CN119811019A - Urban flood prevention early warning and emergency command integrated system and method - Google Patents
Urban flood prevention early warning and emergency command integrated system and method Download PDFInfo
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Abstract
The invention relates to the technical field of flood prevention early warning and emergency command, in particular to an integrated system and method for urban flood prevention early warning and emergency command, which are used for collecting weather, hydrology, urban drainage pipe network and video monitoring in real time through a multi-source data acquisition module, reporting data by a mobile terminal, coupling a weather time sequence predicted value based on a gate control circulation unit, drainage pipe network hydraulic model output and a terrain influence factor function through a dynamic early warning analysis module, and the dynamic early warning map with high precision is generated by real-time calibration of the weight coefficient of KL divergence, the three-dimensional visual command module generates a dynamic submerged region three-dimensional model, and the path planning visualization is realized by utilizing a particle swarm optimization algorithm to add a dangerous gradient item, and in the intelligent scheduling decision module, the improved ant colony optimization algorithm is combined with an environmental risk factor to realize the path planning and real-time catastrophe dynamic coupling. The invention greatly improves the urban flood prevention early warning accuracy and the emergency command efficiency and powerfully deals with urban flood disasters.
Description
Technical Field
The invention relates to the technical field of flood prevention early warning and emergency command, in particular to an integrated system and method for urban flood prevention early warning and emergency command.
Background
With global climate change, extreme weather events are more frequent, and the probability and intensity of urban flood disasters are significantly increased. The rapid development of urban construction changes the original underlying surface condition, greatly increases the watertight area and increases the rainfall runoff coefficient, so that the urban drainage system faces unprecedented pressure.
The existing urban flood prevention early warning system has a plurality of defects. On the one hand, multi-source data acquisition lacks systematicness and real-time. The meteorological department, hydrologic monitoring station, drain management department and the like independently collect data, the data formats are not uniform, the updating frequency is not uniform, and efficient integration and sharing are difficult to achieve. For example, weather data may not accurately reflect local microclimate changes in a city in time, and the monitoring of water flow conditions inside a municipal drainage network by the hydrologic data has hysteresis, which leads to deviation in judgment of flood conditions.
On the other hand, the early warning analysis model has poor precision. The traditional weather prediction model and the urban waterlogging model have low coupling degree, and the interaction of multiple factors such as weather factors, topography and drainage pipe network operation conditions cannot be comprehensively considered. Like in some complicated topography areas, the existing model is difficult to accurately simulate the ponding formation and diffusion process, and an early warning map cannot accurately reflect actual flood conditions, so that early warning information is insufficient in reliability and powerful support cannot be provided for flood prevention decisions.
In the emergency command link, the problem is also outstanding. The departments are difficult to cooperate with each other, and a unified visual command platform is lacking. When departments such as urban planning, traffic, emergency rescue and the like deal with flood conditions, information communication is not smooth, and command and dispatch efficiency is low. For example, when emergency resources are allocated, due to lack of real-time and comprehensive grasp of traffic road conditions, resource distribution and requirements of disaster areas, resource allocation is unreasonable, transportation route planning is poor, the resources are difficult to be delivered to the disaster areas in the optimal time, and timeliness and effectiveness of emergency rescue work are seriously affected. Meanwhile, communication guarantee between the site and the command center is unstable, communication interruption occurs at the extreme weather, and timely feedback of site information and communication of command instructions are affected, so that the urban flood prevention early warning and emergency command integrated system and method are provided for the problems.
Disclosure of Invention
The invention aims to provide an urban flood prevention early warning and emergency command integrated system and method, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
An integrated system for urban flood prevention early warning and emergency command, comprising:
The multi-source data acquisition module is used for acquiring meteorological data, hydrological data, urban drainage pipe network data and video monitoring data in real time and reporting the data by utilizing the mobile terminal;
The dynamic early warning analysis module generates a dynamic early warning map through a coupling weather prediction model and an urban waterlogging model, and the coupling weather prediction model adopts a machine learning algorithm to correct prediction parameters in real time;
the three-dimensional visual command module integrates the BIM city model and GIS geographic information data to realize three-dimensional visual display of flood situation and a multi-department collaborative operation interface;
the intelligent scheduling decision module comprises an emergency resource path planning unit based on an improved ant colony optimization algorithm and a resource matching decision unit based on dynamic weight multi-objective optimization;
and the cross-platform communication module supports the double-link guarantee of 5G-MEC edge calculation and satellite communication, and realizes the multimedia transmission of command instructions and the augmented reality AR interaction of the field terminal.
As a preferable scheme, the dynamic early warning analysis module adopts an improved space-time fusion prediction model, and a core algorithm is defined as follows:
,
Wherein, Is thatA predicted value of time;、、 as a dynamic weight coefficient, real-time calibration is carried out through KL divergence; to predict a value based on the weather timing of the gated loop unit, Is weather data; the rate of change with respect to time is output for the hydraulic model of the drainage network, Is the height of the water level of the pipeline,Is the surface runoff flow; for the terrain to influence the integrated value, As a function of the terrain influencing factor,AndIs the integration interval.
