292 results about "Intelligent city" patented technology

The invention belongs to the technical field of smart city construction and intelligent construction management, and particularly relates to an intelligent scheduling and cooperation system and method for the whole life cycle of city reconstruction. The system comprises an edge sensing layer, a digital twinning network module, a space-time brain module, a block chain collaborative trust layer and an XR collaborative interaction layer. The system collects multi-source data of a construction site in real time through a 5G edge device, realizes fusion modeling of BIM, GIS and TIN models by using a graph convolutional neural network, and performs multi-target scheduling optimization in combination with meta reinforcement learning and a dynamic graph neural network; and meanwhile, construction task verification and fund payment linkage is realized through a block chain smart contract, and immersive cooperation and visual acceptance are provided in cooperation with an AR / VR platform. According to the method, the problems of model splitting, scheduling response lagging, low data collaboration efficiency, insufficient credibility of the performance process and the like in the urban reconstruction project are solved, and the intelligence, transparency and automation level of the construction process is remarkably improved.

The invention relates to the technical field of smart city data visualization, in particular to a visual smart city display method, which comprises the following steps: S1, collecting traffic flow data, energy consumption data, environment monitoring data and city three-dimensional geographic information data in real time; s2, constructing a reference three-dimensional model with a space coordinate system; s3, mapping the data into a dynamic data layer with a timestamp; s4, superposing the dynamic data layer to the reference three-dimensional model according to space-time coordinates to generate a fused dynamic scene; s5, receiving deduction parameters input by a user, and calculating a corresponding evolution path in real time; and S6, converting the evolution path into a dynamic visualization effect, and outputting the dynamic visualization effect to a display terminal. According to the invention, through integrated processing of multi-source dynamic data fusion, space-time path deduction and visual output, continuous expression and dynamic evolution display of the operation state of the smart city are realized.

The invention provides a smart city security abnormal event detection method and system, and the method comprises the steps: obtaining an initial large model, and adding a positioning reasoning normal form in the initial large model, so as to obtain an adjustment large model; designing and adjusting a reward function of the large model; performing first training on the adjustment large model based on a reward function and a first training sample to obtain a first training model; updating the reward function to obtain an updated reward function, and training the first training model for the second time based on a second training sample and the updated reward function to obtain a second training model; and inputting to-be-recognized smart city security anomaly input data into the second training model to output an anomaly recognition result, the method has significant advantages in the aspects of target positioning precision, interpretability and training efficiency, can adapt to various city security scenes, and provides important technical support for smart city construction.

The invention relates to a smart city planning monitoring system, which comprises a multi-source data acquisition module, a database construction and management module, a planning analysis and monitoring module, a communication cooperation module and an interactive decision support module, the database construction and management module is used for constructing and managing a database of urban planning and monitoring data, the planning analysis and monitoring module is used for planning scheme evaluation and progress tracking, the communication cooperation module is used for data communication and module cooperation, and the interactive decision support module is used for data interaction, monitoring visualization and decision support. According to the smart city planning monitoring system, a city planning multi-source data fusion algorithm based on kernel density analysis is put forward to fuse multi-source data, and a smart city planning monitoring algorithm based on analytic hierarchy process and fuzzy comprehensive evaluation is put forward to monitor and evaluate smart city planning.

The invention relates to a smart city ESG multi-source data visualization analysis method, device and equipment and a medium, and the method comprises the steps: carrying out the standardized semantic annotation and space-time alignment of city multi-source heterogeneous data, and generating a semantic triple set with a space-time label; the real-time intensity of the causal relationship in the ESG dynamic knowledge graph is constructed and quantified; semantic binding is carried out on the map and the city information model, and a visual descriptor is generated; discovering and rendering a causal relationship chain in the three-dimensional scene based on user interaction; and deducing simulation intervention and optimizing model parameters. According to the method, dynamic and integrated presentation and interactive deduction of complex causal relationships of environment, society and governance in a multi-dimensional space-time scene are realized, and the problems of surface analysis, disjunction of data and space and insufficient decision support in the prior art are effectively solved.

