Fire-fighting commanding and dispatching system based on Internet of Things
By designing a fire command and dispatch system based on the Internet of Things, real-time monitoring and analysis of fire conditions and fire resources, and intelligently judging the optimal dispatch range, it solves the problem that traditional systems are difficult to quickly respond to fire conditions and uneven distribution of resources, and achieves efficient and accurate fire command and dispatch.
Patent Information
- Application Number
- CN202411634225.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-15
- Publication Date
- 2025-03-04
AI Technical Summary
Traditional fire command and dispatching systems are difficult to respond to fires quickly and accurately, resulting in the spread of fires. The resource distribution of micro-fire stations is uneven and the dispatch efficiency is inefficient, resulting in the missed optimal fire extinguishing time.
Design a fire command and dispatch system based on the Internet of Things, including a fire resource database, a fire growth index analysis module, a dispatching fire extinguishing index analysis module and a dispatching range output module. Through real-time monitoring and analysis of fire conditions and fire resources, intelligently judge the optimal dispatching range to ensure that sufficient fire extinguishing force is quickly dispatched.
It has achieved accurate prediction of the growth trend of fire, intelligently judged the optimal scheduling range, ensuring that sufficient fire extinguishing power is dispatched in the shortest time, avoiding unnecessary scheduling waste, and reducing the impact on fire resources in other areas.
Smart Images
Figure CN119548785A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of Internet of Things, and in particular to a fire control command and dispatch system based on Internet of Things. Background Art
[0002] With the acceleration of urbanization, the density of urban buildings is increasing, and fire safety issues are becoming increasingly prominent. Traditional fire command and dispatch systems often rely on manual reports and static resource allocation, which makes it difficult to respond to fires quickly and accurately, causing fires to spread rapidly and pose a serious threat to people's lives and property. Especially in large cities or building complexes, due to the uneven distribution of fire resources and low dispatch efficiency, the best time to extinguish a fire is often missed.
[0003] Urban micro fire stations play an important role in the fire protection system with their wide distribution and high mobility. However, due to their limited fire-fighting resources, it is often difficult to effectively respond to medium or large-scale fires when acting alone. Excessive dispatch of micro fire stations may trigger a series of chain reactions: chaos on the scene, delays in the arrival of rescue forces, uncontrolled spread of fires, and even excessive dispatching of fire resources in a wider area, resulting in rescue operations in other areas being disturbed or delayed when fires occur in multiple places at the same time, seriously threatening overall public safety. Therefore, how to effectively integrate and utilize the resources of these micro fire stations to achieve rapid and efficient fire command and dispatch has become an urgent problem to be solved. Summary of the invention
[0004] The purpose of the present invention is to provide a fire command and dispatch system based on the Internet of Things to solve the problems raised in the above background technology.
[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a fire command and dispatch system based on the Internet of Things, comprising a fire resource database, a fire growth index analysis module, a dispatch fire extinguishing index analysis module and a dispatch range output module, wherein the fire resource database is used to monitor and collect data on urban fire resources, the fire monitoring module is used to store and record urban building information and fire resource information of micro fire stations, the fire growth index analysis module is suitable for analyzing and predicting the size of fire growth when a fire occurs, the dispatch fire extinguishing index analysis module is used to analyze the fire extinguishing capabilities achieved under different dispatch ranges, and the dispatch range output module is used to determine the dispatch range for outputting the final decision based on the fire growth prediction and the fire dispatch fire extinguishing capability analysis results, and the fire resource database, the fire growth index analysis module, the dispatch fire extinguishing index analysis module and the dispatch range output module are electrically connected.
[0006] According to the above technical scheme, the fire resource database includes a micro fire station registration module, a building information registration module, a fire resource information sorting module and a fire monitoring module. The micro fire station registration module is used to register the micro fire station information in the city and connect it to the fire resource database. The building information registration module is used to register the building information in the city and connect it to the fire resource database. The fire resource information sorting module is used to classify and sort the information registered and recorded in the fire resource database and quickly extract the sorted data. The fire monitoring module is used to monitor the fire in the building.
[0007] According to the above technical solution, the fire growth index analysis module includes a fire spread speed classification module, an initial fire identification module and a fire prediction image construction module. The fire spread speed classification module is used to classify the building fire spread speed according to the building information where the fire monitoring points are deployed. The initial fire identification module is suitable for identifying the size of the monitored fire when a fire occurs in the building. The fire spread speed classification module and the initial fire identification module are both electrically connected to the fire prediction image construction module. The fire prediction image construction module is used to analyze and construct a function image of the fire growth over time.
