CN116308213A - Urban digital emergency integrated platform - Google Patents
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Abstract
The invention provides an urban digital emergency integrated platform, which comprises: the system comprises a weather monitoring module, a fire monitoring module, a traffic accident monitoring module and an emergency command module; the weather monitoring module is used for acquiring weather forecast information of each area in the city and sending weather early warning instructions to the emergency command module; the fire control monitoring module is used for monitoring fire control safety information in the city, and sending a fire control processing instruction to the emergency command module when the fire control safety information displays that a fire accident occurs; the traffic accident monitoring module is used for monitoring traffic accident information in the city, and sending a traffic accident handling instruction to the emergency command module when the traffic accident information shows that a traffic accident occurs; the emergency command module is used for sending early warning information to the user according to the weather early warning instruction and carrying out resource allocation according to the fire control processing instruction and/or the traffic accident processing instruction. The invention can effectively improve the emergency treatment efficiency of cities.
Description
Technical Field
The invention belongs to the technical field of urban emergency management, and particularly relates to an urban digital emergency integrated platform.
Background
The emergency treatment construction of the city is of great importance, and at present, when emergency treatment is carried out on emergencies of the city, specific transaction coordination and resource allocation are realized based on manual work, so that the cost is high, but the emergency treatment efficiency is low. Therefore, how to improve the emergency treatment efficiency of cities is a problem to be solved in the art.
Disclosure of Invention
The invention aims to provide an urban digital emergency integrated platform so as to improve urban emergency treatment efficiency.
In order to achieve the above purpose, the technical scheme adopted by the invention is to provide an integrated urban digital emergency platform, which comprises:
the system comprises a weather monitoring module, a fire monitoring module, a traffic accident monitoring module and an emergency command module;
the weather monitoring module is used for acquiring weather forecast information of each area in the city, judging the severity of future weather in each area according to the weather forecast information, and sending weather early warning instructions corresponding to the area to the emergency command module when the severity of future weather in a certain area is greater than a preset level;
the fire control monitoring module is used for monitoring fire control safety information in cities, and sending a fire control processing instruction to the emergency command module when the fire control safety information shows that a fire accident occurs;
The traffic accident monitoring module is used for monitoring traffic accident information in the city, and sending a traffic accident handling instruction to the emergency command module when the traffic accident information shows that a traffic accident occurs;
the emergency command module is used for sending early warning information to a mobile terminal of a user according to the weather early warning instruction and carrying out resource allocation according to the fire control processing instruction and/or the traffic accident processing instruction;
the weather monitoring module is also used for sending a first weather early warning instruction of the target area to the fire control monitoring module when the bad weather of the target area belongs to the first type of weather; wherein the target area refers to: in the city, the future weather is more severe than the preset area; bad weather of the target area refers to: future weather with the severe degree larger than a preset degree in the target area; the first type of weather includes: weather in which the temperature is greater than a preset temperature or weather in which the humidity is lower than a preset humidity;
the fire control monitoring module is further used for acquiring fire control information of a target area when the first weather early warning instruction is received, determining fire accident probability of the target area according to the fire control information and the early warning level carried in the first weather early warning instruction, and sending the fire accident probability to the emergency command module when the fire accident probability is greater than a first preset probability;
The emergency command module is also used for pre-distributing fire resources for a target area according to the fire accident probability;
the weather monitoring module is further used for sending a second weather early warning instruction of the target area to the traffic accident monitoring module when the bad weather of the target area belongs to a second type of weather; wherein the second type of weather includes: rain and snow weather, hail weather, storm weather, and weather with less than a preset visibility;
the traffic accident monitoring module is further used for acquiring traffic flow information of a target area when receiving the second weather early warning instruction, determining traffic accident probability of the target area according to the traffic flow information and the early warning level carried in the second weather early warning instruction, and sending the traffic accident probability to the emergency command module when the traffic accident probability is greater than a second preset probability;
the emergency command module is also used for pre-distributing traffic command resources for a target area according to the traffic accident probability.
In one possible implementation manner, the fire control processing instruction comprises a fire control accident position and a fire control accident level; the emergency command module performs resource allocation according to the fire control processing instruction, and comprises the following steps:
The emergency command module determines a fire control supporting position according to the fire control accident position, and distributes fire control resources of the fire control supporting position for the fire control accident according to the fire control accident grade;
the emergency command module also generates an optimal route from the fire control support location to the fire control accident location according to the fire control support location and the fire control accident location, and allocates traffic treatment resources for the fire control accident based on the optimal route.
In one possible implementation, the fire information includes: the method comprises the steps of determining the number of fire-fighting facilities in a target area, the average service life of the fire-fighting facilities, traffic flow information of the target area and building information of the target area; the determining the fire accident probability of the target area according to the fire information and the early warning level carried in the first atmospheric early warning instruction comprises the following steps:
generating a first feature vector according to the number of fire facilities, the average service life, the traffic flow information, the building information and the early warning level;
and inputting the first feature vector into a pre-trained deep learning model to obtain the fire accident probability of the target area.
In a possible implementation manner, the pre-allocation of fire resources for the target area according to the fire accident probability includes:
if the fire accident probability is smaller than a third preset probability, pre-distributing first-class resources for a target area; wherein the first type of resource is a fire-fighting equipment resource;
if the fire accident probability is between the third preset probability and the fourth preset probability, pre-distributing second type resources and the first type resources for a target area; wherein the second type of resource is a fire-fighting vehicle resource;
if the fire accident probability is larger than a fourth preset probability, pre-distributing third-class resources, the first-class resources and the second-class resources for a target area; wherein the third type of resource is firefighter resource;
wherein the fourth preset probability is greater than the third preset probability.
In a possible implementation manner, the determining the traffic accident probability of the target area according to the traffic flow information and the early warning level carried in the second weather early warning instruction includes:
by passing through
Determining the traffic accident probability of a target area;
wherein, gamma is the traffic accident probability of the target area, alpha is a preset coefficient, 0< alpha <1, l is the traffic flow information, k and b are linear parameters calibrated in advance, and s is the early warning level carried in the second weather early warning instruction.