The invention relates to the technical field of artificial intelligence, in particular to a visual large screen development method and system based on a multi-modal large model, and the method comprises the following steps: a demand analysis step, an intelligent generation step, a visual arrangement step, a configuration management step and an operation support step. The method has the beneficial effects that the system can synchronously analyze natural language instructions, business data parameters and visual reference examples through a multi-modal semantic alignment engine, and a design scheme with both function completeness and aesthetic consistency is generated. In scenes of smart city situation awareness, industrial equipment real-time monitoring and the like, a user only needs to input demand descriptions of'displaying energy consumption trends and abnormal point locations of all regions in recent half a year 'and the like, a complete large screen scheme including a thermodynamic map, a time sequence broken line graph and a 3D alarm mark can be automatically generated, and the development period is shortened by more than 70% compared with a traditional mode.

The invention discloses a smart city planning three-dimensional scene reconstruction optimization system combined with semantic segmentation, and belongs to the technical field of three-dimensional scene reconstruction optimization. The system comprises a data sensing module which collects aerial images and laser point clouds, and complements a sheltered area to obtain city modeling data; the preprocessing module performs denoising, data registration and data fusion on the city modeling data to generate texture point cloud data; the semantic understanding module realizes multi-modal semantic segmentation of the texture point cloud data through a fine-tuned SAM network and an improved RandLA-Net, and semantic tag data is obtained through restoration and optimization; the reconstruction optimization module constructs an initial three-dimensional grid model based on the texture point cloud data, and optimizes a ground feature boundary and a missing region of the model in combination with a semantic tag; and the output application module converts the optimized model into a standard format and outputs the model. Through deep coupling of semantic segmentation and reconstruction optimization, the precision of the three-dimensional scene model is improved, and reliable support is provided for smart city planning.

The invention discloses an intelligent video monitoring system and method supporting AI strategy cloud side end cooperative execution. According to the system, unified management of computing power resources and dynamic deployment of an AI algorithm are realized based on an extended standardized protocol through a three-level architecture of a cloud side center platform, an edge computing node and an end side camera. The method comprises the following steps: a cloud platform acquires computing power information of edge equipment; an AI algorithm execution strategy is generated and issued according to service requirements; if the required algorithm is not deployed in the equipment, the equipment is controlled to download and automatically deploy an algorithm module; and finally, the driving equipment executes AI analysis and recovers the structured data. According to the invention, AI computing tasks are reasonably distributed through a cloud side-end cooperative computing architecture, so that the computing power construction cost of a central platform is effectively reduced; through algorithm and hardware decoupling and a standardized protocol interface, ecological binding is broken, on-demand loading and flexible scheduling of the algorithm are realized, and the economical efficiency, the flexibility and the intelligent level of the system in large-scale scenes such as smart cities and the like are remarkably improved.

The invention relates to the technical field of big data, and discloses a smart city big data multi-source heterogeneous acquisition and convergence fusion method, which comprises the following steps: step A, multi-source heterogeneous data acquisition: performing data acquisition by using multiple data interface protocols; b, preprocessing and standardizing the data, cleaning the data, and performing unified processing on the data; step C, data aggregation and integration: carrying out logic partitioning on the preprocessed data according to a subject domain; d, performing data fusion and semantic understanding, and performing calculation and recognition by utilizing a machine learning algorithm and semantic similarity; e, data quality control; and step F, a data security and privacy protection mechanism. By adopting a distributed data acquisition framework, various data sources in the smart city are comprehensively covered. By means of the design, universality and diversity of data sources are guaranteed, a rich data basis is provided for subsequent data processing, and the efficiency and accuracy of data collection are greatly improved.

The invention relates to the technical field of smart city services, and discloses a city service agent scheduling method and system based on intention recognition, and the method comprises the steps: collecting the multi-modal original request data of a city complex, and carrying out the preprocessing and feature extraction; identifying a multi-level intention, extracting an intention entity and a constraint condition, and evaluating an intention priority; constructing an intelligent agent capability model and a knowledge base, calculating a semantic matching degree between the intention and the intelligent agent, and generating an intelligent agent combination scheme according to a matching result; constructing a multi-objective optimization model and generating a scheduling scheme of a single intention and a composite intention; task issuing is carried out, execution abnormity is processed, fault-tolerant recovery is carried out, task completion quality is verified, and user feedback is collected; intention recognition optimization is carried out, scheduling strategy parameters are adjusted, and intelligent agent capability evaluation is updated; according to the method, the multi-dimensional intention of the user can be accurately understood, and multi-agent efficient collaboration and resource optimization configuration are realized.