[0008] According to the above technical solution, the scheduling fire extinguishing index analysis module includes a scheduling fire extinguishing index statistics module and a fire extinguishing broken line image construction module. The scheduling fire extinguishing index statistics module is used to count the maximum fire extinguishing index sum of the micro fire station according to the scheduling range, and the fire extinguishing broken line image construction module is used to analyze and construct a scheduling fire extinguishing index broken line image based on the fire occurrence point.
[0009] According to the above technical solution, the dispatch range output module includes a comparison and judgment module and a fire command and dispatch instruction issuing module. The comparison and judgment module is used to compare and analyze the constructed image relationship and judge the fire command and dispatch radius corresponding to the optimal dispatch range. The fire command and dispatch instruction issuing module is used to issue dispatch fire extinguishing instructions to the micro fire stations within the judgment range according to the judgment result of the comparison and judgment module. The comparison and judgment module is electrically connected to the fire command and dispatch instruction issuing module.
[0010] According to the above technical solution, the fire resource information sorting module further includes a position acquisition submodule, a fire extinguishing index acquisition submodule, a building fire resistance level acquisition submodule and a building use density acquisition submodule, wherein the position acquisition submodule is used to acquire the precise position point of the urban micro fire station, the fire extinguishing index acquisition submodule is used to acquire the maximum fire extinguishing index of each urban micro fire station, the building fire resistance level acquisition submodule is used to acquire the fire resistance level of each building, and the building use density acquisition submodule is used to acquire the regional use density inside the building;
[0011] The fire monitoring module further includes a smoke sensing unit, a thermal imaging unit and a positioning unit. The smoke sensing unit is used to sense and monitor smoke to determine whether a fire has occurred at the corresponding monitoring point. The thermal imaging unit is used to detect the thermal imaging image of the fire. The positioning unit is used to send the location of the fire occurrence point.
[0012] According to the above technical solution, the dispatching method of the fire command and dispatching system based on the Internet of Things includes:
[0013] Step S1: Establish a fire resource database, connect the urban micro fire station and building information to the fire resource database, and integrate the fire resource information of the urban micro fire station, wherein the urban micro fire station information includes the precise location of each micro fire station and the maximum fire extinguishing index m of the reserve; wherein the building information includes the fire resistance grade of the building and the building usage density;
[0014] Step S2: deploy fire monitoring points in urban buildings, and connect the monitoring data of the building fire monitoring points to the fire resource database;
[0015] Step S3: according to the building information where the fire monitoring point is deployed, the fire spread speed of the building is divided, and a specific fire spread speed coefficient k is output;
[0016] Step S4: Real-time monitoring of urban buildings. When a fire is detected, the smoke sensing unit outputs an induction electrical signal, and the thermal imaging unit is activated to perform thermal imaging of the monitoring area, fit the thermal imaging contour, and convert the output into an initial fire size index value C when the fire is detected;
[0017] Step S5: According to the initial fire intensity index value C and the fire spread speed coefficient k corresponding to the monitoring point where the fire is detected, the exponential relationship between the fire intensity and time is analyzed and calculated, and a function graph is constructed;
[0018] Step S6: Then determine the location point W where the fire monitoring point is located. With the location point W as the center, r is the fire command and dispatch radius, a is the minimum dispatch unit distance of the fire command and dispatch radius, and when r=a, 2a, 3a, ..., na distances are obtained respectively, the total maximum fire extinguishing index M of the micro fire station within the fire command and dispatch range is M={M1, M2, M3, ..., M n};
[0019] Step S7: Based on the historical big data of the fire resource database, the reference time t of each dispatch minimum dispatch unit distance a is set, then r = a, 2a, 3a, ..., na, the corresponding required dispatch time T = t, 2t, 3t, ..., nt, with the dispatch time T as the horizontal axis and the total maximum fire extinguishing index M of the micro fire station as the vertical axis, a plane rectangular coordinate system is established, and (t, M1), (2t, M2), (3t, M3), ..., (nt, M4) are marked in the plane rectangular coordinate system respectively. n ), then connect all the marked points to construct a line graph of the dispatch fire extinguishing index;
[0020] Step S8: Compare the constructed function graph of the fire intensity increasing over time with the dispatch fire extinguishing index line graph, analyze and determine the fire command dispatch radius r corresponding to the optimal dispatch range j ;
[0021] Step S9: Based on the judgment result, when the system detects a fire, the system takes the location W of the currently determined fire monitoring point as the center, r j The coverage area is of radius, and all micro fire stations in the coverage area are commanded to go to the location W where the fire monitoring point is located to carry out fire extinguishing.