As a preferred scheme, the improved ant colony optimization algorithm in the intelligent scheduling decision module satisfies the following conditions:
,
Wherein, Is thatTime pathThe pheromone concentration on the sample; Is that Time pathThe pheromone concentration on the sample; is the volatilization coefficient of the pheromone; Is the first Ants only on the pathThe pheromone increment left on; Is the total number of ants; is an environmental risk regulator; Is that And (5) estimating the joint risk of the road ponding depth and the bridge bearing at the moment.
As a preferred solution, the resource matching decision unit adopts a dynamic weight multi-objective optimization model:
,
Wherein, 、、The weight parameters are dynamically adjusted and are linked with the early warning level; is the emergency response time; is the cost of emergency resources; The emergency resource allocation efficiency is improved;
Constraint conditions:
Wherein, the method comprises the steps of, wherein, Is the firstThe number of emergency resources; the number of types of emergency resources; the total emergency resource demand is; The demand fluctuation rate is updated in real time according to public opinion data; the time of arrival of the emergency resource; transporting path length for emergency resources; Is that Emergency resource transportation speed at moment; the influence coefficient is the path ponding; is the accumulated water depth of the road section.
As a preferred solution, in the spatiotemporal fusion prediction model:
The LSTM network is improved by adopting a dual-channel attention mechanism, and the attention weight is calculated as follows:
Wherein, the method comprises the steps of, wherein, Is thatAttention weight of moment;、、 is a trainable parameter matrix; Is that Hiding the layer state at the moment; inputting characteristics for the current moment; Is a bias term;
the SWMM model introduces a pipe fouling correction factor:
Wherein, the method comprises the steps of, wherein, Is the actual flow; Is the theoretical flow; Is the ageing coefficient of the pipeline; To maintain an impact factor; for the last maintenance time.
As a preferred solution, the three-dimensional visual command module comprises:
Based on the improved Marching Cubes algorithm, a dynamic submerged area three-dimensional model is generated, and the isosurface extraction formula is as follows:
Wherein, the method comprises the steps of, wherein, Is a space pointAn isosurface function value at the position; Node weight for octree; adding a terrain mutation response for the improved Sigmoid function; The grid point water level is; Is a water level threshold;
the path planning visualization adopts a particle swarm optimization algorithm to generate navigation light beams:
,
Wherein, Is the firstSubstitute for the firstThe particles are at the firstThe speed of the dimension; is an inertial weight; Is the first Substitute for the firstThe particles are at the firstThe speed of the dimension;、、 is a learning factor; 、、 Is that Random numbers within the interval; Is the first The particles are at the firstAn individual optimal position of the dimension; Is the first Substitute for the firstThe particles are at the firstThe position of the dimension; is at the globally optimal position Coordinates of the dimension; And (5) avoiding a high-risk area in real time for dangerous gradient items.
As a preferred embodiment, the method further comprises:
the evaluation feedback module is used for calculating a treatment scheme comprehensive score by adopting an improved TOPSIS algorithm:
Wherein, the method comprises the steps of, wherein, Is the firstA composite score for each treatment regimen; Is the first The weight of each index is dynamically adjusted by introducing a time attenuation function; Is the first Treatment scheme to positive idealDistance on the individual indicators; Is the first Treatment scheme to negative ideal solutionDistance on the individual indicators; is a risk penalty factor; Is the number of indexes.
A city flood prevention early warning and emergency command method utilizes a city flood prevention early warning and emergency command integrated system to conduct city flood prevention early warning and emergency command.
According to the technical scheme provided by the invention, the urban flood prevention early warning and emergency command integrated system and method provided by the invention have the beneficial effects that:
The dynamic early warning analysis module fuses weather prediction and an urban waterlogging model, combines LSTM weather time sequence prediction, drainage pipe network hydraulic model output and a terrain influence factor function by using an innovative space-time fusion prediction model, and can flexibly adjust the weight of each factor according to different scenes by means of KL divergence real-time calibration of dynamic weight coefficients, so that the accuracy and timeliness of the waterlogging early warning are greatly improved, and firm and reliable data support is provided for flood prevention decision;
The method comprises the steps of high-efficiency resource allocation, constructing a time-varying weight three-objective optimization system by a resource matching decision unit, dynamically adjusting weight parameters according to early warning grades, comprehensively balancing emergency response time, resource cost and allocation efficiency, and realizing optimal allocation of emergency resources;
The visual command comprises a three-dimensional visual command module, a path planning visualization, a particle swarm optimization algorithm, a dynamic submerged area three-dimensional model, a path planning visualization, a dynamic visual command module and a dynamic visual command module, wherein the three-dimensional visual command module integrates BIM city model and GIS geographic information data, the dynamic submerged area three-dimensional model is generated by means of an improved MarchangCubes algorithm, and the response to terrain mutation is enhanced by utilizing an improved Sigmoid function, so that the submerged area is displayed more accurately and intuitively;
The reliable communication guarantee is that the cross-platform communication module adopts a double-link guarantee mechanism of 5G-MEC edge calculation and satellite communication, ensures that the multimedia transmission of command instructions is still stable and reliable under complex severe environments;
The evaluation feedback module calculates the comprehensive score of the treatment scheme by using the improved TOPSIS algorithm, dynamically adjusts the weight by introducing the time decay function, and simultaneously considers the risk penalty factor to comprehensively and dynamically evaluate different treatment schemes, thereby providing powerful data basis for the improvement and optimization of the follow-up flood prevention work and promoting the continuous improvement of the urban flood prevention early warning and emergency command overall level.