The invention discloses an automatic page generation method of a software construction platform based on a large language model, which comprises the following steps of: extracting a scene, a page and constraint description from a natural language demand, and generating JSON (JavaScript Object Notation) content containing a data model, a query condition, a table column and static data through the large language model; according to component type constraints and verification rules, the JSON is mapped to components and combinations of buttons, labels, texts, pictures, pull-down selection, multi-choice, single choice, tables, dates and the like of the code-free construction platform; and automatically filling a component set based on the upper and lower partition templates, and injecting static data and verification logic. Through industry knowledge adaptation, component semantic binding and dynamic constraint, it is ensured that the page conforms to field specifications and interaction logic, the learning cost is reduced, manual intervention is reduced, and the method is suitable for the fields of smart cities, natural resources, urban and rural residence construction, emergency management, enterprise digital transformation and the like.

The invention relates to the field of smart city management, and discloses a multi-source data fusion and treatment method for a CIM platform, and the method comprises the steps: sorting the current situation of city spatial data, and carrying out the unified access and classification of the data; carrying out unified conversion on the data, and carrying out merging and layer sequence arrangement; carrying out unified space coding on the geographic space object, and constructing a coding rule; the granularity is divided into construction granularity and expression granularity, data are fused through spatial association, and unified expression of multi-scale data is achieved; extracting spatial semantic information, establishing a mapping relation between a unified address and a CIM model, and realizing semantic expression of a place name and the address; constructing a pyramid model, and realizing fusion of the building information model and the CIM; and performing graph falling processing on the government affair data to form a thematic data base plate associated with the CIM model. According to the method, efficient access, unified processing and deep fusion of the multi-source data are realized, and the integration and availability of the data in the CIM platform are improved.

The invention discloses a smart city cloud platform data authorization sharing method and system based on a block chain, and relates to the field of data sharing, and the method comprises the steps: responding to a received query instruction of an access user, and determining the historical query information of the access user through a smart city cloud platform; performing identity verification on the access user based on a preset identity registration chain, and if the access user passes the identity verification, evaluating a trust value of the access user according to the historical query information; performing trust degree verification on the trust value; if the access user passes the trust degree verification, constructing a puncturable key structure in combination with the trust value of the access user, a preset ABAC model and a preset smart city alliance chain; and performing dynamic authority management on the access user by using the puncturable key structure, performing identity authorization on the access user based on the puncturable key structure, and sharing data queried by the access user. The management efficiency of the smart city can be effectively improved.

The invention provides a data processing method and device based on a smart city, and relates to the technical field of data processing.The method comprises the steps that a city-level spatial data base is constructed through oblique photography of an unmanned aerial vehicle, and a unified and real spatial foundation is formed by generating a live-action three-dimensional model, a digital orthoimage and a digital elevation model; on this basis, a building base and a building white model are extracted, spatial logic verification is carried out on multi-source business basic data, a standard address system stably associated with a building three-dimensional entity is further constructed, precise spatial anchoring of governance objects such as population, houses and units is achieved, and the method is suitable for mass production. And finally, the associated data is uniformly converged to a city information model platform, and reliable and updatable spatial data support is provided for smart city application. According to the invention, the timeliness of smart city data processing in a dynamic earth surface deformation scene can be improved.

The invention relates to the technical field of smart city public safety, in particular to an urban gas pipeline leakage risk intelligent early warning and positioning method and device.Firstly, a digital twinborn construction and dynamic coupling module constructs and drives a virtual image of a gas pipe network, then, a multi-modal data acquisition and fusion module comprehensively senses the state of the pipe network, and finally, the leakage risk of the gas pipeline is monitored. The intelligent early warning and positioning decision module realizes a core intelligent algorithm; a cloud-edge-end collaborative architecture is adopted, and a terminal sensor is responsible for data acquisition; the edge computing node is deployed in a regional pressure regulating station and is used for carrying out primary data processing and local real-time alarming; the cloud center deploys a digital twin platform and a core AI algorithm model, and performs big data analysis, simulation deduction and global decision. Compared with the prior art, the method can realize early and accurate identification and prediction of gas leakage and potential risks (such as abnormal stress) of the pipeline.