[0022] According to the above technical solution, the method for dividing the building fire spread speed in step S3 is: the building fire resistance level corresponds to four cardinal numbers Ω1, Ω2, Ω3, and Ω4 respectively, and the fire resistance level Ω of the building where the fire occurs is obtained. i , where i = 1, 2, 3, 4, and then match the building usage density ρ in the area according to the monitoring point, through the formula k = ρ·Ω i Calculate the fire spread rate coefficient at the fire location.
[0023] According to the above technical solution, in step S5, the exponential relationship between the fire intensity and the time growth is:
[0024]
[0025] In the formula, H is the fire index. The larger the fire index is, the greater the fire intensity is. T is the time value. When T=0, H=C, which means that when the fire is detected, the initial fire index value is C. At the same time, k>1 is satisfied. Therefore, the function graph corresponding to the exponential relationship between the fire intensity and time is: The larger the time is, the greater the fire index H is.
[0026] The time T2 recorded when the fire is detected is taken as the horizontal axis, and the predicted fire index H is taken as the vertical axis. The function graph is constructed based on the exponential relationship between the fire intensity and the growth of the fire over time.
[0027] According to the above technical solution, step S8 specifically includes:
[0028] The constructed function graph of the fire intensity growing over time is compared with the dispatch fire extinguishing index line graph, and the minimum value T corresponding to the horizontal coordinate T when M≥H is satisfied in the comparison image is searched. min , output the two sets of marked points ((∈-1)t, M) whose horizontal coordinates are adjacent in the fire extinguishing index line image ∈-1 ) and (∈t, M ∈ ), then determine ∈t as the optimal dispatch time for analysis, then determine the fire command dispatch radius r corresponding to the optimal dispatch range j =∈a.
[0029] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention can accurately predict the growth trend of fire, and based on the dynamic relationship between the fire situation and fire-fighting resources, intelligently determine the optimal dispatch range, ensuring that sufficient fire-fighting forces are dispatched to the scene in the shortest time, while avoiding unnecessary dispatch waste, reducing the dispatch range, and reducing the impact on fire-fighting resources in other areas. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.
[0031] In the attached picture:
[0032] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION
[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0034] See also Figure 1The present invention provides a technical solution: a fire command and dispatch system based on the Internet of Things, including a fire resource database, a fire growth index analysis module, a dispatch fire extinguishing index analysis module and a dispatch range output module, the fire resource database is used to monitor and collect data on urban fire resources, the fire monitoring module is used to store and record urban building information and fire resource information of micro fire stations, the fire growth index analysis module is suitable for analyzing and predicting the size of fire growth when a fire occurs, the dispatch fire extinguishing index analysis module is used to analyze the fire extinguishing capabilities achieved under different dispatch ranges, and the dispatch range output module is used to determine the dispatch range for outputting the final decision based on the fire growth prediction and the fire dispatch fire extinguishing capability analysis results, and the fire resource database, the fire growth index analysis module, the dispatch fire extinguishing index analysis module and the dispatch range output module are electrically connected; the fire growth trend can be accurately predicted, and based on the dynamic change relationship between the fire situation and fire resources, the optimal dispatch range can be intelligently determined to ensure that sufficient fire extinguishing forces are dispatched to arrive at the scene in the shortest time, while avoiding unnecessary dispatch waste, reducing the dispatch range, and reducing the impact on fire resources in other areas. Compared with traditional manual reporting and static resource allocation methods, the system significantly improves the scientificity and accuracy of fire command and dispatch, providing a strong guarantee for urban fire safety. It is especially suitable for scenarios where fire resources are unevenly distributed and dispatch efficiency is low in large cities or building complexes. It effectively reduces the risk of loss of life and property caused by fire and improves the level of public safety.
[0035] The fire resource database includes a micro fire station registration module, a building information registration module, a fire resource information sorting module and a fire monitoring module. The micro fire station registration module is used to register and connect the micro fire station information in the city to the fire resource database. The building information registration module is used to register and connect the building information in the city to the fire resource database. The fire resource information sorting module is used to classify and sort the information registered and recorded in the fire resource database and quickly extract the sorted data. The fire monitoring module is used to monitor fires occurring in buildings.