Drawings
Fig. 1 is a schematic diagram of the overall structure of an integrated system and method for urban flood control warning and emergency command.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. 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.
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and the specific embodiments.
As shown in fig. 1, the embodiment of the invention provides an integrated system for urban flood prevention early warning and emergency command, which comprises a multi-source data acquisition module, a dynamic early warning analysis module, a three-dimensional visual command module, an intelligent scheduling decision module and a cross-platform communication module.
In this embodiment, the multi-source data acquisition module is configured to acquire meteorological data, hydrological data, urban drainage network data, and video monitoring data in real time, and report the data by using the mobile terminal;
Furthermore, the multisource data acquisition module is used for collecting and integrating various key data in an urban flood prevention early warning and emergency command integrated system, provides necessary basic support for subsequent early warning analysis and command decision, is an important link for guaranteeing efficient development of urban flood prevention work, and is specific in that:
1. data acquisition equipment and technology:
The weather data acquisition equipment is provided with a special weather monitoring station, a rainfall sensor, an anemometer, an air temperature and air pressure monitor and other equipment, and is used for accurately collecting weather data, wherein the rainfall sensor can monitor the rainfall and the rainfall intensity in real time, provides a key basis for predicting the waterlogging risk, can timely capture rainfall change before the storm comes, and early warn the water accumulation situation which possibly occurs in advance;
The hydrological data acquisition facility comprises hydrological monitoring equipment such as a water level gauge, a flow meter and the like arranged in water areas such as rivers, lakes, reservoirs and the like, wherein the water level gauge can monitor the water level change in real time, the flow meter can accurately measure the water flow, for example, the hydrological dynamics can be mastered in time at the junction of the rivers or in areas where flood is likely to occur through the equipment, in addition, more comprehensive hydrological information including flow velocity distribution and the like can be obtained by utilizing advanced technologies such as an acoustic Doppler flow profiler (ADCP) and the like, detailed data is provided for flood evolution simulation, and the equipment can transmit the data to a system in real time in a wired or wireless transmission mode;
The urban drainage pipe network data acquisition technology comprises the steps of adopting equipment such as a pipeline robot, a liquid level sensor and the like to acquire drainage pipe network data, enabling the pipeline robot to go deep into a drainage pipeline, shooting the internal condition of the pipeline, detecting whether the pipeline is damaged, deposited and the like, installing the liquid level sensor at a key node of the pipeline, monitoring the height of the water level of the pipeline in real time, digitally managing the layout, pipe diameter, gradient and other information of the drainage pipe network by combining a Geographic Information System (GIS) technology, and constructing an accurate drainage pipe network model to provide a basis for analyzing drainage capacity and waterlogging risk;
The video monitoring data acquisition equipment is provided with high-definition cameras in key areas such as urban roads, bridges, low-lying areas and the like to form a video monitoring network, wherein the cameras have night vision function and automatic zooming capability, can clearly shoot pictures such as ponding depth, water flow speed, road traffic conditions and the like;
2. and (3) data acquisition and transmission flow:
The data acquisition comprises various data acquisition devices continuously collecting corresponding data according to preset time intervals or triggering conditions, a meteorological monitoring station, hydrologic monitoring equipment, a drainage pipe network sensor, a video monitoring camera and the like which work simultaneously to ensure all-dimensional and multidimensional data acquisition, wherein in the data acquisition process, the acquired data are subjected to preliminary quality detection, obvious error or abnormal data are removed, and the accuracy of the data is ensured;
The data transmission, which is to transmit the collected data to the data processing center through various communication modes, adopts a wired network (such as optical fiber) to transmit the data which is close to the distance and has high real-time requirement, such as urban drainage network data and partial video monitoring data, ensures the stability and high speed of data transmission, and transmits meteorological data, hydrological data and video monitoring data with wider distribution by utilizing a wireless communication technology (such as 4G/5G, wi-Fi, etc.), in addition, partial equipment also has a local storage function to automatically supplement the data after communication is recovered in order to prevent the data loss caused by communication interruption;
the data integration comprises data transmitted to a data processing center, classified integration according to different types and sources, correlation matching of meteorological data, hydrological data, drainage pipe network data and video monitoring data, forming a unified data set, further removing repeated data and filling missing data through data cleaning and preprocessing, and providing a high-quality data base for subsequent analysis and application;
3. importance in flood control work:
By coupling the weather prediction model with the urban flood model and combining the real-time weather, hydrology and drainage pipe network data, a more accurate dynamic early warning map can be generated, the occurrence time, place and severity of the flood can be predicted in advance, and more preparation time is striven for urban flood prevention work;
Based on the collected real-time data, the intelligent scheduling decision module can plan an emergency resource path through an improved ant colony optimization algorithm, and a dynamic weight multi-objective optimization model is utilized to carry out resource matching decision, so that reasonable allocation of emergency resources is realized, and the efficiency and effect of flood prevention emergency response are improved;
The three-dimensional visual command module integrates BIM city model and GIS geographic information data by means of the data provided by the multi-source data acquisition module, so that three-dimensional space visual display of flood situation is realized;
The multisource data acquisition module plays a key role in urban flood prevention early warning and emergency command work through diversified data acquisition equipment and technology and strict data acquisition and transmission flow, and provides firm data guarantee for guaranteeing urban safety flood.
