CN111008781A - Resource scheduling method applied to fire fighting field - Google Patents
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Abstract
The invention provides a resource scheduling method applied to the field of fire fighting. According to the invention, by uniformly collecting data information of multi-party emergency rescue resources, once an alarm condition occurs, the optimal plan is matched according to parameters such as alarm condition factors and the like through alarm condition data analysis. The method has the advantages of comprehensively managing the targeted plans according to different types and levels of the alarms, having flexible design structure, managing various factors under different types of alarms, and bringing the plans into standard management. Once the plan is determined, related resources are directly dispatched, and an all-around and targeted one-click scheduling system is really achieved. And the real-time rescue data is collected to the intelligent command and dispatching platform, and the command center can realize emergency rescue in the shortest time.
Description
Technical Field
The invention belongs to the technical field of emergency fire fighting, and particularly relates to a resource scheduling method applied to the field of fire fighting.
Background
Fire is one of the most common major disasters threatening public safety in the world today. It poses a life threat to human society and also causes serious property loss. With the continuous development of social economy, the risk factors causing fire hazard are increasing, and the hazard of the fire hazard is larger and larger.
According to the introduction of data provided by the 'world fire statistics center' of the united nations, the loss caused by fire doubles in less than 7 years in the united states, 16 years in japan on average, and 12 years in china on average. According to statistics, the average fire loss in 70 years is less than 2.5 million yuan, and the average fire loss in 80 years is less than 3.2 million yuan. Since the 90 s, especially 1993, the direct property loss from fire has risen to hundreds of millions of yuan per year, with 2000 deaths per year.
After entering the new century, economic construction is rapidly increased, higher requirements are put forward for fire protection, and the fire hazard harms human life and health and hinders economic prosperity and development, so that the continuously expanded fire safety requirement is generated, and the fire protection system is a direct guide and original power for fire science and fire protection technology development innovation. Once a fire occurs, the efficiency of fire fighting is effectively improved, and minimizing the loss of human life and property is one of the major issues facing fire fighting systems.
Disclosure of Invention
The invention provides a resource scheduling method; the resource scheduling method is particularly applied to the field of fire fighting, resources are automatically scheduled by uniformly collecting data information of multi-party emergency rescue resources, the intelligent degree is high, the scheduling time is short, and the accuracy is high.
In order to solve the technical problems, the invention adopts the technical scheme that: a resource scheduling method applied to the fire fighting field comprises the following steps,
s1: collecting warning condition basic information;
s2: analyzing the warning condition basic information and grading the warning condition;
s3: matching the structured plan according to the alert level;
s4: generating a dispatching scheme according to the structured plan;
s5: and starting the dispatching scheme.
Further, the S1 includes the following steps,
s11: collecting related information of alarm time, alarm location, alarm casualties, alarm weather and alarm peripheral resources in real time through sensors with various specifications;
s12: and transmitting the various related information to a server in real time.
Further, the S2 includes the following steps,
s21: the server uses the collected warning condition basic information to match warning condition factors through one or more of a contrast method, a cross method and an dimensionality increasing method;
s22: matching an optimal path according to the warning condition factor;
s23: and calculating the warning situation grade according to the optimal path.
Further, the matching method of S3 includes the following steps:
s31: describing whether the two types of factors are matched or not by adopting a function with a value range of (0,1), wherein the difference is larger when the result is closer to 0, and the difference is closer when the result is closer to 1;
s32: assuming two types of factors A and B, the parameters of A are (μ A, σ A) and the parameters of B are (μ B, σ B), and the return value of the function calculation formula is:
wherein the value of c can be calculated by the following formula:
；
s33: the e indexes of the two factors A and the e index of the B are within a tolerance range;
s34: the values of d for both types of factors A and B are also within tolerance.
Further, the S4 includes the following steps,
s41: predicting the development trend of the alert condition, and updating the dispatch scheme in real time;
s42: and analyzing the dispatching route according to the specific resource matched with the structured plan.
Further, the S5 includes the following steps,
s51: the server sends the dispatching information to the terminal for dispatching the resources, so that the resources are dispatched quickly;
s52: and repeatedly starting a new dispatching scheme according to the relevant information updated in real time.
Further, the method also comprises the following steps,
s6: and counting the dispatched resources, generating dispatch history, providing basis for subsequent dispatching, and forming dispatch flow history data for manual analysis.
Furthermore, the invention also provides a device for operating the data processing method.
Further, the present invention also provides an apparatus comprising a memory, a processor and an algorithm stored in the memory and executable on the processor, the processor implementing the data processing method according to any one of claims 1 to 7 when executing the computer program.
Further, the present invention also provides a computer-readable storage medium storing a computer algorithm which, when executed by a processor, implements the data processing method of any one of claims 1 to 7.
