CN115936287B - Urban fire rescue comprehensive treatment method based on big data - Google Patents
Urban fire rescue comprehensive treatment method based on big data Download PDFInfo
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- CN115936287B CN115936287B CN202310225599.8A CN202310225599A CN115936287B CN 115936287 B CN115936287 B CN 115936287B CN 202310225599 A CN202310225599 A CN 202310225599A CN 115936287 B CN115936287 B CN 115936287B
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses a comprehensive urban fire rescue processing method based on big data, which belongs to the field of comprehensive urban fire rescue processing and comprises the steps of utilizing a data processing server to acquire rescue information, wherein the rescue information comprises a rescue target position, a rescue target type and a rescue starting point position; establishing a temporary communication network by taking a rescue target position as a center for covering; establishing an initial rescue route length set in a range covered by a temporary communication network through a data processing server; planning, analyzing and processing the initial rescue route length set to obtain an optimal rescue route; and carrying out comprehensive processing according to the optimal rescue route by utilizing the data processing server. The fire truck can reach the fire scene quickly, and the disaster expansion is avoided; the rescue equipment and personnel are arranged through the collection of accident place information in the early stage, so that resource waste is avoided; and the rescue system can also judge according to the type of the needed rescue target and the surrounding environment of the rescue target when a plurality of dangerous cases occur, so that rescue force is reasonably arranged.
Description
Technical Field
The invention belongs to the field of urban fire rescue comprehensive treatment, and particularly relates to a method for comprehensively treating urban fire rescue based on big data.
Background
The number of the cells in the city is numerous, each cell is managed by adopting independent property, and when a safety accident occurs in one cell, a fire department generally sends out a fire station nearest to the accident place after receiving an alarm to give an alarm, but under the influence of urban traffic specificity, rescue vehicles can sometimes rescue in time to the accident place because of large traffic flow and traffic jam of the selected route; and sometimes, after the rescue vehicle arrives, due to the fact that information communication is not timely, property management prevents the rescue vehicle from entering. Thereby missing the optimal rescue time, enlarging dangerous cases, causing larger economic loss and even threatening the life security of personnel when serious
Therefore, a comprehensive urban fire rescue treatment method based on big data is needed to be designed to solve the problems.
Disclosure of Invention
The invention aims to solve the problem of providing a comprehensive urban fire rescue processing method based on big data, which is particularly suitable for processing and guiding rescue in cities with complex traffic conditions.
In order to solve the technical problems, the invention adopts the following technical scheme:
the urban fire rescue comprehensive treatment method based on big data comprises the following steps:
acquiring rescue information by utilizing a data processing server, wherein the rescue information comprises a rescue target position, a rescue target type and a rescue starting point position;
establishing a temporary communication network by taking the rescue target position as a center for covering;
utilizing the rescue target position as a center of a temporary communication network coverage area;
utilizing the linear distance between the rescue target position and the rescue starting point position as the dividing radius of the temporary communication network coverage area;
obtaining a round coverage area of the temporary communication network by utilizing the center of the coverage area of the temporary communication network and the dividing radius of the coverage area of the temporary communication network;
establishing an initial rescue route length set in a range covered by the temporary communication network through the data processing server;
planning, analyzing and processing the initial rescue route length set to obtain an optimal rescue route;
and carrying out comprehensive processing according to the optimal rescue route by utilizing the data processing server.
Preferably, establishing, by the data processing server, an initial rescue route length set within a range covered by the temporary communication network includes:
retrieving map information of the temporary communication network coverage area stored in the data processing server;
segmenting each rescue route from the rescue starting point position to the rescue target position in the temporary communication network coverage area according to the map information according to intersection nodes, and marking the length of each segmented route of each rescue route;
and calculating the length of the corresponding rescue route by utilizing the number N of the segments of each rescue route and the corresponding length L of each segment to obtain the initial rescue route length set.
The arrangement is convenient for the primary screening of all rescue lines from the rescue starting point position to the rescue target position in the later stage by marking the lines in a segmented mode.