In the embodiment, the dynamic early warning analysis module generates a dynamic early warning map by coupling a weather prediction model and an urban waterlogging model, and the coupled weather prediction model adopts a machine learning algorithm to correct prediction parameters in real time;
Further, the dynamic early warning analysis module is in the central early warning analysis position in the urban flood prevention early warning and emergency command integrated system, deeply analyzes the multi-source data by fusing various models and algorithms to generate an accurate dynamic early warning map, provides a key decision basis for urban flood prevention work, and effectively improves the capability of the urban to cope with flood disasters, and is specific:
1. Core algorithm and model fusion:
the improved space-time fusion prediction model adopts an improved space-time fusion prediction model, creatively integrates various data prediction methods, and has a core algorithm formula of
;
Wherein, among them,Is thatA predicted value of time;、、 as a dynamic weight coefficient, real-time calibration is carried out through KL divergence; to predict a value based on the weather timing of the gated loop unit, Is weather data; the rate of change with respect to time is output for the hydraulic model of the drainage network, Is the height of the water level of the pipeline,Is the surface runoff flow; for the terrain to influence the integrated value, As a function of the terrain influencing factor,AndIs an integration interval;
The time sequence prediction is carried out on the meteorological data based on the gate control circulation unit, so that time sequence features in the meteorological data can be effectively captured, future meteorological variation trends can be accurately predicted, such as the prediction of key meteorological elements including rainfall intensity, duration and the like, and meteorological basic data are provided for subsequent waterlogging risk assessment;
The weather prediction model provides weather information such as rainfall, and the urban waterlogging model (such as SWMM model) simulates the processes of surface runoff formation, drainage pipe network water flow movement and the like according to the weather data and combining urban drainage pipe network data, terrain data and the like; The change rate of time is output for the hydraulic model of the drainage pipe network, the running states of the drainage pipe network at different moments are reflected, and whether the drainage capacity of the pipe network can cope with the runoff generated by the current rainfall is analyzed, so that the possible occurrence area and time of waterlogging are predicted;
Dynamic weight coefficient calibration in the formula 、、The dynamic weight coefficient is calibrated in real time through KL divergence, the calibration mechanism can dynamically adjust the weight of each part of data in a prediction result according to the importance changes of meteorological data, drainage pipe network data and topographic data at different moments, and the influence of the meteorological data on the prediction waterlogging risk is larger at the early stage of a stormThe weight may be relatively high, as rainfall continues, the importance of the operational state data of the drain network increases,The weight can be correspondingly adjusted, so that the prediction model can adapt to the change of the actual situation in real time, and the prediction accuracy is improved;
2. Algorithm optimization and improvement:
The method for improving the LSTM network by adopting the dual-channel attention mechanism comprises the steps of adopting the dual-channel attention mechanism to improve the LSTM network in a space-time fusion prediction model, wherein the attention weight calculation mode is as follows Wherein, the method comprises the steps of, wherein,Is thatAttention weight of moment;、、 is a trainable parameter matrix; Is that Hiding the layer state at the moment; inputting characteristics for the current moment; The mechanism distributes different attention weights for the LSTM network by learning the importance of input features at different moments, can focus on meteorological elements which are more critical to rainfall prediction, such as air pressure change, humidity abnormality and the like, and ignores some relatively secondary information when processing meteorological data, thereby capturing effective information in the meteorological data more accurately and improving the accuracy of meteorological time sequence prediction;
The SWMM model is introduced with a pipeline fouling correction factor, wherein the SWMM model is optimized, the pipeline fouling correction factor is introduced, and the actual flow calculation formula is as follows Wherein, the method comprises the steps of, wherein,Is the actual flow; Is the theoretical flow; Is the ageing coefficient of the pipeline; To maintain an impact factor; Considering that the drainage capacity of the pipeline is reduced due to siltation in the long-term use process, the correction factor can correct the theoretical flow according to the ageing degree and maintenance condition of the pipeline, so that the model is more in line with the actual drainage condition, and the reliability of waterlogging prediction is improved;
3. early warning map generation and application:
The dynamic early warning map generation comprises the steps of generating a dynamic early warning map based on the algorithm and the model by a dynamic early warning analysis module, displaying waterlogging risk levels of different areas of a city at different moments in the future in an intuitive visual mode, combining geographic information of a GIS, and accurately positioning the risk areas;
The generated early warning map provides important basis for subsequent emergency command work; the three-dimensional visual command module displays the situation of flood according to the early warning map, provides visual information support for the cooperative command of multiple departments, and enables each department to develop flood prevention and rescue work in a targeted manner according to the risk area and the grade;
The dynamic early warning analysis module realizes accurate prediction and dynamic early warning of urban waterlogging risk through a complex and precise algorithm model, plays an indispensable key role in urban flood prevention early warning and emergency command systems, and provides powerful support for guaranteeing urban safety and people's life and property safety.
