wherein the fire-fighting decision platform further comprises an auxiliary decision module; the auxiliary decision-making module receives the fire information sent by the multi-source information fusion decision-making module, and generates a visual map and an emergency scheme corresponding to the fire information according to the received fire information.

4. The intelligent fire-fighting full-chain prevention and control system according to claim 3, wherein the fire-fighting decision platform further comprises an escape route determination module; the escape route determining module is connected with the auxiliary decision-making module and receives the visual map with the fire information generated by the auxiliary decision-making module; the escape route module determines an escape route based on the fire information, a visual map, preset initial parameters and an ant colony algorithm, and sends the information of the escape route to the fire-fighting central control platform; and the fire-fighting central control platform receives the information of the escape route and sends the information to the mobile terminal.

5. The intelligent fire-fighting full-chain prevention and control system according to claim 3, wherein the assistant decision module comprises: a visual map generation submodule and an emergency management submodule; the visual map generation submodule receives the fire information sent by the multi-source information fusion decision module and generates a visual map based on a GIS technology;

and the emergency management submodule receives the fire information sent by the multi-source information fusion decision module and generates an emergency scheme corresponding to the fire information.

6. The intelligent fire-fighting full-chain prevention and control system according to claim 3, wherein the alarm processing equipment comprises a fixed fire-fighting sub-equipment and a mobile fire-fighting sub-equipment, the fixed fire-fighting sub-equipment and the mobile fire-fighting sub-equipment are respectively connected with the fire-fighting central control platform, and the mobile fire-fighting sub-equipment is further connected with the multi-source information fusion decision-making module;

the fire-fighting central control platform sends out a control signal to control the fixed fire-fighting sub-equipment to start; the mobile fire extinguishing sub-equipment sends out a control signal according to the received fire control center control platform to extinguish a fire in the fire prevention and control area, meanwhile, the detection equipment of the mobile fire extinguishing sub-equipment detects the fire prevention and control area to obtain third detection information, the third detection information is sent to the multi-source information fusion decision module, the multi-source information fusion decision module judges whether a fire still exists according to the received first detection information, the received second detection information and the received third detection information, and if the fire still exists, the updated fire information is sent to the fire control center control platform; and the auxiliary decision-making module updates a visual map and a pre-made emergency scheme corresponding to the updated fire information according to the processing result of the multi-source information fusion decision-making module.

7. The intelligent fire-fighting full-chain prevention and control system as claimed in claim 1, wherein the detection device has a self-diagnosis function and sends the self-diagnosis result to the fire-fighting central control platform to send out a device failure alarm signal.

8. The intelligent fire-fighting full-chain prevention and control system according to claim 1, further comprising a database SQLite, an embedded web server and a mobile terminal, wherein the database SQLite is connected with a detection device, the database SQLite is connected with the embedded web server, and the embedded web server is connected with the mobile terminal; the database SQLite receives and stores first detection information and second detection information of the detection equipment and fire information determined by the multi-source information fusion decision module, and sends the fire information to the embedded web server, so that the mobile terminal displays the fire information.

9. The intelligent fire-fighting full-chain prevention and control system according to claim 3, further comprising a customer service system and a mobile terminal, wherein the customer service system is connected with the mobile terminal; the customer service system receives a visualized map and an emergency scheme of the assistant decision module; and receiving a request of the mobile terminal, and performing field guidance by combining the visual map and the emergency scheme of the assistant decision module.

10. The intelligent fire-fighting full-chain prevention and control system according to claim 9, further comprising a fire rescue system, wherein the mobile terminal is in communication with the fire rescue system and sends rescue signals and fire information to the fire rescue system.