Preferably, planning, analyzing and processing the initial rescue route length set to obtain an optimal rescue route includes:
acquiring the corresponding real-time mobile phone signal density degree and the corresponding real-time mobile phone signal position moving speed in each segment of each rescue route in the initial rescue route length set by utilizing a temporary communication network;
obtaining real-time road traffic flow saturation of each section of each rescue route by using the real-time mobile phone signal intensity;
obtaining real-time road congestion degree of each section of each rescue route by using the mobile phone signal position moving speed;
obtaining the traffic level of each segment by utilizing the real-time road traffic flow saturation and the real-time road congestion degree;
and obtaining an initial alternative route and an initial rescue route based on the traffic level by utilizing the initial rescue route length set.
The arrangement is convenient for acquiring the passing efficiency of vehicles on each road after segmentation.
Preferably, obtaining the traffic level of each segment by using the real-time road traffic saturation and the real-time road congestion degree includes:
the traffic level comprises A, B, C three types, and is specifically classified as:
the traffic level is class A when the traffic of the road vehicles is saturated and the road is congested;
the traffic level is class B when the traffic of the road vehicles is saturated but the road is not congested;
the traffic level is class C when the traffic of the road vehicles is unsaturated but the road is congested;
wherein, the passing efficiency of the class A is higher than that of the class B, and the passing efficiency of the class B is higher than that of the class C;
the road saturation is the ratio of the current number of vehicles to the designed number of vehicles passing on the road surface with the specified length, if the road saturation is more than or equal to 1, the road traffic is saturated, otherwise, the road traffic is unsaturated;
the road congestion degree is the ratio of the average speed of the running vehicle of the current road to the highest running speed designed for the current road, if the road congestion degree is more than or equal to 1, the road is not congested, otherwise, the road congestion degree is congested.
The road traffic efficiency of each section of road is classified through the road saturation and the road congestion degree, so that the traffic efficiency of the whole rescue route is conveniently obtained.
Preferably, the obtaining the initial alternative route and the initial rescue route based on the traffic level by using the initial rescue route length set includes:
sequencing each rescue line in the initial rescue line length set by using a first standard to obtain a second rescue line set;
classifying the second rescue route set by using the passing level to obtain an initial rescue route and an initial alternative route;
the first criterion is that the shortest distance from the rescue starting point position to the rescue target position is used as a first selection condition, and the smallest number of segments is used as a second selection condition;
the classifying the second rescue route set by using the traffic level includes:
the number of the segments belonging to the class A in the initial rescue route segments is T, the number of the segments belonging to the class B is H, and the number of the segments belonging to the class C is K;
when n=t, i.e. all segments belong to class a, the best rescue route;
the best alternative route when n=t+h, i.e. the segment contains both class a and class B;
a primary alternative route when n=t+k, i.e. the segment contains class a and class C;
when n=t+h+k, and T > h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is less than the number of class a segments, a secondary alternative route;
when n=t+h+k, and T is less than or equal to h+k or n=h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is greater than the number of class a segments or the segments comprise only class B and class C, the segments are not taken as rescue route alternatives;
and when the optimal rescue route does not exist, taking the next result as the optimal rescue route.
The arrangement is that routes with high traffic efficiency to low traffic efficiency are orderly arranged according to comprehensive analysis of traffic efficiency on each road after segmentation, so that the optimal rescue route can be conveniently selected.
Preferably, when there are both the first alternative route and the second alternative route that meet the condition n=t+h, and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered in accordance with N1, N2, N3..
Acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
a comparison is made between MB1 and MB2,
when MB1> MB2, the first alternative route is the best alternative route, and the second alternative route is the primary alternative route;
when MB1< MB2, the second alternative route is the best alternative route, and the first alternative route is the primary alternative route;
when there are both the first alternative route and the second alternative route that meet the condition n=t+k, and the number of C-class segments H1 in the first alternative route is the same as the number of C-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered according to N1, N2, N3..
Acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
a comparison is made between MC1 and MC2,
when MC1> MC2, the first alternative route is a primary alternative route, and the second alternative route is a secondary alternative route;
when MC1< MC2, the second alternative route is the primary alternative route, and the first alternative route is the secondary alternative route;
when there are both the first alternative route and the second alternative route meeting the condition n=t+h+k, and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the number of C-class segments K1 in the first alternative route is the same as the number of C-class segments K2 in the second alternative route, it is necessary to sort the segments of the first alternative route and the second alternative route starting from the rescue start point position according to N1, N2, N3...nm;
acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
comparing MB1 and MB2 and MC1 and MC2;
when MB1> MB2, MC1> MC2, and MC2> MB2, the second alternative route is a secondary alternative route;
when MB2> MB1, MC2> MC1, and MC1> MB1, the first alternative route is the secondary alternative route.
The setting is that the analysis and comparison are carried out to the different conditions of each section of route, and the route with the best travel efficiency is screened.
Preferably, the comprehensive processing by the data processing server according to the optimal rescue route includes:
transmitting optimal rescue route information to the rescue vehicle by utilizing a data processing server;
controlling all traffic signal lamps on the optimal rescue route to be in a state allowing traffic by using a data processing server according to the running speed of the rescue vehicle;
and controlling cloud electronic billboards and cloud broadcasting along the optimal rescue route by using the data processing server to broadcast.
By the arrangement, the comprehensive guidance of the vehicle can be realized, and the rescue vehicle can quickly reach the rescue target position.
Preferably, when new rescue information exists, judging whether a circular area covered by a temporary communication network corresponding to the new rescue information overlaps with a circular area covered by a temporary communication network corresponding to the adjacent previous rescue information, if so, establishing a first rescue network and a second rescue network in the temporary communication network corresponding to the adjacent previous rescue information, otherwise, independently establishing the second temporary communication network.
By the arrangement, a network can be established for a plurality of targets to rescue.
Preferably, when the first rescue network and the second rescue network exist, the data management server compares the risk level Z1 of the rescue target covered by the first rescue network with the risk level Z2 of the rescue target covered by the second rescue network, when Z1> Z2, the communication priority of the first rescue network is higher than that of the second rescue network, when Z2> Z1, the communication priority of the second rescue network is higher than that of the first rescue network, and when Z2=Z1, the communication priority of the first rescue network and the second rescue network is the same;
the risk level comparison table of the rescue target is preset in the data processing server, and the limited level of the rescue network is adjusted after the information transmitted back by the communication terminal of the area to which the rescue target belongs is compared with the fire risk level table.
By the arrangement, the priority of the network can be adjusted according to the danger level of the rescue target, the communication smoothness is ensured, the rescue force can be quickly adjusted, and the damage is avoided.
The invention has the advantages and positive effects that:
the method utilizes information transmission between the data processing server and the communication terminal to eliminate the problem of rescue blockage caused by untimely communication, analyzes the rescue route through a temporary communication network established by taking the accident place as the center, further selects the optimal rescue route, and dredges the optimal rescue route, so that the fire truck can quickly reach a fire scene, and the expansion of disaster is avoided; the rescue equipment and personnel are arranged through the collection of accident place information in the early stage, so that resource waste is avoided; and the rescue system can also judge according to the type of the needed rescue target and the surrounding environment of the rescue target when a plurality of dangerous cases occur, so that rescue force is reasonably arranged.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of the urban fire rescue comprehensive treatment method based on big data.
Detailed Description
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
The invention is further described below with reference to the accompanying drawings:
example 1: as shown in fig. 1, the urban fire rescue comprehensive treatment method based on big data comprises the following steps:
s1, acquiring rescue information by utilizing a data processing server, wherein the rescue information comprises a rescue target position, a rescue target type and a rescue starting point position;
s2, establishing a temporary communication network by taking the rescue target position as a center for covering;
s3, establishing an initial rescue route length set in a range covered by the temporary communication network through the data processing server;
s4, planning, analyzing and processing the initial rescue route length set to obtain an optimal rescue route;
s5, comprehensively processing by utilizing the data processing server according to the optimal rescue route.