[0036] The fire growth index analysis module includes a fire spread speed classification module, an initial fire recognition module and a fire prediction image construction module. The fire spread speed classification module is used to classify the building fire spread speed according to the building information where the fire monitoring points are deployed. The initial fire recognition module is suitable for identifying the size of the monitored fire when a fire occurs in the building. The fire spread speed classification module and the initial fire recognition module are both electrically connected to the fire prediction image construction module. The fire prediction image construction module is used to analyze and construct a function image of the fire growth over time.
[0037] The dispatching fire extinguishing index analysis module includes a dispatching fire extinguishing index statistics module and a fire extinguishing line image construction module. The dispatching fire extinguishing index statistics module is used to count the maximum fire extinguishing index sum of the micro fire station according to the dispatching range, and the fire extinguishing line image construction module is used to analyze and construct a dispatching fire extinguishing index line image based on the fire occurrence point.
[0038] The dispatch range output module includes a comparison and judgment module and a fire command and dispatch instruction issuing module. The comparison and judgment module is used to compare and analyze the constructed image relationship and judge the fire command and dispatch radius corresponding to the optimal dispatch range. The fire command and dispatch instruction issuing module is used to issue dispatch fire extinguishing instructions to the micro fire stations within the judgment range according to the judgment results of the comparison and judgment module. The comparison and judgment module is electrically connected to the fire command and dispatch instruction issuing module.
[0039] The fire resource information sorting module further includes a location acquisition submodule, a fire extinguishing index acquisition submodule, a building fire resistance level acquisition submodule and a building use density acquisition submodule. The location acquisition submodule is used to obtain the precise location point of the urban micro fire station, the fire extinguishing index acquisition submodule is used to obtain the maximum fire extinguishing index of each urban micro fire station, the building fire resistance level acquisition submodule is used to obtain the fire resistance level of each building, and the building use density acquisition submodule is used to obtain the regional use density inside the building;
[0040] The fire monitoring module further includes a smoke sensing unit, a thermal imaging unit and a positioning unit. The smoke sensing unit is used to sense and monitor smoke to determine whether a fire has occurred at the corresponding monitoring point. The thermal imaging unit is used to detect the thermal imaging image of the fire. The positioning unit is used to send the location of the fire occurrence point.
[0041] A dispatching method for a fire command and dispatching system based on the Internet of Things, comprising:
[0042] Step S1: Establish a fire resource database, connect the urban micro fire station and building information to the fire resource database, and integrate the fire resource information of the urban micro fire station, wherein the urban micro fire station information includes the precise location of each micro fire station and the maximum fire extinguishing index m of the reserve; wherein the building information includes the fire resistance grade of the building and the building usage density;
[0043] Step S2: deploy fire monitoring points in urban buildings, and connect the monitoring data of the building fire monitoring points to the fire resource database;
[0044] Step S3: according to the building information where the fire monitoring point is deployed, the fire spread speed of the building is divided, and a specific fire spread speed coefficient k is output;
[0045] Step S4: Real-time monitoring of urban buildings. When a fire is detected, the smoke sensing unit outputs an induction electrical signal, and the thermal imaging unit is activated to perform thermal imaging of the monitoring area, fit the thermal imaging contour, and convert the output into an initial fire size index value C when the fire is detected;
[0046] Step S5: According to the initial fire intensity index value C and the fire spread speed coefficient k corresponding to the monitoring point where the fire is detected, the exponential relationship between the fire intensity and time is analyzed and calculated, and a function graph is constructed;
[0047] Step S6: Then determine the location point W where the fire monitoring point is located, take the location point W as the center, r is the fire command and dispatch radius, a is the minimum dispatch unit distance of the fire command and dispatch radius, and obtain r=a, 2a, 3a, ..., na distances respectively. The total maximum fire extinguishing index M of the micro fire station within the fire command and dispatch range is M={M1, M2, M3, ..., M n}; The total maximum fire extinguishing index of the micro fire station within the fire command and dispatch range is M = m1 + m2 + ... + m m The total maximum fire extinguishing index M of the micro fire stations within the fire command and dispatch range is equal to the sum of the maximum fire extinguishing indexes of the reserves of each micro fire station within the fire command and dispatch range;
[0048] Step S7: Based on the historical big data of the fire resource database, the reference time t of each dispatch minimum dispatch unit distance a is set, then r = a, 2a, 3a, ..., na, the corresponding required dispatch time T = t, 2t, 3t, ..., nt, with the dispatch time T as the horizontal axis and the total maximum fire extinguishing index M of the micro fire station as the vertical axis, a plane rectangular coordinate system is established, and (t, M1), (2t, M2), (3t, M3), ..., (nt, M4) are marked in the plane rectangular coordinate system respectively. n ), then connect all the marked points to construct a line graph of the dispatch fire extinguishing index;
[0049] Step S8: Compare the constructed function graph of the fire intensity increasing over time with the dispatch fire extinguishing index line graph, analyze and determine the fire command dispatch radius r corresponding to the optimal dispatch range j ;
[0050] Step S9: Based on the judgment result, when the system detects a fire, the system takes the location W of the currently determined fire monitoring point as the center, r j The coverage area is of radius, and all micro fire stations in the coverage area are commanded to go to the location W where the fire monitoring point is located to carry out fire extinguishing.