In one possible implementation manner, the traffic guidance resource is the number of traffic guidance personnel; the pre-allocation of traffic command resources for the target area according to the traffic accident probability comprises the following steps:
acquiring a first mapping relation, wherein the first mapping relation is a mapping relation between traffic accident probability and the number of traffic commanders;
determining the number of traffic directors corresponding to the target area according to the traffic accident probability of the target area and the first mapping relation, and recording the number of the traffic directors corresponding to the target area as a first number;
a first number of traffic directors is pre-assigned to the target area.
In one possible implementation manner, the determining the severity of the future weather in each area according to the weather forecast information includes:
determining weather types and weather parameters of future weather in each area according to the weather forecast information;
determining a preset threshold corresponding to each type of weather in each area according to the weather type of the future weather in each area;
and determining the degree that the weather parameters of each type of weather in each area exceed the preset threshold corresponding to each type of weather in each area as the future severity of each type of weather in each area.
In one possible implementation manner, the integrated digital emergency platform for cities further includes:
a geological disaster monitoring module;
the geological disaster monitoring module is used for monitoring geological disaster information of the peripheral mountain areas of the city, and sending a geological disaster processing instruction to the emergency command module when the geological disaster information shows that geological disasters occur;
the emergency command module is also used for distributing resources according to the geological disaster processing instruction.
In a possible implementation manner, the weather monitoring module is further configured to send a third weather early warning instruction of the target area to the geological disaster monitoring module when severe weather of the target area belongs to rainy and snowy weather;
the geological disaster monitoring module is further used for acquiring geological information of a target area when the third weather early warning instruction is received, determining geological disaster probability of the target area according to the geological information of the target area and the early warning level carried in the third weather early warning instruction, and sending the geological disaster probability to the emergency command module when the geological disaster probability is larger than a fifth preset probability;
the emergency command module is also used for pre-distributing rescue resources for the target area according to the geological disaster probability.
In one possible implementation, the rescue resources include material resources; after pre-allocation of rescue resources for the target area according to the geological disaster probability, the emergency command module is further configured to:
determining a first distance according to the geological disaster probability;
and conveying the material resource to a position at a first distance from the target area in advance.
The urban digital emergency integrated platform provided by the embodiment of the invention has the beneficial effects that:
on one hand, the embodiment of the invention can realize the automatic early warning and automatic processing of the emergency event through a plurality of digital functional modules, and greatly reduces the workload of manual coordination and manual allocation, thereby reducing the labor cost, and simultaneously, the automatic process can also effectively improve the emergency processing efficiency of cities.
On the other hand, the embodiment of the invention also optimizes the emergency treatment process, can realize automatic early warning and automatic allocation, and predicts the occurrence of accidents in advance through the synergistic effect among the weather monitoring module, the fire monitoring module and the traffic accident monitoring module, thereby realizing the pre-allocation of resources. On the basis, when an accident occurs, the resource is pre-allocated, so that the accident treatment efficiency can be effectively improved.
In view of the above, the embodiments of the present invention effectively solve the problems in the prior art.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic structural diagram of an integrated digital emergency platform for cities according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an integrated digital emergency platform for cities according to another embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention will be described in further detail with reference to the drawings and the detailed description.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an integrated digital urban emergency platform according to an embodiment of the present invention, where the integrated digital urban emergency platform includes:
The weather monitoring module 10 is configured to obtain weather forecast information of each area in the city, determine a severity of future weather in each area according to the weather forecast information, and send a weather early warning command corresponding to the area to the emergency command module 40 when the severity of future weather in the area is greater than a preset severity.
In this embodiment, the weather monitoring module 10 is configured to monitor weather, and is specifically configured to obtain weather forecast information of each area in the city according to a preset time interval, and determine a future weather severity of each area according to the weather forecast information.
In this embodiment, the severity of weather refers to the extreme degree of weather, that is, the degree of influence of weather on normal life production of a person.
The fire control monitoring module 20 is used for monitoring fire safety information in the city, and sending a fire control processing instruction to the emergency command module 40 when the fire safety information indicates that a fire accident occurs.
The traffic accident monitoring module 30 is configured to monitor traffic accident information in a city, and send a traffic accident handling instruction to the emergency command module 40 when the traffic accident information indicates that a traffic accident occurs.
The emergency command module 40 is configured to send early warning information to a mobile terminal of a user according to a weather early warning instruction, and perform resource allocation according to a fire control instruction and/or a traffic accident handling instruction.
In this embodiment, the weather warning instruction may include: severe weather and the area where the severe weather is located. The emergency command module 40 is configured to generate early warning information according to the severe weather, obtain a contact way of a user in an area where the severe weather is located, and send the early warning information to a mobile terminal of the user based on the contact way.
In this embodiment, the emergency command module 40 is configured to perform fire-fighting resource allocation when receiving a fire-fighting command, and perform traffic command resource allocation when receiving a traffic accident handling command.
The weather monitoring module 10 is further configured to send a first weather early warning instruction of the target area to the fire monitoring module 20 when bad weather of the target area belongs to a first type of weather. Wherein the target area refers to: in a city, the future weather is more severe than a preset level. Bad weather in the target area refers to: future weather in which the severity is greater than a preset level in the target area. The first type of weather includes: weather in which the temperature is greater than a preset temperature or weather in which the humidity is lower than a preset humidity.
The fire control monitoring module 20 is further configured to, when receiving the first weather early warning command, obtain fire control information of the target area, determine a fire accident probability of the target area according to the fire control information and an early warning level carried in the first weather early warning command, and send the fire accident probability to the emergency command module 40 when the fire accident probability is greater than a first preset probability.
The emergency command module 40 is further configured to pre-allocate fire resources for the target area according to the fire accident probability.
In this embodiment, the weather monitoring module 10 is further linked with the fire monitoring module 20, and when the weather monitoring module detects bad weather belonging to the first type of weather, the weather monitoring module sends a first weather early warning instruction to the fire monitoring module 20, on the basis, the fire monitoring module 20 determines the fire accident probability of the target area by combining the fire information of the target area and the information in the first weather early warning instruction, and the fire accident probability is used for describing the probability of the fire accident of the target area. When the probability of the fire accident is high, the fire control monitoring module 20 will send the probability of the fire accident to the emergency command module 40, so that the emergency command module 40 performs pre-allocation of fire resources (i.e. pre-allocation of fire resources, i.e. pre-reservation of corresponding fire resources).