In the embodiment, the three-dimensional visual command module integrates the BIM city model and GIS geographic information data to realize three-dimensional space visual display of flood situation and multi-department collaborative operation interface;
furthermore, the three-dimensional visual command module is a key component of an urban flood prevention early warning and emergency command integrated system, presents complex flood information in visual and image three-dimensional form by means of advanced technical means, provides a high-efficiency cooperative operation platform for flood prevention command, greatly improves the scientificity and accuracy of command decision, and is specific:
1. data integration and fusion:
the BIM and GIS data integration comprises integrating a BIM city model and GIS geographic information data, wherein the BIM model records three-dimensional structure information of city buildings, infrastructures and the like in detail, the position and the attribute of each layer of a building and each key facility are accurate, the GIS geographic information data covers the macroscopic geographic information of topography and landform, water system distribution, traffic network and the like, and a comprehensive and accurate city three-dimensional geographic information scene can be constructed by integrating the two information, for example, when a flood condition of a certain area of a city is checked, the topography fluctuation and the road trend of the area can be seen, the structure and the layout of the building can be clearly known, and a comprehensive data base is provided for analyzing the influence range of the flood condition and formulating a response strategy;
The three-dimensional visual command module is connected with multi-source information such as weather data, hydrologic data, urban drainage pipe network data, video monitoring data and the like, and realizes real-time association with a three-dimensional scene, for example, the real-time water level data is associated with rivers and lakes in the three-dimensional scene, the height of water bodies in the three-dimensional scene can be correspondingly changed when the water level changes, rainfall areas and intensities in the weather data are intuitively displayed on a three-dimensional map, and the water accumulation areas and the waterlogging risk can be more accurately predicted by combining the topography and the drainage pipe network information;
2. Three-dimensional visual display function:
the flood situation real-time display comprises the steps of utilizing the fused data, realizing the three-dimensional space visual display of the flood situation by a three-dimensional visual command module, displaying the information such as flood submerging range, water level change trend, road ponding depth and the like in a visual mode, for example, displaying the ponding depth of different areas through rendering with different colors and transparencies, wherein red represents the area with deeper ponding and high danger degree, and blue represents the area with shallower ponding;
The construction of the dynamic submerged area three-dimensional model, namely generating the dynamic submerged area three-dimensional model based on an improved MarchingCubes algorithm, wherein the isosurface extraction formula is as follows Wherein, the method comprises the steps of, wherein,Is a space pointAn isosurface function value at the position; Node weight for octree; adding a terrain mutation response for the improved Sigmoid function; The grid point water level is; Is a water level threshold value, and the algorithm is based on the water level height of different grid points And water level thresholdThrough the weight of the octree nodesAnd improved Sigmoid functionCalculating spatial pointsEquivalent surface function value atThe improved Sigmoid function increases the landform mutation response, so that the model can more accurately reflect the flooding condition of flood under complex terrain conditions, and provides more accurate basis for commanding decisions;
3. path planning and co-operation:
path planning visualization, wherein the path planning visualization adopts a particle swarm optimization algorithm to generate navigation light beams, and the formula is that
,
Wherein, Is the firstSubstitute for the firstThe particles are at the firstThe speed of the dimension; is an inertial weight; Is the first Substitute for the firstThe particles are at the firstThe speed of the dimension;、、 is a learning factor; 、、 Is that Random numbers within the interval; Is the first The particles are at the firstAn individual optimal position of the dimension; Is the first Substitute for the firstThe particles are at the firstThe position of the dimension; is at the globally optimal position Coordinates of the dimension; As dangerous gradient items, high-risk areas are avoided in real time; the algorithm takes inertial weights into account when planning paths Learning factor、、Individual optimal positions of particlesGlobal optimum positionDangerous gradient termBy the synergistic effect of the parameters, an optimal path avoiding high-risk areas (such as a region with serious water accumulation and road damage) can be generated and displayed in a three-dimensional scene in the form of navigation beams;
The system comprises a multi-department collaborative operation interface, a three-dimensional visual command module, a traffic department, a water conservancy department and a control system, wherein the three-dimensional visual command module provides a collaborative operation interface for the multi-departments, integrates service functions of the multi-departments such as emergency management, fire control, traffic, water conservancy and the like, can perform information sharing and collaborative operation under the same three-dimensional scene, such as marking important protection areas, issuing task instructions, reporting work progress and the like, for example, the emergency management department can mark areas needing emergency rescue in the three-dimensional scene and give rescue tasks to the fire department;
the three-dimensional visual command module provides an omnibearing and visual decision support platform for urban flood control command through data integration, visual display and collaborative operation functions, effectively improves the capacity and level of urban flood control emergency command, and plays an important role in guaranteeing urban safety flood.