S1 specifically comprises:
the method comprises the steps that a data processing server is arranged in a city, the data processing server not only has the function of connecting with the Internet, but also can position mobile phone signals through a base station, meanwhile, a communication terminal is arranged in a miniature fire station in the city, after the communication terminal is connected with the data processing server, information transmission can be carried out between the communication terminal and the data processing server, rescue information of a dangerous place in the city can be obtained through the data processing server, such as a network telephone called by any person or a telephone transferred through an operator base station, and rescue target position information, rescue target type information and rescue starting point position information in the telephone are extracted.
S2 specifically comprises:
s2-1, using the rescue target position as a center of a temporary communication network coverage area;
s2-2, utilizing the linear distance between the rescue target position and the rescue starting point position as the dividing radius of the temporary communication network coverage area;
s2-3, obtaining a round coverage area of the temporary communication network by utilizing the dividing radius of the center of the coverage area of the temporary communication network and the coverage area of the temporary communication network.
After the temporary communication network is established, all communication terminals in the coverage area of the temporary communication network are connected with a data processing server in an information transmission manner, then information is sent to the communication terminals in the miniature fire-fighting station to which the rescue target position belongs, the on-duty personnel is informed to go to the rescue target position to confirm the type of the rescue target again, if the rescue target type is fire, the rescue target environment is also required to be confirmed, if the rescue target type is fire, the type of a combustion object is required to be confirmed, and whether other inflammable and explosive objects exist around the combustion object or not is also required to be confirmed, and the information is sent to the data processing server through the communication terminals in time, so that reasonable rescue force is arranged to go to rescue by combining the type of the rescue target and the environment around the rescue target, and the problem of public resource waste or the shortage of rescue force when a second danger occurs around is avoided.
S3 specifically comprises:
s3-1, retrieving map information of the temporary communication network coverage area stored in the data processing server;
the data processing server stores a detailed traffic route map of the whole city, and when the temporary communication network is established, the data processing server calls the traffic route map of the area covered by the temporary communication network by taking the rescue target position as the center.
S3-2, segmenting each rescue route from the rescue starting point position to the rescue target position in the temporary communication network coverage area according to the map information, for example, segmenting the rescue route according to intersection nodes when one rescue route has no intersection point, changing the intersection point into two segments when one intersection point exists, changing the intersection point into a separation point when two intersection points exist, adding one segmentation point corresponding to the rescue route when three segmentation points exist, and marking the length of each segmentation route of each rescue route;
s3-3, calculating the length of the corresponding rescue route by using the segmentation number N of each rescue route and the corresponding length L of each segmentation to obtain the initial rescue route length set.
S4 specifically comprises the following steps:
s4-1, acquiring the corresponding real-time mobile phone signal density degree and the real-time mobile phone signal position moving speed in each segment of each rescue route in the initial rescue route length set according to a temporary communication network by utilizing the function of a base station for positioning mobile phone signals through a data processing server;
s4-2, obtaining real-time road traffic flow saturation of each section of each rescue route by using the real-time mobile phone signal intensity;
s4-3, obtaining real-time road congestion degree of each section of each rescue route by using the mobile phone signal position moving speed;
s4-4, obtaining the traffic level of each segment by utilizing the real-time road traffic flow saturation and the real-time road congestion degree;
wherein, the passing level comprises A, B, C three categories, which are specifically classified as:
the traffic level is class A when the traffic of the road vehicles is saturated and the road is congested;
the traffic level is class B when the traffic of the road vehicles is saturated but the road is not congested;
the traffic level is class C when the traffic of the road vehicles is unsaturated but the road is congested;
in the passing level, the passing efficiency of the class A is higher than that of the class B, and the passing efficiency of the class B is higher than that of the class C;
the road saturation is the ratio of the current number of vehicles to the designed number of vehicles passing on the road surface with the specified length, if the road saturation is more than or equal to 1, the road traffic is saturated, otherwise, the road traffic is unsaturated;
the road congestion degree is the ratio of the average speed of the running vehicle of the current road to the highest running speed designed for the current road, if the road congestion degree is more than or equal to 1, the road is not congested, otherwise, the road congestion degree is congested.
S4-5, obtaining an initial alternative route and an initial rescue route based on the traffic level by utilizing the initial rescue route length set.