[0051] The method for dividing the fire spread speed of a building in step S3 is as follows: the fire resistance level of a building corresponds to four base numbers Ω1, Ω2, Ω3, and Ω4, respectively, and the fire resistance level Ω of the building where the fire occurs is obtained. i , where i = 1, 2, 3, 4, and then match the building usage density ρ in the area according to the monitoring point, through the formula k = ρ·Ω i Calculate the fire spread rate coefficient of the fire point; where the building usage density ρ is proportional to the fire spread rate coefficient k. The greater the regional density of the fire, the more likely it is that the area is densely populated and there are many items in the building, so the fire is more likely to spread. On the contrary, if the regional density of the fire is very small, it means that the area where the fire occurred may be an empty room with few combustible materials around, and the fire spreads more slowly. By dividing the building fire spread rate and accurately determining it to a specific fire monitoring point, the same building can be further divided into several areas at each fire monitoring point based on the technology of dividing different building component types into different basic spread rate levels, and accurate data can be obtained based on the regional usage density, so that a more accurate fire spread rate can be predicted, providing a complete data premise for subsequent accurate control of fire dispatch.
[0052] In step S5, the exponential relationship between the fire intensity and the time is:
[0053]
[0054] In the formula, H is the fire index. The larger the fire index is, the greater the fire intensity is. T is the time value. When T=0, H=C, which means that when the fire is detected, the initial fire index value is C. At the same time, k>1 is satisfied. Therefore, the function graph corresponding to the exponential relationship between the fire intensity and time is: The larger the time is, the greater the fire index H is.
[0055] The time T2 recorded when the fire is detected is taken as the horizontal axis, and the predicted fire index H is taken as the vertical axis. The function graph is constructed based on the exponential relationship between the fire intensity and the growth of the fire over time.
[0056] Step S8 specifically includes:
[0057] The constructed function graph of the fire intensity growing over time is compared with the dispatch fire extinguishing index line graph, and the minimum value T corresponding to the horizontal coordinate T when M≥H is satisfied in the comparison image is searched. min , output the two sets of marked points ((∈-1)t, M) whose horizontal coordinates are adjacent in the fire extinguishing index line image ∈-1 ) and (∈t, M ∈ ), then determine ∈t as the optimal dispatch time for analysis, then determine the fire command dispatch radius r corresponding to the optimal dispatch range j =∈a;
[0058] When a fire occurs, by analyzing the fire spread speed at the fire point and determining the size of the fire at the time of fire monitoring, the relationship between the fire intensity and time is constructed. Then, based on the historical big data of the fire resource database, the maximum fire extinguishing capacity that can be dispatched in different dispatch ranges is calculated. However, since the dispatch ranges corresponding to different maximum fire extinguishing capacities are different, and the dispatch time required for different dispatch ranges is different, the relationship between the maximum fire extinguishing capacity and time is further transformed and constructed. Finally, the fire intensity that grows over time and the maximum fire extinguishing capacity that can be dispatched over time are dynamically tracked and compared. After capturing and predicting a certain period of time, although the fire has grown, the maximum fire extinguishing capacity dispatched after this period has caught up with the growing fire intensity. This can achieve the fastest completion of fire command and dispatch within the fire extinguishing capacity, and minimize the dispatch range to reduce unnecessary labor and the impact on fire extinguishing resources in other areas.