In this embodiment, the method for determining the early warning level carried in the first early warning instruction by the weather monitoring module 10 is as follows:
determining a temperature index based on the weather temperature of the target area and a preset temperature, determining a humidity index based on the weather humidity of the target area and the preset humidity, carrying out weighted summation on the temperature index and the humidity index to obtain a first early warning index, and determining an early warning level carried in a first early warning instruction according to a first index range to which the first early warning index belongs.
The temperature index is determined based on the weather temperature of the target area and the preset temperature, and can be described as follows:
if the weather temperature of the target area is greater than the preset temperature, passing
A temperature index is calculated. s1 is temperature fingerAnd t1 is the weather temperature of the target area, and t0 is the preset temperature.
If the weather temperature of the target area is not greater than the preset temperature, the temperature index is 0.
The humidity index is determined based on the weather humidity and the preset humidity of the target area, and can be described as follows:
if the weather humidity of the target area is lower than the preset humidity, passing
The humidity index was calculated. S2 is a humidity index, h1 is the weather humidity of the target area, and h0 is the preset humidity.
If the weather humidity of the target area is not lower than the preset humidity, the humidity index is 0.
The temperature index and the humidity index are weighted and summed to obtain a first early warning index, namely:
wherein sa is a first early warning index, and k1 is a preset weighting coefficient.
In this embodiment, a plurality of continuous first-type index ranges may be predetermined, where each first-type index range corresponds to one early warning level. On the basis, the early warning level carried in the first early warning instruction can be determined according to the first class index range to which the first early warning index belongs.
For example, three first-class index ranges, that is, a first-class index range 1, a first-class index range 2 and a first-class index range 3, are preset from small to large, wherein the three first-class index ranges respectively correspond to a first-class early warning level (which can be represented by a numerical value 1), a second-class early warning level (which can be represented by a numerical value 2) and a third-class early warning level (which can be represented by a numerical value 3). On the basis, if the first early warning index belongs to the first class index range 1, the early warning level carried in the first early warning instruction is a first early warning level. If the first early warning index belongs to the first class index range 2, the early warning level carried in the first early warning instruction is a second early warning level. If the first early warning index belongs to the first class index range 3, the early warning level carried in the first early warning instruction is three-level early warning level.
In this embodiment, the higher the early warning level in the first weather early warning instruction, the worse the weather.
The weather monitoring module 10 is further configured to send a second weather warning instruction of the target area to the traffic accident monitoring module 30 when the bad weather of the target area belongs to the second type of weather. Wherein the second type of weather includes: rain and snow weather, hail weather, storm weather, and weather with less than a preset visibility.
The traffic accident monitoring module 30 is further configured to, when receiving the second weather warning command, obtain traffic flow information of the target area, determine a traffic accident probability of the target area according to the traffic flow information and a warning level carried in the second weather warning command, and send the traffic accident probability to the emergency command module 40 when the traffic accident probability is greater than a second preset probability.
The emergency command module 40 is further configured to pre-allocate traffic command resources for the target area according to the traffic accident probability.
In this embodiment, the weather monitoring module 10 is further linked with the traffic accident monitoring module 30, and when the weather monitoring module detects bad weather belonging to the second type of weather, a second weather early warning instruction is sent to the traffic accident monitoring module 30, on the basis of this, the traffic accident monitoring module 30 determines the traffic accident probability of the target area by combining the traffic flow information of the target area and the information in the second weather early warning instruction, where the traffic accident probability is used to describe the probability of occurrence of a traffic accident in the target area. When the probability of the traffic accident is high, the fire monitor module 20 sends the probability of the traffic accident to the emergency command module 40, so that the emergency command module 40 performs pre-allocation of traffic command resources (i.e. pre-allocation of traffic command resources, i.e. pre-assigning traffic commanders to target areas).
In this embodiment, the method for determining the early warning level carried in the second weather early warning instruction by the weather monitoring module 10 is:
determining a rainfall index according to a rainfall range of a target area, determining a snowfall index according to the rainfall range of the target area, determining a hail index according to the hail range of the target area, determining a wind power index according to the wind power range of a wind power grade of the target area, determining a visibility index based on the visibility of the target area and a preset visibility, and carrying out weighted summation on the rainfall index, the snowfall index, the hail index, the wind power index and the visibility index to obtain a second early warning index, and determining an early warning level carried in a second weather early warning instruction based on a second class index range of the second early warning index.
In this embodiment, a plurality of continuous rainfall ranges may be preset, and a rainfall index may be set for each rainfall range, and on this basis, the rainfall index corresponding to the rainfall range of the target area may be determined according to the rainfall range to which the rainfall of the target area belongs. For example, three rainfall ranges, namely, a rainfall range 1, a rainfall range 2 and a rainfall range 3, are preset from small to large, wherein the three rainfall ranges respectively correspond to a rainfall index 1 (which can be represented by a numerical value 1), a rainfall index 2 (which can be represented by a numerical value 2) and a rainfall index 3 (which can be represented by a numerical value 3). On the basis, if the rainfall of the target area belongs to the rainfall range 1, the corresponding rainfall index is rainfall index 1. And if the rainfall of the target area belongs to the rainfall range 2, the corresponding rainfall index is rainfall index 2. If the rainfall of the target area belongs to the rainfall range 3, the corresponding rainfall index is rainfall index 3.
In this embodiment, a plurality of continuous snowfall ranges may be preset, and a snowfall index may be set for each snowfall range, and on this basis, the corresponding snowfall index may be determined according to the snowfall range to which the snowfall of the target area belongs. For example, three snowfall ranges, namely, a snowfall range 1, a snowfall range 2 and a snowfall range 3, are preset from small to large, wherein the three snowfall ranges respectively correspond to a snowfall index 1 (which can be represented by a numerical value 1), a snowfall index 2 (which can be represented by a numerical value 2) and a snowfall index 3 (which can be represented by a numerical value 3). On this basis, if the snowfall of the target area belongs to the snowfall range 1, the corresponding snowfall index is the snowfall index 1. If the snowfall of the target area belongs to the snowfall range 2, the corresponding snowfall index is the snowfall index 2. If the snowfall of the target area belongs to the snowfall range 3, the corresponding snowfall index is the snowfall index 3.