S4-5, specifically comprising:
s4-5-1, sequencing each rescue line in the initial rescue line length set by using a first standard to obtain a second rescue line set;
s4-5-2, classifying the second rescue route set by using the passing level to obtain an initial rescue route and an initial alternative route;
the first criterion is that the shortest distance from the rescue starting point position to the rescue target position is used as a first selection condition, and the smallest number of segments is used as a second selection condition;
the classifying the second rescue route set by using the traffic level includes:
the number of the segments belonging to the class A in the initial rescue route segments is T, the number of the segments belonging to the class B is H, and the number of the segments belonging to the class C is K;
when n=t, i.e. all segments belong to class a, the best rescue route;
the best alternative route when n=t+h, i.e. the segment contains both class a and class B;
a primary alternative route when n=t+k, i.e. the segment contains class a and class C;
when n=t+h+k, and T > h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is less than the number of class a segments, a secondary alternative route;
when n=t+h+k, and T is less than or equal to h+k or n=h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is greater than the number of class a segments or the segments comprise only class B and class C, the segments are not taken as rescue route alternatives;
and when the optimal rescue route does not exist, taking the next result as the optimal rescue route.
When there are both the first alternative route and the second alternative route that meet the condition n=t+h, and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered according to N1, N2, N3..
Acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
a comparison is made between MB1 and MB2,
when MB1> MB2, the first alternative route is the best alternative route, and the second alternative route is the primary alternative route;
when MB1< MB2, the second alternative route is the best alternative route, and the first alternative route is the primary alternative route;
when there are both the first alternative route and the second alternative route that meet the condition n=t+k, and the number of C-class segments H1 in the first alternative route is the same as the number of C-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered according to N1, N2, N3..
Acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
a comparison is made between MC1 and MC2,
when MC1> MC2, the first alternative route is a primary alternative route, and the second alternative route is a secondary alternative route;
when MC1< MC2, the second alternative route is the primary alternative route, and the first alternative route is the secondary alternative route;
when there are both the first alternative route and the second alternative route meeting the condition n=t+h+k, and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the number of C-class segments K1 in the first alternative route is the same as the number of C-class segments K2 in the second alternative route, it is necessary to sort the segments of the first alternative route and the second alternative route starting from the rescue start point position according to N1, N2, N3...nm;
acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
comparing MB1 and MB2 and MC1 and MC2;
when MB1> MB2, MC1> MC2, and MC2> MB2, the second alternative route is a secondary alternative route;
when MB2> MB1, MC2> MC1, and MC1> MB1, the first alternative route is the secondary alternative route.
S5 specifically comprises the following steps:
s5-1, transmitting optimal rescue route information to a rescue vehicle by utilizing a data processing server;
s5-2, controlling all traffic signal lamps on the optimal rescue route to be in a state of allowing traffic by using a data processing server according to the running speed of the rescue vehicle;
s5-3, utilizing a data processing server to control a cloud electronic billboard and a cloud broadcast along the optimal rescue route to broadcast, wherein the broadcast content is the driving direction of the rescue vehicle and the countdown of the travel of the rescue vehicle, the cloud electronic billboard prompts through countdown display and voice, and the cloud broadcast is through public settings distributed on the optimal rescue route, such as a red-green lamp with a sound prompt function, a public transport station and monitoring equipment with a voice broadcast function, and simultaneously, the cloud electronic billboard also broadcasts through broadcasting, and warns pedestrians and vehicles on the optimal rescue route through various prompt modes.
And the temporary communication network is connected with all communication terminals distributed in the urban miniature fire station in the coverage area of the temporary communication network, the data processing server can also send information to the communication terminals near the optimal rescue route through the temporary communication network, inform the operator on duty to go to the optimal rescue route to assist in dredging traffic, especially dredge some road sections without traffic signal lamp control, facilitate the rapid passing of rescue vehicles, and inform the communication terminals of the area where the rescue target position belongs, so that the operator on duty can fully open all fire-fighting channel protection doors on the optimal rescue route, and the rescue vehicles can conveniently and rapidly reach the rescue target position.