[0059] Because urban micro fire stations generally have the characteristics of relatively dense deployment and flexible mobility but limited fire-fighting resources at a single station, this system is effectively suitable for the fire command and dispatch operations of urban micro fire stations. By linking the command and dispatch of all micro fire station fire-fighting resources within a certain range, it can quickly and efficiently reach the fire scene to provide manpower.
[0060] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.
[0061] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A fire command and dispatch system based on the Internet of Things, comprising a fire resource database, a fire growth index analysis module, a dispatch fire extinguishing index analysis module and a dispatch range output module, characterized in that: The fire resource database is used to monitor and collect data on urban fire resources, the fire monitoring module is used to store and record urban building information and fire resource information of micro fire stations, the fire growth index analysis module is suitable for analyzing and predicting the size of fire growth when a fire occurs, the dispatching fire extinguishing index analysis module is used to analyze the fire extinguishing capabilities achieved under different dispatching ranges, and the dispatching range output module is used to determine the dispatching range for outputting the final decision based on the fire growth prediction and the fire dispatching fire extinguishing capability analysis results. The fire resource database, fire growth index analysis module, dispatching fire extinguishing index analysis module and dispatching range output module are electrically connected.
2. The fire command and dispatch system based on the Internet of Things according to claim 1 is characterized in that: The fire resource database includes a micro fire station registration module, a building information registration module, a fire resource information sorting module and a fire monitoring module. The micro fire station registration module is used to register and connect the micro fire station information in the city to the fire resource database. The building information registration module is used to register and connect the building information in the city to the fire resource database. The fire resource information sorting module is used to classify and sort the information registered and recorded in the fire resource database and quickly extract the sorted data. The fire monitoring module is used to monitor fires occurring in buildings.
3. The fire command and dispatch system based on the Internet of Things according to claim 1 is characterized in that: The fire growth index analysis module includes a fire spread speed classification module, an initial fire identification module and a fire prediction image construction module. The fire spread speed classification module is used to classify the building fire spread speed according to the building information where the fire monitoring points are deployed. The initial fire identification module is suitable for identifying the size of the monitored fire when a fire occurs in the building. The fire spread speed classification module and the initial fire identification module are both electrically connected to the fire prediction image construction module. The fire prediction image construction module is used to analyze and construct a function image of the fire growth over time.
4. The fire command and dispatch system based on the Internet of Things according to claim 1 is characterized in that: The dispatching fire extinguishing index analysis module includes a dispatching fire extinguishing index statistics module and a fire extinguishing broken line image construction module. The dispatching fire extinguishing index statistics module is used to count the maximum fire extinguishing index sum of the micro fire station according to the dispatching range, and the fire extinguishing broken line image construction module is used to analyze and construct a dispatching fire extinguishing index broken line image based on the fire occurrence point.
5. The fire command and dispatch system based on the Internet of Things according to claim 1 is characterized in that: The dispatch range output module includes a comparison and judgment module and a fire command and dispatch instruction issuing module. The comparison and judgment module is used to compare and analyze the constructed image relationship and judge the fire command and dispatch radius corresponding to the optimal dispatch range. The fire command and dispatch instruction issuing module is used to issue dispatch fire extinguishing instructions to the micro fire stations within the judgment range according to the judgment result of the comparison and judgment module. The comparison and judgment module is electrically connected to the fire command and dispatch instruction issuing module.
6. The fire command and dispatch system based on the Internet of Things according to claim 2 is characterized in that: The fire resource information sorting module further includes a position acquisition submodule, a fire extinguishing index acquisition submodule, a building fire resistance level acquisition submodule and a building use density acquisition submodule. The position acquisition submodule is used to acquire the precise position point of the urban micro fire station, the fire extinguishing index acquisition submodule is used to acquire the maximum fire extinguishing index of each urban micro fire station, the building fire resistance level acquisition submodule is used to acquire the fire resistance level of each building, and the building use density acquisition submodule is used to acquire the area use density inside the building; The fire monitoring module further includes a smoke sensing unit, a thermal imaging unit and a positioning unit. The smoke sensing unit is used to sense and monitor smoke to determine whether a fire has occurred at the corresponding monitoring point. The thermal imaging unit is used to detect the thermal imaging image of the fire. The positioning unit is used to send the location of the fire occurrence point.