In this embodiment, a plurality of continuous hail-level ranges may be preset, and a hail index may be set for each hail-level range, on the basis of which the corresponding hail index may be determined according to the hail-level range to which the hail-level of the target area belongs. For example, three hail amount ranges, namely, a hail amount range 1, a hail amount range 2 and a hail amount range 3, are preset from small to large, wherein the three hail amount ranges respectively correspond to a hail index 1 (which can be represented by a numerical value 1), a hail index 2 (which can be represented by a numerical value 2) and a hail index 3 (which can be represented by a numerical value 3). On this basis, if the hail amount of the target area belongs to the hail amount range 1, the corresponding hail index is the hail index 1. If the hail level of the target area falls within the hail level range 2, the corresponding hail index is hail index 2. If the hail level of the target area falls within the hail level range 3, the corresponding hail index is hail index 3.
In this embodiment, a plurality of continuous wind ranges may be preset, and a wind index may be set for each wind range, and on this basis, the corresponding wind index may be determined according to the wind range to which the wind level of the target area belongs. For example, three wind ranges, i.e., wind range 1, wind range 2 and wind range 3, are preset from small to large, wherein the three wind ranges correspond to wind index 1 (which may be represented by value 1), wind index 2 (which may be represented by value 2) and wind index 3 (which may be represented by value 3), respectively. On the basis, if the wind power grade of the target area belongs to the wind power range 1, the corresponding wind power index is wind power index 1. If the wind power level of the target area belongs to the wind power range 2, the corresponding wind power index is wind power index 2. If the wind power level of the target area belongs to the wind power range 3, the corresponding wind power index is wind power index 3.
In this embodiment, the method for calculating the visibility index is as follows:
if the visibility of the target area is smaller than the preset visibility, the method comprises the following steps of
A visibility index is calculated. sn is a visibility index, sn1 is the visibility of the target area, and sn0 is a preset visibility.
If the visibility of the target area is not less than the preset visibility, the visibility index is 0.
In this embodiment, the aforementioned rainfall index, snowfall index, hail index, wind power index, visibility index are weighted and summed, that is:
wherein s is a second early warning index, k2, k3, k4 and k5 are all preset weighting coefficients, s3 is a rainfall index, s4 is a snowfall index, s5 is a hail index, and s6 is a wind power index.
In this embodiment, a plurality of consecutive second-class index ranges may be predetermined, where each second-class index range corresponds to one early warning level. On the basis, the early warning level carried in the second weather early warning instruction can be determined according to the second class index range to which the second early warning index belongs.
For example, three second-class index ranges are preset from small to large, namely a second-class index range 1, a second-class index range 2 and a second-class index range 3, wherein the three second-class index ranges correspond to a first-class early warning level (which can be represented by a numerical value 1), a second-class early warning level (which can be represented by a numerical value 2) and a third-class early warning level (which can be represented by a numerical value 3) respectively. On the basis, if the second early warning index belongs to the second class index range 1, the early warning level carried in the second weather early warning instruction is a first early warning level. If the second early warning index belongs to the second class index range 2, the early warning level carried in the second weather early warning instruction is a second early warning level. If the second early warning index belongs to the second class index range 3, the early warning level carried in the second weather early warning instruction is three-level early warning level.
In this embodiment, the higher the warning level in the second weather warning instruction, the worse the weather is indicated.
From the above description, on one hand, the embodiment of the invention can realize the automatic early warning and automatic processing of the emergency event through a plurality of digital functional modules, thereby greatly reducing the workload of manual coordination and manual allocation, further reducing the labor cost, and simultaneously effectively improving the emergency processing efficiency of cities in the automatic process. On the other hand, the embodiment of the invention also optimizes the emergency treatment process, can realize automatic early warning and automatic allocation, and predicts the occurrence of accidents in advance through the synergistic effect among the weather monitoring module, the fire monitoring module and the traffic accident monitoring module, thereby realizing the pre-allocation of resources. On the basis, when an accident occurs, the resource is pre-allocated, so that the accident treatment efficiency can be effectively improved. Therefore, the embodiment of the invention effectively solves the problems in the prior art.
In one possible implementation, the fire handling instructions include a fire location and a fire level. The emergency command module performs resource allocation according to the fire control processing instruction, and comprises the following steps:
The emergency command module determines a fire control supporting position according to the fire control accident position, and distributes fire control resources of the fire control supporting position for the fire control accident according to the fire control accident grade.
The emergency command module also generates an optimal route from the fire support location to the fire location based on the fire support location and the fire location, and allocates traffic handling resources for the fire based on the optimal route.
In this embodiment, when the emergency command module performs resource allocation according to the fire control processing instruction, the location of the fire control support may be determined according to the location of the fire accident, for example, the location of the fire accident is located in the xx administrative area, and then the location of the fire control support may be determined as the location of the fire team in the xx administrative area. Alternatively, the location of the fire department closest to the location of the fire accident may be determined as the fire support location.
In this embodiment, fire resources at the fire control support location may be allocated to the fire control accident according to the fire control accident level, that is, the allocation number of the fire control resources may be determined according to the fire control accident level. Wherein the fire accident rating is used to describe the severity of the fire accident. For example, a higher fire rating indicates a more serious fire, at which time a greater number of fire resources may be allocated to the target area. Among other fire resources, fire-fighting resources include, but are not limited to, fire-fighting equipment, fire-fighting vehicles, fire-fighting personnel, and the like.
In the embodiment, besides fire-fighting resources, traffic resources can be allocated, so that traffic cost in fire-fighting accidents is reduced, and emergency treatment efficiency is improved. Specifically, an optimal route from the fire-fighting support position to the fire-fighting accident position can be planned, traffic flow information on the optimal route is obtained, and traffic processing resources are distributed according to the traffic flow information on the optimal route. For example, if the traffic flow information of a certain position on the optimal route shows that the position has traffic jam, a corresponding number of traffic directors are assigned to the position according to the traffic jam degree of the position.
In one possible implementation, the fire information includes: the number of fire-fighting facilities in the target area, the average service life of the fire-fighting facilities, traffic flow information of the target area, building information of the target area. Determining the fire accident probability of the target area according to the fire information and the early warning level carried in the first weather early warning instruction, including:
and generating a first feature vector according to the number of fire facilities, the average service life, traffic flow information, building information and the early warning level carried in the first early warning instruction.
And inputting the first feature vector into a pre-trained deep learning model to obtain the fire accident probability of the target area.