When new rescue information exists, the data processing server firstly judges whether a circular area covered by a temporary communication network corresponding to the new rescue information is overlapped with a circular area covered by a temporary communication network corresponding to the adjacent previous rescue information, if so, and if the overlapped area exceeds 40%, a first rescue network and a second rescue network are built in the temporary communication network corresponding to the adjacent previous rescue information, otherwise, a second temporary communication network is built independently.
When the overlapped area exceeds 40%, and a first rescue network and the second rescue network are established in a first temporary passing network, the data management server compares the risk level Z1 of the rescue target type covered by the first rescue network with the risk level Z2 of the rescue target type covered by the second rescue network, when Z1> Z2, the communication priority of the first rescue network is higher than that of the second rescue network, when Z2> Z1, the communication priority of the second rescue network is higher than that of the first rescue network, and when Z2 = Z1, the communication priority of the first rescue network and the second rescue network is the same;
the risk level comparison table of the rescue target is preset in the data processing server, and is used for comparing the information transmitted back by the communication terminal of the area to which the rescue target belongs with fire risk level classification and then adjusting the limited level of the rescue network.
Fire hazard classes are classified as follows:
1. light risk level: old people building, infant building, hotel and office building with building height of 24m or less. A building with a closed system is arranged only on the walkway, etc.
2. Medium risk level: high-rise civil building: hotels, office buildings, complex buildings, postal buildings, financial telecommunications buildings, command and dispatch buildings, broadcast television buildings (towers), etc.
2.1 public buildings (including single and multiple high floors): hospitals, nursing homes, libraries (except for book libraries), archives, exhibition halls (except for stages), movie theaters, concert halls, auditoriums (except for stages) and other entertainment venues, buildings of railway stations, airports and wharfs, shops with total building areas of less than 5000 square meters, underground shops with total building areas of less than 1000 square meters, and the like.
2.2, cultural heritage building: wood structure ancient architecture, national cultural relic protection units, and the like.
2.3, industrial building: factory material preparation and production workshops for foods, household appliances, glass products and the like, and building components such as refrigerators, steel roof trusses and the like.
2.4, civil architecture: book store, stage (except for grape trellis), car parking lot, market with total building area of 5000 square meter or more, underground market with total building area of 1000 square meter or more, etc.
2.5, industrial building: the production process includes the steps of preparing materials and production workshops of factories such as cotton, wool, hemp and chemical fiber spinning, fabrics and products, wood ware and plywood, grain processing, tobacco and products, drinking wine (except beer), leather and products, paper making and paper products, pharmacy and the like.
3. Serious risk level: stock and workshops in factories such as printing plants, alcohol products and flammable liquid products.
3.1, flammable liquid spraying operation area, solid inflammable objects, flammable aerosol products, solvents, paints, asphalt products and other factory material preparation and production workshops, studio and lower part of stage 'grape trellis'.
4. Warehouse hazard level: food, tobacco and wine, wooden case, incombustible and nonflammable articles packaged by cardboard box, shelf area of warehouse type market, etc.
4.1, wood, paper, leather, grains and products, cotton, wool, hemp and products, household appliances, cables, B group plastics and rubber and products thereof, steel-plastic mixed material products, incombustible articles packaged by various plastic bottle boxes, warehouses for mixing and storing various articles and the like.
4.2, group A plastics and rubber, products thereof, asphalt products and the like.