7. A dispatching method for a fire command and dispatch system based on the Internet of Things is applied as claimed in any one of claims 1 to 6, characterized in that: include: Step S1: Establish a fire resource database, connect the urban micro fire station and building information to the fire resource database, and integrate the fire resource information of the urban micro fire station, wherein the urban micro fire station information includes the precise location of each micro fire station and the maximum fire extinguishing index m of the reserve; wherein the building information includes the fire resistance grade of the building and the building usage density; Step S2: deploy fire monitoring points in urban buildings, and connect the monitoring data of the building fire monitoring points to the fire resource database; Step S3: according to the building information where the fire monitoring point is deployed, the fire spread speed of the building is divided, and a specific fire spread speed coefficient k is output; Step S4: Real-time monitoring of urban buildings. When a fire is detected, the smoke sensing unit outputs an induction electrical signal, and the thermal imaging unit is activated to perform thermal imaging of the monitoring area, fit the thermal imaging contour, and convert the output into an initial fire size index value C when the fire is detected; Step S5: According to the initial fire intensity index value C and the fire spread speed coefficient k corresponding to the monitoring point where the fire is detected, the exponential relationship between the fire intensity and time is analyzed and calculated, and a function graph is constructed; Step S6: Then determine the location point W where the fire monitoring point is located. With the location point W as the center, r is the fire command and dispatch radius, a is the minimum dispatch unit distance of the fire command and dispatch radius, and when r=a, 2a, 3a, ..., na distances are obtained respectively, the total maximum fire extinguishing index M of the micro fire station within the fire command and dispatch range is M={M1, M2, M3, ..., M n }; Step S7: Based on the historical big data of the fire resource database, the reference time t of each dispatch minimum dispatch unit distance a is set, then r = a, 2a, 3a, ..., na, the corresponding required dispatch time T = t, 2t, 3t, ..., nt, with the dispatch time T as the horizontal axis and the total maximum fire extinguishing index M of the micro fire station as the vertical axis, a plane rectangular coordinate system is established, and (t, M1), (2t, M2), (3t, M3), ..., (nt, M4) are marked in the plane rectangular coordinate system respectively. n ), then connect all the marked points to construct a line graph of the dispatch fire extinguishing index; Step S8: Compare the constructed function graph of the fire intensity increasing over time with the dispatch fire extinguishing index line graph, analyze and determine the fire command dispatch radius r corresponding to the optimal dispatch range j ; Step S9: Based on the judgment result, when the system detects a fire, the system takes the location W of the currently determined fire monitoring point as the center, r j The coverage area is of radius, and all micro fire stations in the coverage area are commanded to go to the location W where the fire monitoring point is located to carry out fire extinguishing.
8. The dispatching method of a fire command and dispatching system based on the Internet of Things according to claim 7 is characterized in that: The method for dividing the fire spread speed of a building in step S3 is as follows: the fire resistance level of a building corresponds to four base numbers Ω1, Ω2, Ω3, and Ω4, respectively, and the fire resistance level Ω of the building where the fire occurs is obtained. i , where i = 1, 2, 3, 4, and then match the building usage density ρ in the area according to the monitoring point, through the formula k = ρ·Ω i Calculate the fire spread rate coefficient at the fire location.
9. The dispatching method of a fire command and dispatching system based on the Internet of Things according to claim 7, characterized in that: In step S5, the exponential relationship between the fire intensity and the time is: In the formula, H is the fire index. The larger the fire index is, the greater the fire intensity is. T is the time value. When T=0, H=C, which means that when the fire is detected, the initial fire index value is C. At the same time, k>1 is satisfied. Therefore, the function graph corresponding to the exponential relationship between the fire intensity and time is: The larger the time is, the greater the fire index H is. The time T2 recorded when the fire is detected is taken as the horizontal axis, and the predicted fire index H is taken as the vertical axis. The function graph is constructed based on the exponential relationship between the fire intensity and the growth of the fire over time.
10. The dispatching method of a fire command and dispatching system based on the Internet of Things according to claim 9, characterized in that: Step S8 specifically includes: The constructed function graph of the fire intensity growing over time is compared with the dispatch fire extinguishing index line graph, and the minimum value T corresponding to the horizontal coordinate T when M≥H is satisfied in the comparison image is searched. min , output the two sets of marked points ((∈-1)t,M) whose horizontal coordinates are adjacent in the fire extinguishing index line image ∈-1 ) and (∈t,M ∈ ), then determine ∈t as the optimal dispatch time for analysis, then determine the fire command dispatch radius r corresponding to the optimal dispatch range j =∈a.