The invention relates to a geographic information technology, and discloses a smart city planning management method and system based on digital twinning, and the method comprises the steps: obtaining a multi-dimensional city data set of a target city, constructing a park demand intensity atlas according to the multi-dimensional city data set, recognizing a preset number of candidate regions through the park demand intensity atlas, and carrying out the recognition of the preset number of candidate regions; the method comprises the steps of obtaining a multi-dimensional city data set of a target city, obtaining a candidate region set, constructing a digital twinborn body of the target city according to the multi-dimensional city data set, obtaining a city digital twinborn model, carrying out traffic accessibility analysis on each candidate region in the candidate region set by using the city digital twinborn model, and obtaining a traffic accessibility score set, and selecting an optimal candidate area in the candidate area set according to the accessibility score set, and performing urban park construction planning according to the optimal candidate area. According to the invention, the scientificity of park site selection in urban planning can be improved.

The invention discloses a hierarchical city operation agent memory management method and system, and relates to the technical field of artificial intelligence and smart cities. The method comprises the steps of collecting multi-modal task data of smart city operation; estimating the occurrence intensity of the multi-modal task data in the time dimension to obtain a task intensity factor; calculating the dynamic weight of the memory entry in combination with the task intensity factor, the time attenuation factor and the industry key factor; realizing hierarchical evolution of short-term memory, medium-term memory and long-term memory according to the dynamic weight of the memory entry; establishing a unified embedding and indexing mechanism for the multi-modal task data, and storing the multi-modal task data in the same memory knowledge graph; and performing scoring by integrating the semantic similarity, the dynamic weight and the knowledge graph centrality, and performing memory retrieval and sorting according to a scoring result. According to the invention, the hit rate, timeliness and accuracy of agent emergency disposal and operation and maintenance decision can be improved.

The invention relates to the field of data processing, in particular to an information retrieval method for a smart city system, which comprises the following steps of: obtaining a historical data block of a business system and user interaction session data, and performing word segmentation to obtain an original word and a to-be-processed word set; calculating topic probabilities and topic correlation degrees of original words and historical data blocks through a topic model, screening candidate words and calculating importance degrees of the candidate words; expansion words and historical perception words are generated and spliced into a dynamic sequence, the semantic similarity of the sequence and historical data blocks is calculated, a preset number of data blocks are sequenced and displayed, and retrieval is completed. The topic probability of the original word and the historical data block and the corresponding topic correlation degree are calculated through the topic model, the candidate word inherits the topic attribute of the original word, the topic probability distribution consistency of the candidate word and the original word is quantified in combination with the JS divergence to screen the extension word, the topic deviation risk of semantic extension is avoided from the source, and the semantic extension efficiency is improved. And the retrieval matching precision is improved.

The invention discloses a smart city event perception and emergency scheduling method based on artificial intelligence. The method comprises the following steps: S1, constructing a standardized structured sample; s2, forming a city sub-event graph; s3, constructing a Bayesian event inference network, and synchronously recording intermediate layer feature response; s4, outputting a dynamic thermodynamic diagram as an event perception model; s5, constructing a multi-target scheduling graph, and generating an emergency scheduling task; s6, taking training of a lightweight student model as a target, constructing a fusion type knowledge distillation mechanism for edge deployment, and fusing teacher model output, intermediate layer feature response and Bayesian causal structure consistency as a distillation target; and S7, adjusting an event state association structure in the Bayesian event inference network and a response weight distribution mechanism of the lightweight student model. The method has the advantages of high reasoning precision, low response delay and edge deployment.

The invention discloses a smart city monitoring and simulation deduction method based on a digital twinborn model, and belongs to the field of electric digital data processing.The smart city monitoring and simulation deduction method based on the digital twinborn model comprises the following steps that dynamic data are continuously accessed, static data are obtained at the same time, a digital twinborn body with a timestamp is constructed, and the digital twinborn body is constructed; forming a virtual mirror image of the physical state of the city; on the basis of real-time indexes in a digital twinborn body, hydrological model parameters are corrected in real time, the short-term rainfall prediction precision is improved by fusing an LSTM model, and a twinborn driving model matched with the current reality is generated; compared with the prior art, the method has the advantages that dynamic data and static data of a city are collected in real time, a digital twinborn model for analyzing city drainage is constructed, the ponding risk level can be rapidly evaluated, differentiated emergency plans are automatically generated according to different risk levels, and the method has the advantages of being high in prediction precision and high in response speed.