In the embodiment, the intelligent scheduling decision module comprises an emergency resource path planning unit based on an improved ant colony optimization algorithm and a resource matching decision unit based on dynamic weight multi-objective optimization;
The intelligent scheduling decision module is a core component of an integrated system of urban flood prevention early warning and emergency command, plays a key role in flood prevention emergency response, integrates an advanced algorithm, comprehensively considers various factors, provides scientific decision basis for emergency resource allocation and path planning, ensures quick and efficient response in the face of flood conditions, reduces loss to the greatest extent, and is specific:
1. emergency resource path planning unit:
the improved ant colony optimization algorithm principle is that the unit adopts the improved ant colony optimization algorithm to plan an emergency resource transportation path, and the core formula is as follows
,
Wherein, Is thatTime pathThe concentration of the pheromone can volatilize along with the time, and the volatilization coefficient of the pheromone,;Is thatTime pathThe pheromone concentration on the sample; Is the first Ants only on the pathThe pheromone increment left on; Is the total number of ants; is an environmental risk regulator; Is that Moment road ponding depth and bridge bearing combined risk evaluation value, each antOn the pathWill leave a pheromone incrementThe sum of the pheromone increment left by all ants can influence the concentration of the path pheromone, and simultaneously, the environmental risk regulating factor is introducedAndMoment road ponding depth and bridge bearing combined risk evaluation valueThis allows the algorithm to fully take into account environmental risk factors when calculating the path pheromone concentration;
compared with the traditional algorithm, the algorithm has the advantages that the algorithm can better adapt to complex and changeable environments of urban flood prevention compared with the traditional algorithm, for example, under the condition that road ponding is caused by heavy rain and the bearing capacity of bridges is limited, the algorithm can be in real time The evaluation value reduces the pheromone concentration of the high-risk path, guides ants (representing emergency resource transportation path selection) to avoid roads with serious ponding or insufficient bridge bearing, and selects a safer and more efficient path; in practical application, whether a fire-fighting vehicle goes to a fire and flood concurrent area or medical materials go to a centralized placement point of a disaster-stricken crowd, an optimal path can be planned by means of the algorithm;
2. a resource matching decision unit:
the dynamic weight multi-objective optimization model construction, wherein the resource matching decision unit uses the dynamic weight multi-objective optimization model to carry out resource matching decision, and the objective function is that
Wherein, the method comprises the steps of, wherein,、、The weight parameters are dynamically adjusted and are linked with the early warning level; is the emergency response time; is the cost of emergency resources; for emergency resource allocation efficiency, when the early warning level is higher and the disaster is urgent, the emergency response time is shorter Weights of (2)The method can increase, emphasize that the resources are put into use as soon as possible, and emergency resource cost is emphasized when the early warning level is relatively low and the resource allocation is more important to cost effectivenessWeights of (2)Can correspondingly improve the emergency resource allocation efficiencyAlso considered in the model is that,The weight of the resource allocation process is ensured to be carried out efficiently;
constraint setting and meaning the model sets a series of constraints including Ensuring that the quantity of emergency resources can meet the actual demand, and simultaneously taking the demand fluctuation rate into considerationUpdating in real time according to public opinion data so as to cope with the possible resource demand change; comprehensively consider the emergency resource transportation path length 、Transport speed at momentAnd path water impact coefficientDepth of accumulated water in road sectionEnsuring that the resource can reach the disaster area within a specified time; the constraint conditions provide comprehensive limitation and guidance for resource matching decision in terms of resource quantity, arrival time, weight balance and the like, so that the decision result meets the actual flood prevention requirement (among them, Is the firstThe number of emergency resources; the number of types of emergency resources; the total emergency resource demand is; The demand fluctuation rate is updated in real time according to public opinion data; the time of arrival of the emergency resource; transporting path length for emergency resources; Is that Emergency resource transportation speed at moment; the influence coefficient is the path ponding; Is the road section ponding depth);
3. Module cooperation and overall performance:
The intelligent scheduling decision module is closely cooperated with other modules in the system, the multi-source data acquisition module provides data such as weather, hydrology, drainage pipe network, on-site real-time video and the like for the intelligent scheduling decision module, the data are used for evaluating the severity of flood conditions, road traffic conditions and the like and providing basic information for path planning and resource matching, the early warning map and the forecast data generated by the dynamic early warning analysis module help the intelligent scheduling decision module to determine the emergency response priority and the resource demand scale of different areas, and the three-dimensional visual command module displays the result of the intelligent scheduling decision module in an intuitive three-dimensional form, so that command personnel can conveniently make decisions and command coordination, and information sharing and collaborative work among the modules are realized;
The intelligent scheduling decision module can rapidly plan an optimal emergency resource transportation path according to real-time flood conditions through cooperative work of the emergency resource path planning unit and the resource matching decision unit, reasonably allocate various emergency resources and realize efficient utilization of the resources, and in actual flood control work, the intelligent scheduling decision module can greatly improve emergency response speed, ensure rescue force to arrive at a disaster-stricken area in time, improve scientificity and accuracy of flood control emergency command and play an important role in guaranteeing urban safety and life and property safety of people.