The invention has the advantages and positive effects that:
1. according to the invention, by uniformly collecting data information of multi-party emergency rescue resources, once an alarm condition occurs, the optimal plan is matched according to parameters such as alarm condition factors and the like through alarm condition data analysis. The method has the advantages of comprehensively managing the targeted plans according to different types and levels of the alarms, having flexible design structure, managing various factors under different types of alarms, and bringing the plans into standard management. Once the plan is determined, related resources are directly dispatched, and an all-around and targeted one-click scheduling system is really achieved. The method provides reliable basis for scientifically making emergency rescue decisions, dispatch resources immediately receive dispatch information and collect real-time rescue data to the intelligent command and dispatch platform, and a command center can realize emergency rescue in the shortest time.
2. The invention utilizes various sensors to comprehensively monitor the relevant information of the alarm condition center in real time and send the information to the server of the command center in time, really realizes that the alarm condition is taken as the center and the resource is directly matched with the resource points for resource allocation, does not need manual selection and has high allocation efficiency.
3. The invention utilizes various analysis methods such as a contrast method, a cross method, an dimension increasing method and the like to comprehensively analyze the acquired data so as to match alarm condition factors and improve the matching precision. And calculating the alarm factors successfully matched to find all the alarm factors which best meet the conditions, and then classifying the alarms according to a plurality of rules bound by the alarm factors so as to facilitate the production of dispatch schemes.
4. The invention plans routes from all the resource locations to the alarm situation generating place according to the matched specific resources in the structured plan, calculates the best route for use according to the distance of the current route, road conditions and weather conditions, and guides the resources to quickly reach the alarm situation site.
5. The invention realizes intelligent dispatch by one-key dispatching, can carry out one-key dispatching for multiple times, intelligently analyzes the current alarm situation according to the progress of the alarm situation, provides a dispatch-increasing scheme in real time and has foresight property.
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FIG. 1 is an overall flow diagram of an embodiment of the present invention.
Detailed Description
Embodiments of the invention are further described below with reference to the accompanying drawings:
as shown in fig. 1, a resource scheduling method applied to the field of fire protection mainly aims at the problem that resources such as vehicles, personnel, medicaments, equipment and the like are difficult to schedule when an alarm occurs, and matches an optimal plan according to parameters such as alarm factors, places, time, resource types and the like through alarm data analysis. The method has the advantages of comprehensively managing the targeted plans according to different types and levels of the alarms, having flexible design structure, managing various factors under different types of alarms, and bringing the plans into standard management. Once the plan is determined, related resources can be directly dispatched, and a one-key scheduling system which is all-around and has pertinence is really achieved, and the method specifically comprises the following steps:
s1: collecting alarm condition basic information, and collecting all alarm condition related data of all types and each moment.
S11: the method comprises the steps of collecting relevant information such as alarm time, alarm places, alarm casualties, dispatched resources, alarm weather, alarm peripheral resources and the like in real time through sensors with various specifications, wherein the peripheral resources comprise fire departments, fire-fighting facilities, key units, personnel, vehicles and the like.
S12: and transmitting the various related information to the command console server in real time.
S2: and analyzing the warning condition basic information and grading the warning condition.
S21: and the command console server uses the acquired warning condition basic information to match warning condition factors through one or more of a contrast method, a cross method and an dimensionality increasing method.
The comparison method is an analysis method for showing the difference between the actual number and the base number by comparing the actual number and the base number so as to know the performance and the problems of economic activities. The currently collected data and the rules of the alarm situation judging scheme are compared to analyze the data.
Specifically, taking the number of casualties as an example, the maximum deviation value allowed by two times of sampling is determined and is set as S,
then each time a new value is detected it is determined:
if the difference between the current value and the previous value is greater than S, the current value is valid;
if the difference between the current value and the previous value is less than or equal to S, the current value is invalid, the current value is discarded, and the previous value is used to replace the current value.
The cross method is to compare data in the transverse direction and in the longitudinal direction. The cross analysis method is to perform cross presentation on data from multiple dimensions and perform multi-angle combined analysis. Here we want to analyze multiple types of data, using a contrast method on a single type of data, and multiple types of data using a cross analysis method to match the corresponding plans.
Specifically, taking the number of dead people as an example, N sampling values are continuously taken to perform arithmetic mean operation for transverse comparison.
When the value of N is larger: the occurrence probability of mutation dangerous cases is high;
when the value of N is smaller: the mutation risk occurrence probability is low.
The base range of N varies depending on the alert factor.
And setting the plurality of warning condition factors as M, and performing longitudinal comparison.
For example, at the alert level, a plurality of M's are compared, where M includes: death, injury and property loss.
The method is particularly important, more than 30 people die, more than 100 people are seriously injured, or more than 1 billion yuan of direct property loss is caused.