The invention relates to the technical field of smart city information management, in particular to a smart city information management method and system based on GIS and AI fusion, and the method comprises the steps: carrying out the data mining and statistical analysis of the basic information of each economic entity in a city, and achieving the overview of economic development situations; collecting geographic position data of an economic body and matching coordinates, and constructing a three-dimensional digital city model associated with a GIS system; a hierarchical comprehensive evaluation algorithm is adopted to calculate the economic innovation value, the contribution degree of the economic innovation value is analyzed, and a long-short memory network is utilized to carry out space-time dynamic evolution analysis and trend prediction; and intelligent semantic understanding and personalized question and answer feedback are realized by analyzing a multi-modal query request of a user. The problems that an existing system is difficult in data fusion, static state analysis lags behind, and decision support is insufficient are solved, unified perception, intelligent analysis and scientific decision support of the urban operation state are achieved, and the urban fine management and service level is remarkably improved.

The invention discloses a city platform and method based on a national network identity authentication public service, and relates to the field of smart cities, and the method comprises the steps: firstly completing user identity authentication through the national network identity authentication public service, so as to establish a trusted access basis; and constructing a data request contract, and storing an evidence after a user confirms authorization, thereby forming a transparent and traceable authorization mechanism. And then generating a data token for limiting access based on a user authorization range, obtaining required cross-source data based on a unified data aggregation service, realizing on-demand aggregation and safe circulation of the data, automatically auditing the aggregated data through business logic to obtain an auditing result, and finally returning the auditing result to the user. In this way, the business process can be simplified, the problems of repeated authorization and data islands are solved, meanwhile, the user data control right is guaranteed, and the intelligence and efficiency of urban platform business handling are improved.

The invention discloses a smart city similar complaint event recognition method based on a graph database and semantic recognition, and relates to the technical field of smart city management, and the method comprises the steps: carrying out the vectorization calculation of a complaint event text through employing a sentence-transformers / paraphrase-multilingual-Mini LM-L12-v2 model, and carrying out the model fine tuning for the field of city governance; constructing an event-complaint-address-keyword association network model based on a graph database, defining points and edges, and realizing complaint event multi-dimensional association modeling through attribute design; preprocessing the stock data, establishing an association relationship among events, complaints, geographic positions and keywords, and importing the association relationship into a graph database; and performing preprocessing operation on the newly added complaint event, and calculating similarity based on keywords and complaint person information in combination with graph database retrieval so as to realize intelligent identification of multi-person simultaneous complaint and one-person multi-complaint. According to the invention, intelligent clustering and repeated reporting identification of city complaint events can be realized.

The invention discloses an audio and video emergency commanding and dispatching system for smart cities and villages, and relates to the technical field of emergency commanding, and the system comprises an audio and video collection terminal which is disposed at an emergency site and is used for synchronously collecting and transmitting video data and audio data of the same scene; the audio detection module is used for carrying out real-time analysis on the audio data, identifying abnormal audio events of a preset category, and generating a first analysis result containing event types, sound source positions and detection probabilities; according to the invention, the problem of how to fuse more accurately when both audios and videos have results is solved, and the problem of how to complement without omission when only one result exists is solved, so that the alarm can be accurate and complete regardless of a complex environment of a smart city or a sheltered scene of a country, and the commanding and dispatching efficiency is improved.

The invention relates to the technical field of smart city operation and maintenance, in particular to a smart city-oriented municipal facility state operation and maintenance analysis method. The method comprises the following steps: collecting multi-source monitoring data of municipal facilities; performing linkage facility state load feature analysis under each collaborative operation based on the municipal facility multi-source monitoring data, and generating linkage facility state load feature data; performing linkage facility state load characteristic trend prediction processing on the linkage facility state load characteristic data to generate linkage facility state load characteristic trend data; establishing a load energy efficiency multi-agent decision model according to the linkage facility state load characteristic data and the linkage facility energy efficiency data; and transmitting the state load characteristic trend data of the linkage facility to a load energy efficiency multi-agent decision-making model to carry out linkage facility intelligent control parameter analysis of global energy efficiency optimization, and generating linkage facility intelligent control parameters. According to the invention, state linkage intelligent operation and maintenance control of smart city municipal facilities is realized.