In this embodiment, the first feature vector may be generated by means of feature connection, that is, the first feature vector may be expressed as [ e1, e2, e3, e4, e5 ], where e1 is the number of fire facilities, e2 is the average service life, e3 is traffic flow information, e4 is building information, and e5 is the early warning level carried in the first early warning instruction.
In this embodiment, the deep learning model may be trained in advance, and based on this, the fire accident probability of the target area may be predicted based on the deep learning model trained in advance.
In one possible implementation, the pre-allocation of fire resources for the target area according to the fire accident probability includes:
if the fire accident probability is smaller than the third preset probability, pre-distributing first-class resources for the target area. Wherein the first type of resource is a fire-fighting equipment resource.
If the fire accident probability is between the third preset probability and the fourth preset probability, pre-distributing the second type of resources and the first type of resources for the target area. Wherein the second type of resource is a fire engine resource.
If the fire accident probability is larger than the fourth preset probability, pre-distributing third-class resources, first-class resources and second-class resources for the target area. Wherein the third type of resource is firefighter resource.
Wherein the fourth preset probability is greater than the third preset probability.
In this embodiment, the fire resources allocated thereto may be determined according to the probability range to which the fire accident probability belongs. For example, the fire accident probability belongs to the first probability range (i.e., when the fire accident probability is smaller than the third preset probability), and the probability of the fire accident is relatively low at this time, fire equipment resources can be allocated in advance for the target area (i.e., a corresponding number of fire equipment is reserved). For example, the fire accident probability falls within the second probability range (i.e., when the fire accident probability is between the third preset probability and the fourth preset probability), and the probability of the fire accident occurring is relatively centered at this time, and fire equipment resources and fire vehicle resources (i.e., corresponding numbers of fire equipment and fire vehicles are reserved) may be allocated in advance to the target area. For example, the fire accident probability falls within the third probability range (i.e., when the fire accident probability is greater than the fourth preset probability), and the probability of the fire accident occurring is relatively high, more fire resources, such as fire equipment resources, fire vehicle resources, and fire personnel resources (corresponding numbers of fire equipment, fire vehicles, and fire personnel are reserved) may be allocated to the target area in advance.
In one possible implementation manner, determining the traffic accident probability of the target area according to the traffic flow information and the early warning level carried in the second weather early warning instruction includes:
by passing through
Determining the traffic accident probability of a target area;
wherein, gamma is the traffic accident probability of the target area, alpha is a preset coefficient, 0< alpha <1, l is the traffic flow information, k and b are linear parameters calibrated in advance, and s is the early warning level carried in the second weather early warning instruction.
In the present embodiment, the probability of occurrence of a traffic accident is determined based on the above equation, considering that the larger the traffic flow is, the worse the weather is, and the higher the probability of occurrence of a traffic accident.
In one possible implementation, the traffic guidance resource is the number of traffic guidance personnel. The traffic command resource pre-allocation is carried out for the target area according to the traffic accident probability, and the traffic command resource pre-allocation method comprises the following steps:
and obtaining a first mapping relation, wherein the first mapping relation is a mapping relation between the traffic accident probability and the number of traffic commanders.
And determining the number of traffic directors corresponding to the target area according to the traffic accident probability of the target area and the first mapping relation, and recording the number of the traffic directors corresponding to the target area as the first number.
A first number of traffic directors is pre-assigned to the target area.
In this embodiment, the mapping relationship between the traffic accident probability and the number of traffic directors may be calibrated in advance, where the number of traffic directors is positively related to the traffic accident probability, that is, the greater the traffic accident probability (the greater the probability of occurrence of a traffic accident), the greater the number of traffic directors is.
In one possible implementation, determining the severity of future weather in each area according to weather forecast information includes:
and determining weather types and weather parameters of future weather in each area according to the weather forecast information.
And determining a preset threshold corresponding to each type of weather in each area according to the weather type of the future weather in each area.
And determining the degree that the weather parameters of each type of weather in each area exceed the preset threshold corresponding to each type of weather in each area as the future severity of each type of weather in each area.
In the present embodiment, if the weather type of the future weather is rainy/snowy, the weather parameter may be rainfall/snowfall. If the weather type of the future weather is fog days, the weather parameter may be visibility. If the weather type of the future weather is wind, the weather parameter may be a wind level. If the weather type of the future weather is high temperature days, the weather parameter may be directly outdoor temperature. That is, the specific weather parameters may be determined by the weather type.
In the present embodiment, δ= (q) 1 -q 0 )/q 0 The severity of each type of weather is determined. Wherein delta is the severity of each type of weather, q 1 For (parameter values of) weather parameters of each type of weather, q 0 For a preset threshold value corresponding to the weather of the type,
in one possible implementation, referring to fig. 2, the integrated digital urban emergency platform further includes a geological disaster monitoring module 50.
The geological disaster monitoring module 50 is used for monitoring geological disaster information of the peripheral mountain area of the city, and sending a geological disaster processing instruction to the emergency command module 40 when the geological disaster information shows that the geological disaster occurs.
The emergency command module 40 is further used for performing resource allocation according to the geological disaster processing instruction.
In this embodiment, the geological disaster monitoring module 50 can detect geological disaster information of the peripheral mountain area of the city, and on this basis, send a geological disaster processing instruction to the emergency command module 40 when a geological disaster occurs. The geological disaster processing command may include a position of occurrence of a geological disaster and a geological disaster level, and the emergency command module 40 may allocate rescue resources according to the position of occurrence and the geological disaster level.
In this embodiment, resource allocation is performed according to a geological disaster processing instruction, including:
And determining a geological disaster supporting position according to the occurrence position of the geological disaster, and distributing rescue resources of the geological disaster supporting position for the geological disaster according to the geological disaster grade.
Generating an optimal route from the geological disaster support location to the occurrence location of the geological disaster according to the geological disaster support location and the occurrence location of the geological disaster, and distributing traffic processing resources for the geological disaster based on the optimal route.
In one possible implementation manner, the weather monitoring module is further configured to send a third weather early warning instruction of the target area to the geological disaster monitoring module when the bad weather of the target area belongs to rain and snow weather.
The geological disaster monitoring module is further used for acquiring geological information of the target area when receiving the third weather early warning instruction, determining geological disaster probability of the target area according to the geological information of the target area and the early warning level carried in the third weather early warning instruction, and sending the geological disaster probability to the emergency command module when the geological disaster probability is larger than a fifth preset probability.