In the embodiment, a cross-platform communication module supports double-link guarantee of 5G-MEC edge calculation and satellite communication, and achieves multimedia transmission of command instructions and augmented reality AR interaction of a field terminal;
Furthermore, the cross-platform communication module is used as a key hub of an urban flood prevention early warning and emergency command integrated system, plays an indispensable role in ensuring efficient and stable transmission of information, integrates an advanced communication technology, constructs a multi-link guarantee system, realizes multimedia transmission of command instructions and Augmented Reality (AR) interaction of field terminals, and forcefully promotes coordination and efficient development of flood prevention emergency command work, wherein the method comprises the following steps:
1. Communication link guarantee:
The 5G-MEC edge computing link ensures that data can be quickly transmitted by a cross-platform communication module through the high-speed and low-delay characteristics of the 5G network, can meet the requirements of quick uploading and downloading of a large amount of real-time data (such as high-definition video monitoring data, high-resolution GIS map data and the like), enables a command center to acquire detailed information of on-site flood conditions in real time, such as road ponding depth, drainage conditions of a water outlet and the like, provides accurate basis for decision making, and simultaneously, the MEC (mobile edge computing) technology is combined to sink computing and storage capacity to the edge of the network, reduces data transmission delay and improves the response speed of the system, for example, data acquired by on-site terminal equipment can be initially processed and analyzed at a local edge server, key information is quickly generated and then transmitted to the command center, the burden of the core network is reduced, and communication efficiency is further improved, so that command instructions can be quickly transmitted to on-site terminals to realize real-time command of flood prevention work;
The satellite communication link is used as a standby guarantee for coping with complex flood prevention environments, such as under the condition that the 5G network is not covered enough or the ground communication network is damaged due to disasters, has the advantages of wide coverage and no limitation of geographical conditions, can ensure that a command center is in contact with areas such as remote disaster areas and mountain areas which are difficult to communicate through the ground network, can transmit various information such as voice, data and images, and can ensure the transmission of key command instructions and important disaster information;
2. command instruction transmission function:
The multimedia transmission comprises a cross-platform communication module, a command center, a communication module and a communication module, wherein the cross-platform communication module supports multimedia transmission of command instructions, can integrate and transmit various forms of information such as characters, voice, images and videos, can quickly communicate decision deployment through voice instructions, improves communication efficiency and avoids delay time caused by character input;
The module adopts advanced communication protocol and signal processing technology to ensure the accuracy and the integrity of command instructions in the transmission process, monitors and repairs the transmitted data in real time through mechanisms such as data verification, error correction coding and the like to avoid the loss or the error transmission of the instructions caused by signal interference or transmission errors;
3. on-site terminal interaction function:
The Augmented Reality (AR) interaction comprises the steps of realizing an AR interaction function of a field terminal through a cross-platform communication module, combining virtual information with a real scene through an AR technology, enabling field staff to wear AR equipment (such as intelligent glasses), checking virtual marking information in a real environment, such as dangerous area warning, rescue route planning, equipment operation guidance and the like, enabling the AR equipment to display structural schematic diagrams, fault checking steps and maintenance guidance information of the equipment in the real scene when the drainage equipment is salvaged, helping maintenance staff to quickly locate fault points and repair the fault points, improving maintenance efficiency, and enabling the staff to interact with the command center in real time through the AR equipment, such as returning the field view to the command center in real time, enabling the command staff to know the field situation more intuitively and make more accurate decisions;
The on-site working efficiency and safety are improved, the AR interactive function greatly improves the on-site working efficiency and safety, reduces the time for workers to review paper data or operate complex terminal equipment, enables the workers to concentrate more energy on actual working tasks, effectively avoids safety accidents caused by human negligence or unfamiliar complex operation through real-time displayed risk prompts and operation guidelines, and can display the information of ponding depth, potential danger and the like in real time when rescue is carried out in dangerous ponding areas, thereby providing safety guarantee for rescue workers and improving the efficiency and success rate of rescue actions;
The cross-platform communication module breaks through the barriers of information transmission and interaction through double-link security, multimedia command instruction transmission and AR interaction functions of the field terminal, realizes efficient communication and cooperation between the flood control command center and the field, provides powerful communication support for urban flood control early warning and emergency command work, and effectively improves flood control emergency response capability.