The fire disaster is serious, more than 10 and less than 30 people die, more than 50 and less than 100 people are seriously injured, or more than 5000 ten thousand and less than 1 hundred million direct property loss.
In a large fire, more than 3 and less than 10 people die, or more than 10 and less than 50 people are seriously injured, or more than 1000 million and less than 5000 million direct property losses.
Generally, the fire disaster is that less than 3 people die, less than 10 people are seriously injured, or less than 1000 ten thousand people are directly lost.
The dimension increasing method means that when the dimension of the user can not explain the problem well, the user needs to do an operation on the data and add an index.
The alarm condition factor is added to the matching rule, and the alarm condition factor is a large class of alarm condition data which is more easily summarized according to a multi-class data specification, and comprises the following steps: basic building information, casualties, ignition area, disaster types, sudden change dangerous situations, important attention and the like. And matching the warning condition factors by using the acquired basic data through the three data analysis methods.
S22: and matching the optimal path according to the warning condition factor.
And matching the optimal path, namely calculating the alarm condition factors successfully matched to find all the alarm condition factors which best meet the conditions.
S23: and calculating the warning situation grade according to the optimal path.
According to the method, the warning condition is classified into 4 levels, different warning condition factor combinations are combined, and different levels are calculated.
Specifically, the alert level of the present embodiment is specified as follows:
the method is particularly important, more than 30 people die, more than 100 people are seriously injured, or more than 1 billion yuan of direct property loss is caused.
The fire disaster is serious, more than 10 and less than 30 people die, more than 50 and less than 100 people are seriously injured, or more than 5000 ten thousand and less than 1 hundred million direct property loss.
In a large fire, more than 3 and less than 10 people die, or more than 10 and less than 50 people are seriously injured, or more than 1000 million and less than 5000 million direct property losses.
Generally, the fire disaster is that less than 3 people die, less than 10 people are seriously injured, or less than 1000 ten thousand people are directly lost.
S3: and matching a structured plan according to the alarm level, wherein the structured plan refers to the type and the quantity of resource allocation proposed aiming at different alarm factors and alarm levels.
The warning condition factors are matched, the warning condition grade is calculated, the structured plan can be determined according to the data, the available resources on the periphery are analyzed by taking the warning condition as a central point according to the resources needing to be dispatched in the plan, the matching is carried out according to factors such as the warning condition distance, the resource type and the resource quantity, the resource location point is locked, and the support is provided for the subsequent one-key dispatching.
S31: accurate plan matching can bring more effective rescue measures, so when the plans are automatically matched, the plans which most meet the conditions can be matched as far as possible. Specifically, the system uses a function with a value range of (0,1) to describe whether the two types of factors match, and the difference is larger when the result is closer to 0, and the difference is closer when the result is closer to 1.
S32: assuming two types of factors A and B, the parameters of A are (μ A, σ A) and the parameters of B are (μ B, σ B), and the return value of the function calculation formula is:
wherein the value of c can be calculated by the following formula:
。
s33: when the two factors are matched with a greater probability, the e indexes of the two factors A and the e index of the two factors B are required to be within a tolerance range;
s34: at the same time, it is required that the values of d for the two types of factors A and B are also within the tolerance range.
S4: and generating a dispatching scheme according to the structured plan.
S41: predicting the development trend of the alarm situation, updating the dispatching scheme in real time, specifically, carrying out dispatching prediction according to alarm situation related data collected in real time, intelligently matching the dispatching-added resource plan on the basis of the issued resource, and recommending the resource dispatching-added scheme in real time.
S42: and analyzing the dispatching route according to the specific resource matched with the structured plan. Specifically, a route from a resource distribution point to an alarm scene is judged, and the optimal driving route and time are obtained by distinguishing according to the route distance, the road condition and the weather factor.
S43: and generating a specific dispatching scheme according to the plan, the prediction and the route analysis generated by the analysis.
S5: and starting the dispatching scheme, and synthesizing the factors and the matching rules to generate a final dispatching scheme, thereby realizing one-key dispatching.
S51: and the server sends the dispatching information to the terminal for dispatching the resources, so that the resources are dispatched quickly.
S52: and repeatedly starting a new dispatching scheme according to the relevant information updated in real time, wherein the one-touch dispatching can be carried out for multiple times, so that the dispatching for each time is not full dispatching, the steps are repeated according to the collected data, and then the dispatching is compared for several times to predict what resources and quantity are needed.
S6: and counting the dispatched resources, generating dispatch history, providing basis for subsequent dispatching, and forming dispatch flow history data for manual analysis.
