116 results about "Natural disaster" patented technology

The invention relates to the technical field of natural disaster risk assessment, in particular to a multi-disaster disaster-inducing factor internal correlation analysis method, which comprises four steps of data preprocessing, Bayesian network correlation model construction, space-time dynamic evolution analysis and risk early warning threshold model construction. And deep coupling analysis of disaster-inducing factors of multiple disasters such as mountain torrent-debris flow and the like is realized. The method comprises the following steps: firstly, collecting 17 disaster-inducing factor data such as terrain and rainfall, performing dimensionality reduction through kernel principal component analysis, and calculating a dynamic weight by adopting an entropy evaluation method; then constructing a Bayesian network model to quantify conditional probability association; introducing a space-time attention mechanism to optimize a multi-scale coupling weight; and finally, establishing a coupling risk early warning threshold value and outputting a relevance intensity matrix. According to the method, the problem that a traditional single-disaster analysis method cannot capture the space-time linkage effect of disaster-inducing factors is solved, the risk early warning accuracy of multiple disasters is improved, and scientific decision support is provided for regional disaster prevention and reduction.

The invention belongs to the field of natural disaster monitoring and early warning information processing, and discloses a landslide monitoring system and method based on multi-source data fusion. A data preprocessing module; a data processing and analyzing module; a dynamic early warning module and a remote visualization module; the method comprises the following steps: S1, installing equipment; s2, collecting data; s3, data preprocessing; s4, data fusion analysis; s5, risk judgment and early warning; s6, displaying a result; by adopting the technical scheme, the environmental factors can be monitored in real time, the environmental factors are fused into the basis of early warning judgment, the influence of the induction factors on the stability of the mountain can be sensed in advance, the comprehensiveness of landslide judgment is improved, and the accuracy and sensitivity of mountain early warning are improved; meanwhile, according to the technical scheme, the threshold value is optimized, so that the system judges whether the threshold value is a fixed threshold value or not, the threshold value can be dynamically adjusted according to the monitored environmental factors, and the early warning of the system on the landslide is more accurate.

The invention discloses a temporary emergency shelter site selection method and system suitable for a huge disaster scene, and relates to the technical field of natural disaster emergency management. According to the method, disaster data and remote sensing image data of a disaster area are processed, disaster grids and non-disaster grids in the disaster area are identified, the site selection range is narrowed, and the site selection precision and accuracy are further improved; risk evaluation, openness and traffic evaluation are carried out on the non-disaster grids, based on the evaluation result, the grey wolf algorithm is utilized to carry out site selection on the non-disaster grids, a temporary emergency shelter site selection scheme is obtained, through data driving, manual analysis dependence is reduced, the site selection automation degree is improved, the site investigation requirement is reduced, and efficiency is improved. And through integration and rapid analysis of multi-source data, dynamic response to change demands is realized, dynamics is enhanced, and a site selection strategy is updated through real-time data, so that emergency service coverage is ensured to be matched with actual demands.

We provide the system. [Solution] A method that uses generative models to predict future natural disasters by analyzing environmental data collected from diverse sources, A means for providing an appropriate evacuation route to a user terminal based on the predictions of the generation model, A means of sharing community information among users in real time and promoting its use in disaster prevention, A method for using unmanned aerial vehicles to acquire information on the situation in disaster-stricken areas and then re-proposing the optimal evacuation route based on that information, A system that includes this.

The invention relates to the technical field of electric power, and discloses an electric power natural disaster emergency resource allocation method and system based on multi-data fusion, and the key points of the technical scheme are as follows: multi-source data acquisition and fusion, resource demand prediction, dynamic allocation scheme generation, and real-time monitoring and adjustment. By constructing a multi-source data fusion system, establishing a high-precision demand prediction model and dynamically generating an optimal allocation scheme in combination with traffic accessibility, accurate and efficient overall planning of emergency resources is realized, the resource utilization rate is improved, and the power recovery time after disasters is shortened.