In the embodiment, an evaluation feedback module calculates a treatment scheme comprehensive score by adopting an improved TOPSIS algorithm;
further, the assessment feedback module plays an important role in an integrated system of urban flood control early warning and emergency command, quantitatively assesses a flood control treatment scheme through a scientific algorithm, feeds back an assessment result to the system, promotes continuous optimization of the system, and improves the overall efficiency of flood control work, and the method comprises the following steps:
scheme evaluation algorithm the evaluation feedback module adopts improved TOPSIS algorithm to calculate the comprehensive score of treatment scheme, and the formula is Wherein, the method comprises the steps of, wherein,Is the firstThe comprehensive score of each treatment scheme is a core index for measuring the advantages and disadvantages of the scheme; Is the first The weight of each index is dynamically adjusted by introducing a time decay function, and the weight of some indexes related to quick response is relatively high in the early stage of flood control; Is the first Treatment scheme to positive idealDistance on the individual indicators; Is the first Treatment scheme to negative ideal solutionDistances on the indexes, which are used for measuring the difference between the scheme and the optimal and worst conditions on each index; as a risk penalty factor, for a scheme with high risk, the deduction force is increased, so that the evaluation result can truly reflect the risk degree of the scheme; The comprehensive effect of the scheme is comprehensively evaluated in terms of the number of indexes, including the aspects of emergency response time, resource allocation efficiency, disaster damage control and the like;
The method comprises the steps of dynamically adjusting and feedback optimizing indexes, wherein the evaluation indexes are dynamically adjusted according to actual flood prevention conditions and system operation feedback, mining new indexes which have obvious influence on flood prevention results or reallocating existing index weights by analyzing historical flood prevention data and comparing implementation effects of different schemes, if a certain area is found to have rescue delay caused by unsmooth information transmission in certain flood prevention, subsequently improving the weight of information transmission efficiency in the evaluation indexes, feeding back the scheme evaluation results to each link of a system by an evaluation feedback module, providing references for an intelligent scheduling decision module to help the intelligent scheduling decision module optimize resource allocation and path planning strategies, assisting a dynamic early warning analysis module to perfect an early warning model, improving early warning accuracy, enabling a three-dimensional visual command module to display more specific information, improving the scientificity of command decisions and promoting continuous optimization of the whole flood prevention system;
The overall efficiency of the flood control work is improved, the module effectively improves the overall efficiency of the flood control work through evaluation feedback of the treatment scheme, in the actual flood control process, different rescue schemes are evaluated, the scheme with high comprehensive score is selected for execution, the rescue efficiency can be remarkably improved, casualties and property loss are reduced, after each flood control work is finished, the evaluation feedback module carries out repeated evaluation on the whole process, and the experience teaching and training is summarized, so that precious references are provided for the subsequent flood control work, the urban flood control early warning and emergency command system is continuously perfected, and future flood disasters are better dealt with.
A city flood prevention early warning and emergency command method realizes real-time monitoring, accurate early warning, efficient command and scientific assessment of city flood conditions through multi-module cooperative work so as to ensure city safety, and comprises the following detailed operation steps:
The method comprises the steps of S1, data acquisition and transmission, wherein a multi-source data acquisition module collects weather, hydrology, drainage pipe networks and video monitoring data in real time by using professional equipment and a mobile terminal, a weather monitoring station acquires data such as precipitation, wind speed and the like, hydrology monitoring equipment monitors water level, flow and the like, a drainage pipe network sensor acquires pipeline water level and drainage capacity information, and a video monitoring camera captures field pictures, and the data are stably transmitted to a data processing center in a wired or wireless communication mode to provide comprehensive and accurate data support for subsequent analysis;
S2, dynamic early warning analysis, namely receiving collected data by a dynamic early warning analysis module, processing the data by using an improved space-time fusion prediction model, calculating waterlogging risk values of different moments and areas by combining the meteorological prediction model with an urban waterlogging model and combining terrain data to generate a dynamic early warning map, for example, predicting the meteorological data by using an LSTM (localized laser technology) network, simulating the water flow of a drainage pipe network by combining an SWMM (single wave multiple machine) model, correcting a prediction result according to a terrain influence factor, and if the waterlogging risk of a certain area is predicted to be high, timely sending early warning information by a system and notifying related departments and personnel;
Step S3, visual command and decision, wherein a three-dimensional visual command module integrates BIM city model and GIS geographic information data to display flood situation, a command personnel checks information such as submerged area, water level change and the like in a three-dimensional scene to conduct multi-department collaborative command;
step S4, cross-platform communication and execution, namely, a cross-platform communication module transmits command instructions to a field terminal in a multimedia mode through a double link of 5G-MEC edge calculation and satellite communication;
And S5, evaluating feedback and optimizing, wherein an evaluation feedback module adopts an improved TOPSIS algorithm to comprehensively evaluate the treatment scheme and calculate scores, feedback information is provided for other modules according to the evaluation result and the advantages and disadvantages of the analysis scheme, for example, an intelligent scheduling decision module improves a prediction model according to a feedback optimized resource allocation strategy, and the flood prevention capability of the system is continuously improved by a dynamic early warning analysis module.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
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