The invention has the advantages and positive effects that:
1. according to the invention, by uniformly collecting data information of multi-party emergency rescue resources, once an alarm condition occurs, the optimal plan is matched according to parameters such as alarm condition factors and the like through alarm condition data analysis. The method has the advantages of comprehensively managing the targeted plans according to different types and levels of the alarms, having flexible design structure, managing various factors under different types of alarms, and bringing the plans into standard management. Once the plan is determined, related resources are directly dispatched, and an all-around and targeted one-click scheduling system is really achieved. The method provides reliable basis for scientifically making emergency rescue decisions, dispatch resources immediately receive dispatch information and collect real-time rescue data to the intelligent command and dispatch platform, and a command center can realize emergency rescue in the shortest time.
2. The invention utilizes various sensors to comprehensively monitor the relevant information of the alarm condition center in real time and send the information to the server of the command center in time, really realizes that the alarm condition is taken as the center and the resource is directly matched with the resource points for resource allocation, does not need manual selection and has high allocation efficiency.
3. The invention utilizes various analysis methods such as a contrast method, a cross method, an dimension increasing method and the like to comprehensively analyze the acquired data so as to match alarm condition factors and improve the matching precision. And calculating the alarm factors successfully matched to find all the alarm factors which best meet the conditions, and then classifying the alarms according to a plurality of rules bound by the alarm factors so as to facilitate the production of dispatch schemes.
4. The invention plans routes from all the resource locations to the alarm situation generating place according to the matched specific resources in the structured plan, calculates the best route for use according to the distance of the current route, road conditions and weather conditions, and guides the resources to quickly reach the alarm situation site.
5. The invention realizes intelligent dispatch by one-key dispatching, can carry out one-key dispatching for multiple times, intelligently analyzes the current alarm situation according to the progress of the alarm situation, provides a dispatch-increasing scheme in real time and has foresight property.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (10)
1. A resource scheduling method applied to the field of fire fighting is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
s1: collecting warning condition basic information;
s2: analyzing the warning condition basic information and grading the warning condition;
s3: matching the structured plan according to the alert level;
s4: generating a dispatching scheme according to the structured plan;
s5: and starting the dispatching scheme.
2. The resource scheduling method applied to the field of fire protection according to claim 1, wherein: the S1 includes the steps of,
s11: collecting related information of alarm time, alarm location, alarm casualties, alarm weather and alarm peripheral resources in real time through sensors with various specifications;
s12: and transmitting the various related information to a server in real time.
3. A resource scheduling method applied to the fire fighting field according to claim 1 or 2, characterized in that: the S2 includes the steps of,
s21: the server uses the collected warning condition basic information to match warning condition factors through one or more of a contrast method, a cross method and an dimensionality increasing method;
s22: matching an optimal path according to the warning condition factor;
s23: and calculating the warning situation grade according to the optimal path.
4. A resource scheduling method applied to the fire fighting field according to claim 1 or 2, characterized in that: the matching method of S3 includes the steps of:
s31: describing whether the two types of factors are matched or not by adopting a function with a value range of (0,1), wherein the difference is larger when the result is closer to 0, and the difference is closer when the result is closer to 1;
s32: assuming two types of factors A and B, the parameters of A are (μ A, σ A) and the parameters of B are (μ B, σ B), and the return value of the function calculation formula is:
wherein the value of c can be calculated by the following formula:
；
s33: the e indexes of the two factors A and the e index of the B are within a tolerance range;
s34: the values of d for both types of factors A and B are also within tolerance.
5. A resource scheduling method applied to the fire fighting field according to claim 1 or 2, characterized in that: the S4 includes the steps of,
s41: predicting the development trend of the alert condition, and updating the dispatch scheme in real time;
s42: and analyzing the dispatching route according to the specific resource matched with the structured plan.
6. A resource scheduling method applied to the fire fighting field according to claim 1 or 2, characterized in that: the S5 includes the steps of,
s51: the server sends the dispatching information to the terminal for dispatching the resources, so that the resources are dispatched quickly;
s52: and repeatedly starting a new dispatching scheme according to the relevant information updated in real time.
7. A resource scheduling method applied to the fire fighting field according to claim 1 or 2, characterized in that: the method also comprises the following steps of,
s6: and counting the dispatched resources, generating dispatch history, providing basis for subsequent dispatching, and forming dispatch flow history data for manual analysis.
8. An apparatus, characterized by: operating the data processing method according to any one of claims 1 to 7.
9. An apparatus comprising a memory, a processor, and an algorithm stored in the memory and executable on the processor, characterized in that: the processor, when executing the computer program, implements the data processing method of any of claims 1 to 7.
10. A computer-readable storage medium storing a computer algorithm, wherein the computer algorithm, when executed by a processor, implements the data processing method of any one of claims 1 to 7.
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| CN112883089A (en) * | 2020-10-29 | 2021-06-01 | 北京华胜天成科技股份有限公司 | Fire information processing method, fire information processing device, computer equipment and storage medium |
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Application publication date: 20200414 |