The emergency command module is also used for pre-distributing rescue resources for the target area according to the geological disaster probability.
In this embodiment, the weather monitoring module is further linked with the geological disaster monitoring module, and when the weather monitoring module detects severe rain and snow weather, a third weather early warning instruction is sent to the geological disaster monitoring module, on this basis, the geological disaster monitoring module determines the geological disaster probability of the target area by combining the geological information of the target area and the information in the third weather early warning instruction, and the geological disaster probability is used for describing the probability of occurrence of geological disasters of the target area. When the probability of the geological disaster is high, the geological disaster monitoring module can send the probability of the geological disaster to the emergency command module so that the emergency command module performs pre-allocation of rescue resources (namely, the rescue resources are allocated in advance, namely, reserved in advance).
In this embodiment, the method for determining the early warning level carried in the third weather early warning instruction by the weather monitoring module is as follows:
determining a rainfall index according to a rainfall range of the rainfall of the target area, determining a snowfall index according to the rainfall range of the rainfall of the target area, carrying out weighted summation on the rainfall index and the snowfall index to obtain a third early warning index, and determining an early warning level carried in a third weather early warning instruction based on a third class index range of the third early warning index.
In this embodiment, a plurality of continuous rainfall ranges may be preset, and a rainfall index may be set for each rainfall range, and on this basis, the rainfall index corresponding to the rainfall range of the target area may be determined according to the rainfall range to which the rainfall of the target area belongs. For example, three rainfall ranges, namely, a rainfall range 1, a rainfall range 2 and a rainfall range 3, are preset from small to large, wherein the three rainfall ranges respectively correspond to a rainfall index 1 (which can be represented by a numerical value 1), a rainfall index 2 (which can be represented by a numerical value 2) and a rainfall index 3 (which can be represented by a numerical value 3). On the basis, if the rainfall of the target area belongs to the rainfall range 1, the corresponding rainfall index is rainfall index 1. And if the rainfall of the target area belongs to the rainfall range 2, the corresponding rainfall index is rainfall index 2. If the rainfall of the target area belongs to the rainfall range 3, the corresponding rainfall index is rainfall index 3.
In this embodiment, a plurality of continuous snowfall ranges may be preset, and a snowfall index may be set for each snowfall range, and on this basis, the corresponding snowfall index may be determined according to the snowfall range to which the snowfall of the target area belongs. For example, three snowfall ranges, namely, a snowfall range 1, a snowfall range 2 and a snowfall range 3, are preset from small to large, wherein the three snowfall ranges respectively correspond to a snowfall index 1 (which can be represented by a numerical value 1), a snowfall index 2 (which can be represented by a numerical value 2) and a snowfall index 3 (which can be represented by a numerical value 3). On this basis, if the snowfall of the target area belongs to the snowfall range 1, the corresponding snowfall index is the snowfall index 1. If the snowfall of the target area belongs to the snowfall range 2, the corresponding snowfall index is the snowfall index 2. If the snowfall of the target area belongs to the snowfall range 3, the corresponding snowfall index is the snowfall index 3.
In this embodiment, the aforementioned rainfall index, snowfall index, is weighted and summed, that is:
wherein sc is a third early warning index, k6 is a preset weighting coefficient, s3 is a rainfall index, and s4 is a snowfall index.
In this embodiment, a plurality of consecutive third-class index ranges may be predetermined, where each third-class index range corresponds to one pre-warning level. On the basis, the early warning level carried in the third weather early warning instruction can be determined according to a third class index range to which the third early warning index belongs.
For example, three third class index ranges are preset from small to large, namely a third class index range 1, a third class index range 2 and a third class index range 3, wherein the three third class index ranges correspond to a first-level early warning level (which can be represented by a numerical value 1), a second-level early warning level (which can be represented by a numerical value 2) and a third-level early warning level (which can be represented by a numerical value 3) respectively. On the basis, if the third early warning index belongs to the third class index range 1, the early warning level carried in the third weather early warning instruction is a first-level early warning level. If the third early warning index belongs to the third class index range 2, the early warning level carried in the third weather early warning instruction is a second early warning level. If the third early warning index belongs to the third class index range 3, the early warning level carried in the third weather early warning instruction is three-level early warning level.
The first type of index range, the second type of index range, and the third type of index range may be the same or different, which is not limited in this embodiment.
In this embodiment, the higher the warning level in the third weather warning instruction, the worse the weather is indicated. The geological information may include a soil type of the target area and a historical geological disaster occurrence frequency of the target area, and on this basis, the geological disaster probability of the target area is determined according to the geological information of the target area and an early warning level carried in a third weather early warning instruction, which may be described in detail as follows:
And inputting the soil types, the historical geological disaster occurrence probability and the early warning level carried in the third weather early warning instruction into a pre-trained neural network model to obtain the geological disaster probability.
That is, a neural network model for outputting a corresponding geological disaster probability according to the inputted soil type, the historical geological disaster occurrence probability, and the early warning level may be trained in advance. On the basis, the geological disaster probability of the target area can be determined directly based on the neural network model.
In this embodiment, the rescue resources include material resources and rescue personnel resources; the pre-allocation of rescue resources for the target area according to the geological disaster probability can be detailed as follows:
and obtaining a second mapping relation and a third mapping relation, wherein the second mapping relation is a mapping relation between the geological disaster probability and the number of the material resources, and the second mapping relation is a mapping relation between the geological disaster probability and the number of the rescue personnel resources.
And determining the quantity of the material resources corresponding to the target area according to the geological disaster probability of the target area and the second mapping relation to obtain a second quantity. And determining the number of the rescue personnel resources corresponding to the target area according to the geological disaster probability of the target area and the third mapping relation to obtain a third number.
And pre-distributing a second number of material resources and a third number of rescue workers for the target area.
In one possible implementation, the rescue resources include material resources. After pre-allocation of rescue resources for the target area according to the geological disaster probability, the emergency command module is further used for:
a first distance is determined based on the geological disaster probability.
The material resource is transported in advance to a location a first distance from the target area.
In this embodiment, the linear relationship between the first distance and the geological disaster probability may be calibrated in advance, and on this basis, the first distance corresponding to the target area may be determined according to the linear relationship. The first distance is inversely related to the probability of the geological disaster, that is, the greater the probability of the address disaster is, the closer the first distance is, so that emergency treatment of the geological disaster can be realized rapidly.