The invention discloses an event automatic allocation method and system based on historical disposal information and a multi-target genetic algorithm, and relates to the technical field of information technology and smart city management. Comprising the steps that 1, event data samples which are processed are extracted from a historical event library, each data sample comprises event features, historical processing departments and multiple processing performance indicators, and a training data set is constructed according to the data samples; step 2, training an adaptation degree prediction model based on the data set, learning a mapping relation from the combination of the event characteristics and the disposal departments to each performance indicator through the adaptation degree prediction model, and predicting each performance result possibly generated by any combination of the event and the disposal departments; step 3, when a new event arrives, predicting performance results generated by multiple performance indicators of each candidate department by using the fitness prediction model, and establishing a multi-objective optimization model; 4, solving the multi-objective optimization model by adopting a multi-objective genetic algorithm to obtain a group of Pareto optimal allocation schemes; and 5, selecting a final allocation scheme from the Pareto optimal solution set according to a preset strategy, and executing the final allocation scheme.

The invention discloses a smart city planning method and system based on digital twinning, relates to the technical field of city planning, and solves the problems that the scheme is not feasible due to dependence on manual interpretation of regulation texts, lack of automatic generation and matching of index constraint lists and possible neglect of key constraint conditions in planning suggestions, and meanwhile, the scheme is high in subjectivity and low in cost. And a unified quantitative model is lacked. Through the NLP technology, planning suggestions and regulation terms are compared in real time, conflict indexes are automatically marked, planning conditions and preliminary index calculation results are combined, the generated project planning suggestions strictly follow a policy framework, and manual interpretation errors or violation risks are avoided. A collaborative quantitative evaluation model of the single building and the regional landscape is established, and the landscape effect of the planning suggestion is evaluated from the dimensions of spatial layout, visual vestibule, skyline, color coordination and the like. The fusion degree of the project and the surrounding environment is visually reflected through quantitative scoring, and the deviation of subjective evaluation is avoided.

The present invention relates to the field of smart city environmental perception technology, and in particular to a flood intelligent deduction method and system based on global fusion. The method includes the following steps: deploying ground-nailed intelligent node units in a preset area, and collecting regional waterlogging data through the ground-nailed intelligent node units; constructing a geographic adjacency graph for the regional waterlogging data to obtain proximity graph data; performing local cross-domain graph attention calculation on the proximity graph data to obtain proximity perception graph data; performing cross-domain meta-correlation perception on the proximity perception graph data to obtain cross-domain meta-correlation data; performing waterlogging trend prediction on the cross-domain meta-correlation data to obtain waterlogging trend data; performing global flood simulation based on the waterlogging trend data to obtain global flood data. The present invention combines edge computing units to perform global flood simulation, generates spatially continuous and semantically clear risk layers, and provides efficient and explainable decision support for urban-level flood control scheduling.

The invention provides a modularized large screen automatic layout optimization method and system based on a constraint genetic algorithm. The method comprises the following steps: constructing decision variables and constraint conditions of modularized large screen layout optimization; encoding components in the large modularized screen to obtain different layout schemes corresponding to different chromosomes, and forming an initial layout group; performing optimization operation on each chromosome in the initial layout group by adopting a genetic operator to obtain a secondary layout group; and taking the secondary generation layout group as a new initial layout group, performing optimization operation again until a preset requirement is met, and outputting a final layout scheme. The system is used for implementing the method. The method is suitable for a visual platform in the fields of smart cities, industrial internet of things and the like, and solves the problem of automatic layout of large-scale components on the premise of meeting complex business rules and standard index requirements.

The invention discloses an urban inland inundation risk intelligent monitoring and early warning device based on short and temporary rainfall forecast, and relates to the technical field of urban disaster prevention and reduction and smart cities. The device comprises a generative approach rainfall forecasting module, an urban hydrological underlying surface module, an intelligent waterlogging risk deduction module, a high-performance calculation and data base and an intelligent emergency decision support module, the generative approach rainfall forecasting module outputs high-temporal-spatial-resolution rainfall data, and the urban hydrological underlying surface module provides static and dynamic hydrological data. Inputting the two into an intelligent waterlogging risk deduction module to calculate a dynamic risk level; the high-performance computing and data base provides computing power and data support for all the modules, the intelligent emergency decision support module generates a dynamic risk avoiding path and an emergency plan based on a risk result, and the device improves waterlogging early warning accuracy and emergency decision effectiveness and assists active defense of urban waterlogging.