Wherein, when flammable and explosive dangerous goods are found around the rescue target, the dangerous level needs to be adjusted up to a level, such as a light dangerous level when a hotel with a building height of 24m or below breaks out a fire, and a medium dangerous level when a gas station or a timber warehouse exists beside the hotel with the fire, so as to adjust rescue force and avoid accident expansion.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (7)
1. The urban fire rescue comprehensive treatment method based on big data is characterized by comprising the following steps of:
s1, acquiring rescue information by utilizing a data processing server, wherein the rescue information comprises a rescue target position, a rescue target type and a rescue starting point position;
s2, establishing a temporary communication network by taking the rescue target position as a center for covering;
s2-1, using the rescue target position as a center of a temporary communication network coverage area;
s2-2, utilizing the linear distance between the rescue target position and the rescue starting point position as the dividing radius of the temporary communication network coverage area;
s2-3, obtaining a round coverage area of the temporary communication network by utilizing the center of the coverage area of the temporary communication network and the dividing radius of the coverage area of the temporary communication network;
s3, establishing an initial rescue route length set in a range covered by the temporary communication network through the data processing server;
s3-1, retrieving map information of the temporary communication network coverage area stored in the data processing server;
s3-2, segmenting each rescue route from the rescue starting point position to the rescue target position in the temporary communication network coverage area according to the map information according to intersection nodes, and marking the length of each segmented route of each rescue route;
s3-3, calculating the length of the corresponding rescue route by using the number N of the segments of each rescue route and the corresponding length L of each segment to obtain the initial rescue route length set;
s4, planning, analyzing and processing the initial rescue route length set to obtain an optimal rescue route;
s4-1, acquiring the corresponding real-time mobile phone signal density degree and the real-time mobile phone signal position moving speed in each segment of each rescue route in the initial rescue route length set by utilizing a temporary communication network;
s4-2, obtaining real-time road traffic flow saturation of each section of each rescue route by using the real-time mobile phone signal intensity;
s4-3, obtaining real-time road congestion degree of each section of each rescue route by using the mobile phone signal position moving speed;
s4-4, obtaining the traffic level of each segment by utilizing the real-time road traffic flow saturation and the real-time road congestion degree;
s4-5, obtaining an initial alternative route and an initial rescue route based on the passing level by utilizing the initial rescue route length set;
s4-5-1, sequencing each rescue line in the initial rescue line length set by using a first standard to obtain a second rescue line set;
s4-5-2, classifying the second rescue route set by using the passing level to obtain an initial rescue route and an initial alternative route;
the first criterion is that the shortest distance from the rescue starting point position to the rescue target position is used as a first selection condition, and the smallest number of segments is used as a second selection condition;
s5, comprehensively processing by utilizing the data processing server according to the optimal rescue route.
2. The general processing method for urban fire rescue based on big data according to claim 1, wherein obtaining the traffic level of each segment by using the real-time road traffic saturation and the real-time road congestion degree comprises:
the traffic level comprises A, B, C three types, and is specifically classified as:
the traffic level is class A when the traffic of the road vehicles is saturated and the road is congested;
the traffic level is class B when the traffic of the road vehicles is saturated but the road is not congested;
the traffic level is class C when the traffic of the road vehicles is unsaturated but the road is congested;
wherein, the passing efficiency of the class A is higher than that of the class B, and the passing efficiency of the class B is higher than that of the class C;
the road saturation is the ratio of the current number of vehicles to the designed number of vehicles passing on the road surface with the specified length, if the road saturation is more than or equal to 1, the road traffic is saturated, otherwise, the road traffic is unsaturated;
the road congestion degree is the ratio of the average speed of the running vehicle of the current road to the highest running speed designed for the current road, if the road congestion degree is more than or equal to 1, the road is not congested, otherwise, the road congestion degree is congested.
3. The general urban fire rescue processing method based on big data according to claim 2, wherein classifying the second rescue route set using the traffic level comprises:
the number of the segments belonging to the class A in the initial rescue route segments is T, the number of the segments belonging to the class B is H, and the number of the segments belonging to the class C is K;
when n=t, i.e. all segments belong to class a, the best rescue route;
the best alternative route when n=t+h, i.e. the segment contains both class a and class B;
a primary alternative route when n=t+k, i.e. the segment contains class a and class C;
when n=t+h+k, and T > h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is less than the number of class a segments, a secondary alternative route;
when n=t+h+k, and T is less than or equal to h+k or n=h+k, i.e. the segments comprise class a, class B and class C, and the sum of the number of class B and class C segments is greater than the number of class a segments or the segments comprise only class B and class C, the segments are not taken as rescue route alternatives;
and when the optimal rescue route does not exist, taking the next result as the optimal rescue route.