In one possible implementation, the emergency command module includes a central processor, a plurality of fixed communication base stations, and a plurality of mobile communication base stations, where the central processor, the plurality of fixed communication base stations, and the plurality of mobile communication base stations are all capable of being connected to each other to transmit data, and the plurality of fixed communication base stations and the plurality of mobile communication base stations are each capable of being connected to the weather monitoring module, the fire monitoring module, the traffic accident monitoring module, and the geological disaster monitoring module to transmit data.
Specifically, the central processing unit is respectively communicated with one of the monitoring modules such as the weather monitoring module, the fire control monitoring module, the traffic accident monitoring module and the geological disaster monitoring module through the two fixed communication base stations, namely, two communication channels are formed through the two fixed communication base stations, and the validity of the corresponding fixed communication base stations and the corresponding monitoring modules is checked through information respectively transmitted by the central processing unit through the two communication channels. When the verification finds that the data transmitted by one of the fixed communication base stations is problematic, namely, the mobile communication base station is replaced by a mobile communication base station to be carried by a carrier to be communicated, the carrier carrying the mobile communication base station can be an automobile, a subway, an airplane or the like.
In order to reduce the possibility of damage of the mobile communication base station caused by transportation vibration, the mobile communication base station is connected with a carrier through a vibration-proof seat, the vibration-proof seat comprises an outer rubber shell and an inner rubber shell, the outer rubber shell and the inner rubber shell are of elastic structures, the inner rubber shell is arranged inside the outer rubber shell, non-Newtonian fluid and a plurality of pellets are filled between the inner rubber shell and the outer rubber shell, the density of the pellets is greater than that of the non-Newtonian fluid, the inner rubber shell is closed, compressed gas is filled inside the inner rubber shell, a pressure release valve is arranged on the inner rubber shell, the pressure difference between the inside and the outside of the inner rubber shell is opened when the pressure difference between the inside and the outside of the inner rubber shell reaches a preset threshold value, the inside and the outside of the inner rubber shell are communicated, and the non-Newtonian fluid at least surrounds the upper part and the periphery of the inner rubber shell; the outer rubber shell is provided with a connecting structure connected with the mobile communication base station and the carrier, such as a connecting hole, a connecting lug, a clamping groove and the like, wherein the non-Newtonian fluid adopts shearing liquefied fluid. The inner rubber shell and the compressed air filled in the inner rubber shell can reduce the filling quantity of non-Newtonian fluid, reduce the overall weight, dissipate energy through air friction in the inner rubber shell, and simultaneously can form an air cushion structure to achieve a better buffering effect.
When the carrier operates, if the vibration between the mobile communication base station and the carrier is smaller, the non-Newtonian fluid is in a solid state or a semi-solid state, the whole shockproof seat is firm and is not easy to deform, and the shock absorption and the buffering can be performed through the outer rubber shell, the inner rubber shell, the internal non-Newtonian fluid and compressed air; when the vibration between the mobile communication base station and the carrier is relatively large, the small ball obtains energy, moves in the non-Newtonian fluid, and combines external vibration to enable the non-Newtonian fluid to be sheared and liquefied, so that the non-Newtonian fluid is softened, the whole vibration-proof seat is softened, and vibration reduction and buffering are carried out through larger deformation; if vibration between the mobile communication base station and the carrier exceeds a certain limit, such as when an accident such as collision occurs, a pressure release valve on the inner rubber shell is opened, gas in the inner rubber shell escapes, the non-Newtonian fluid fills the space of the inner rubber shell so as to fully absorb energy, then the upper part of the inner rubber shell is gas, and the lower part of the inner rubber shell is in a non-Newtonian fluid state, so that the inner rubber shell still has better buffering and energy dissipation effects until the inner rubber shell is replaced by a new shock-proof seat.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. An integrated urban digital emergency platform, comprising:
the system comprises a weather monitoring module, a fire monitoring module, a traffic accident monitoring module and an emergency command module;
the weather monitoring module is used for acquiring weather forecast information of each area in the city, judging the severity of future weather in each area according to the weather forecast information, and sending weather early warning instructions corresponding to the area to the emergency command module when the severity of future weather in a certain area is greater than a preset level;
the fire control monitoring module is used for monitoring fire control safety information in cities, and sending a fire control processing instruction to the emergency command module when the fire control safety information shows that a fire accident occurs;
the traffic accident monitoring module is used for monitoring traffic accident information in the city, and sending a traffic accident handling instruction to the emergency command module when the traffic accident information shows that a traffic accident occurs;
the emergency command module is used for sending early warning information to a mobile terminal of a user according to the weather early warning instruction and carrying out resource allocation according to the fire control processing instruction and/or the traffic accident processing instruction;
The weather monitoring module is also used for sending a first weather early warning instruction of the target area to the fire control monitoring module when the bad weather of the target area belongs to the first type of weather; wherein the target area refers to: in the city, the future weather is more severe than the preset area; bad weather of the target area refers to: future weather with the severe degree larger than a preset degree in the target area; the first type of weather includes: weather in which the temperature is greater than a preset temperature or weather in which the humidity is lower than a preset humidity;
the fire control monitoring module is further used for acquiring fire control information of a target area when the first weather early warning instruction is received, determining fire accident probability of the target area according to the fire control information and the early warning level carried in the first weather early warning instruction, and sending the fire accident probability to the emergency command module when the fire accident probability is greater than a first preset probability;
the emergency command module is also used for pre-distributing fire resources for a target area according to the fire accident probability;
the weather monitoring module is further used for sending a second weather early warning instruction of the target area to the traffic accident monitoring module when the bad weather of the target area belongs to a second type of weather; wherein the second type of weather includes: rain and snow weather, hail weather, storm weather, and weather with less than a preset visibility;
The traffic accident monitoring module is further used for acquiring traffic flow information of a target area when receiving the second weather early warning instruction, determining traffic accident probability of the target area according to the traffic flow information and the early warning level carried in the second weather early warning instruction, and sending the traffic accident probability to the emergency command module when the traffic accident probability is greater than a second preset probability;
the emergency command module is also used for pre-distributing traffic command resources for a target area according to the traffic accident probability.
2. The integrated urban digital emergency platform according to claim 1, wherein the fire control treatment instructions comprise fire control accident positions and fire control accident levels; the emergency command module performs resource allocation according to the fire control processing instruction, and comprises the following steps:
the emergency command module determines a fire control supporting position according to the fire control accident position, and distributes fire control resources of the fire control supporting position for the fire control accident according to the fire control accident grade;
the emergency command module also generates an optimal route from the fire control support location to the fire control accident location according to the fire control support location and the fire control accident location, and allocates traffic treatment resources for the fire control accident based on the optimal route.
3. The integrated urban digital emergency platform according to claim 1, wherein said fire information comprises: the method comprises the steps of determining the number of fire-fighting facilities in a target area, the average service life of the fire-fighting facilities, traffic flow information of the target area and building information of the target area; the determining the fire accident probability of the target area according to the fire information and the early warning level carried in the first atmospheric early warning instruction comprises the following steps:
generating a first feature vector according to the number of fire facilities, the average service life, the traffic flow information, the building information and the early warning level;
and inputting the first feature vector into a pre-trained deep learning model to obtain the fire accident probability of the target area.
4. The integrated urban digital emergency platform according to claim 1, wherein said pre-allocation of fire resources for a target area according to said fire probability comprises:
if the fire accident probability is smaller than a third preset probability, pre-distributing first-class resources for a target area; wherein the first type of resource is a fire-fighting equipment resource;
if the fire accident probability is between the third preset probability and the fourth preset probability, pre-distributing second type resources and the first type resources for a target area; wherein the second type of resource is a fire-fighting vehicle resource;
If the fire accident probability is larger than a fourth preset probability, pre-distributing third-class resources, the first-class resources and the second-class resources for a target area; wherein the third type of resource is firefighter resource;
wherein the fourth preset probability is greater than the third preset probability.
5. The integrated urban digital emergency platform according to claim 1, wherein said determining the traffic accident probability of the target area according to the traffic flow information and the early warning level carried in the second weather early warning instruction comprises:
by passing through
Determining the traffic accident probability of a target area;
wherein, gamma is the traffic accident probability of the target area, alpha is a preset coefficient, 0<α<And 1, l is the traffic flow information, k and b are linear parameters calibrated in advance, and s is the early warning level carried in the second weather early warning instruction.
6. The integrated urban digital emergency platform according to claim 1, wherein the traffic guidance resource is the number of traffic guidance personnel; the pre-allocation of traffic command resources for the target area according to the traffic accident probability comprises the following steps:
acquiring a first mapping relation, wherein the first mapping relation is a mapping relation between traffic accident probability and the number of traffic commanders;
Determining the number of traffic directors corresponding to the target area according to the traffic accident probability of the target area and the first mapping relation, and recording the number of the traffic directors corresponding to the target area as a first number;
a first number of traffic directors is pre-assigned to the target area.
7. The integrated urban digital emergency platform according to claim 1, wherein said determining the severity of future weather in said areas based on said weather forecast information comprises:
determining weather types and weather parameters of future weather in each area according to the weather forecast information;
determining a preset threshold corresponding to each type of weather in each area according to the weather type of the future weather in each area;
and determining the degree that the weather parameters of each type of weather in each area exceed the preset threshold corresponding to each type of weather in each area as the future severity of each type of weather in each area.
8. The integrated urban digital emergency platform according to claim 1, further comprising:
a geological disaster monitoring module;
the geological disaster monitoring module is used for monitoring geological disaster information of the peripheral mountain areas of the city, and sending a geological disaster processing instruction to the emergency command module when the geological disaster information shows that geological disasters occur;
The emergency command module is also used for distributing resources according to the geological disaster processing instruction.
9. The integrated urban digital emergency platform according to claim 8, wherein the weather monitoring module is further configured to send a third weather early warning command of the target area to the geological disaster monitoring module when the bad weather of the target area belongs to rain and snow weather;
the geological disaster monitoring module is further used for acquiring geological information of a target area when the third weather early warning instruction is received, determining geological disaster probability of the target area according to the geological information of the target area and the early warning level carried in the third weather early warning instruction, and sending the geological disaster probability to the emergency command module when the geological disaster probability is larger than a fifth preset probability;
the emergency command module is also used for pre-distributing rescue resources for the target area according to the geological disaster probability.
10. The integrated urban digital emergency platform according to claim 9, wherein said rescue resources comprise material resources; after pre-allocation of rescue resources for the target area according to the geological disaster probability, the emergency command module is further configured to:
Determining a first distance according to the geological disaster probability;
and conveying the material resource to a position at a first distance from the target area in advance.
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| CN107316441A (en) * | 2017-06-22 | 2017-11-03 | 安徽山鼎信息科技有限公司 | A kind of Natural calamity monitoring alarm emergency system |
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| CN110533231A (en) * | 2019-08-13 | 2019-12-03 | 四川科达乐气象科技有限公司 | Disaster-ridden kind of monitoring and warning and emergency commading system |
| CN112561341A (en) * | 2020-12-18 | 2021-03-26 | 创意信息技术股份有限公司 | Multi-element dynamic cooperative disposal system for urban disasters |
| CN215647110U (en) * | 2021-08-09 | 2022-01-25 | 郑培兵 | Smart city is with intelligent monitoring system who has linkage alarming function |
| CN114091743A (en) * | 2021-11-12 | 2022-02-25 | 中国船舶重工集团公司第七一九研究所 | Mountain forest fire-fighting command decision method and system |
| CN114662583A (en) * | 2022-03-15 | 2022-06-24 | 北京金山云网络技术有限公司 | Emergency event prevention and control scheduling method and device, electronic equipment and storage medium |
| CN114723133A (en) * | 2022-04-07 | 2022-07-08 | 华北科技学院(中国煤矿安全技术培训中心) | City emergency early warning and evacuation command method and system under emergency |
| CN115909639A (en) * | 2022-09-20 | 2023-04-04 | 楼兰 | Intelligent informationized fire-fighting accident dynamic monitoring system and method |
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| CN116863708A (en) * | 2023-09-04 | 2023-10-10 | 成都市青羊大数据有限责任公司 | Smart city scheduling distribution system |
| CN116863708B (en) * | 2023-09-04 | 2024-01-12 | 成都市青羊大数据有限责任公司 | Smart city scheduling distribution system |
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