4. The general urban fire rescue processing method based on big data according to claim 3, wherein when a first alternative route and a second alternative route which meet the condition n=t+h coexist and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered according to N1, N2, N3...nm;
acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
a comparison is made between MB1 and MB2,
when MB1> MB2, the first alternative route is the best alternative route, and the second alternative route is the primary alternative route;
when MB1< MB2, the second alternative route is the best alternative route, and the first alternative route is the primary alternative route;
when there are both the first alternative route and the second alternative route that meet the condition n=t+k, and the number of C-class segments H1 in the first alternative route is the same as the number of C-class segments H2 in the second alternative route, the segments of the first alternative route and the second alternative route from the rescue start point position need to be ordered according to N1, N2, N3..
Acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
a comparison is made between MC1 and MC2,
when MC1> MC2, the first alternative route is a primary alternative route, and the second alternative route is a secondary alternative route;
when MC1< MC2, the second alternative route is the primary alternative route, and the first alternative route is the secondary alternative route;
when there are both the first alternative route and the second alternative route meeting the condition n=t+h+k, and the number of B-class segments H1 in the first alternative route is the same as the number of B-class segments H2 in the second alternative route, the number of C-class segments K1 in the first alternative route is the same as the number of C-class segments K2 in the second alternative route, it is necessary to sort the segments of the first alternative route and the second alternative route starting from the rescue start point position according to N1, N2, N3...nm;
acquiring a position sequence number MB1 with the minimum B-class segmentation in a first alternative route;
acquiring a position sequence number MB2 with the minimum B-class segmentation in the second alternative route;
acquiring a position serial number MC1 with the smallest C-class segmentation in a first alternative route;
acquiring a position serial number MC2 with the smallest C-class segmentation in a second alternative route;
comparing MB1 and MB2 and MC1 and MC2;
when MB1> MB2, MC1> MC2, and MC2> MB2, the second alternative route is a secondary alternative route;
when MB2> MB1, MC2> MC1, and MC1> MB1, the first alternative route is the secondary alternative route.
5. The general processing method for urban fire rescue based on big data according to claim 4, wherein the general processing according to the optimal rescue route using the data processing server comprises:
s5-1, transmitting optimal rescue route information to a rescue vehicle by utilizing a data processing server;
s5-2, controlling all traffic signal lamps on the optimal rescue route to be in a state of allowing traffic by using a data processing server according to the running speed of the rescue vehicle;
s5-3, utilizing the data processing server to control cloud electronic billboards and cloud broadcasting along the optimal rescue route for broadcasting.
6. The general processing method for urban fire rescue based on big data according to claim 1, further comprising:
connecting all communication terminals distributed in the urban miniature fire station in the coverage area of the temporary communication network through the temporary communication network;
when new rescue information exists, judging whether a circular area covered by a temporary communication network corresponding to the new rescue information overlaps with a circular area covered by a temporary communication network corresponding to the adjacent previous rescue information, if so, establishing a first rescue network and a second rescue network in the temporary communication network corresponding to the adjacent previous rescue information, otherwise, independently establishing the second temporary communication network.
7. The general urban fire rescue processing method based on big data according to claim 6, wherein when the first rescue network and the second rescue network exist, the data management server compares a risk level Z1 of a rescue target covered by the first rescue network with a risk level Z2 of a rescue target covered by the second rescue network, when Z1> Z2, the communication priority of the first rescue network will be higher than that of the second rescue network, when Z2> Z1, the communication priority of the second rescue network will be higher than that of the first rescue network, when z2=z1, the first rescue network and the second rescue network are the same;
the system comprises a data processing server, a communication terminal, a fire hazard level comparison table, a rescue network, a fire hazard level comparison table, a data processing server and a rescue network, wherein the hazard level comparison table of the rescue target is preset in the data processing server, and the priority level of the rescue network is adjusted according to information transmitted back by the communication terminal in an area to which the rescue target belongs.
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| CN112085265A (en) * | 2020-08-28 | 2020-12-15 | 深圳市富思源智慧消防股份有限公司 | Fire rescue guiding method, system, device and computer readable storage medium |
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