The invention provides a flood disaster range monitoring method and system based on satellite remote sensing images, and belongs to the technical field of natural disaster monitoring and artificial intelligence crossing. The method comprises the steps that S1, a large number of historical SAR satellite remote sensing images are acquired to construct a data set; s2, training the flood segmentation model through the data set, and optimizing model parameters through a joint loss function in the training process; s3, deploying the trained flood segmentation model; s4, acquiring a target SAR satellite remote sensing image, inputting the target SAR satellite remote sensing image into the flood segmentation model, and reasoning to obtain a water body distribution diagram; s5, performing differential operation on the adjacent water body distribution diagrams to obtain a newly added flood disaster range; and S6, generating a time sequence flood inundation range map based on each flood disaster range, calculating flood characteristic parameters, and carrying out dynamic monitoring and early warning based on the time sequence flood inundation range map and the flood characteristic parameters. The method has the advantages that the accuracy and timeliness of flood disaster range monitoring are greatly improved.

Systems and methods for natural disaster damage analysis. Aerial images are converted (710) into a set of property images. The property images are then clustered (720) using vector embedding. Clustering the property images includes classifying the property images into separate categories, determining a symmetric similarity between the property images in each category, and clustering the property images based on the similarity. A first artificial intelligence agent extracts (730) damage information from a set of representative members of the clustered property images, where the damage information includes damage level information and damage reasoning information. The damage information is then stored (740) in a datastore with at least two databases, where at least one of the databases stores damage reasoning information and at least one other one of the databases stores damage level information.

A routing optimization method for truck-drone integrated rescue vehicles in forest firefighting includes the following steps: collecting the data of the disaster sites caused by forest fires, calculating transportation time on road and flight time according to the data of the disaster sites, and getting the transportation time data of post-disaster relief; based on the disaster site data, transportation time data, and an amount of relief supplies that can be allocated to disaster relief sites, constructing a mathematical model of the truck-drone based vehicle routing problem; solving the mathematical model of the truck-drone based vehicle routing problem by the optimization algorithm, and specifying a post-disaster rescue route of the truck-drone integrated rescue vehicle according to the solution results. The model based on the truck-drone based vehicle routing problem method can reduce the impact of sudden natural disasters, and give full play to the advantages of truck-drone integrated rescue vehicles.

This pipeline damage prediction system uses a computer to predict pipeline damage due to a natural disaster, the pipeline damage predication system comprising: a basic data storage unit that stores pipeline attribute data indicating an attribute of a pipeline, stores ground characteristic data which indicates a characteristic of the ground in which the pipeline is buried and which includes at least liquefaction data, ground boundary data, or terrain modification data in units of polygons in a map information system GIS, and stores damage data indicating the degree of damage due to a natural disaster occurring in the past; and a damage prediction calculation unit that generates damage prediction information in which damage occurring in the pipeline is predicted on the basis of the pipeline attribute data, the ground characteristic data, and the damage data stored in the basic data storage unit.

The invention relates to the technical field of roadbed slope protection, discloses a roadbed slope protection composition based on solid waste-geopolymer and a construction method of the roadbed slope protection composition, and aims to solve the problems of high carbon emission, low solid waste utilization rate, strong ecological destructiveness and weak disaster resistance of a traditional roadbed slope protection material. According to the invention, fly ash, desulfurized gypsum, mineral powder and pretreated red mud are taken as core raw materials, and are matched with a geopolymer activator and a heavy metal stabilizer to form a cement-free flow state system with a high solid waste mixing ratio; during construction, a casing pipe is not needed, through the drilling-layered pouring technology, the solidification body is naturally attached to soil through the fluidity, a multi-deformation solidification structure without rigid cutting is formed, the anti-scouring and anti-collapse capacity of a roadbed slope can be enhanced through the structure, damage of natural disasters such as flood to a roadbed can be effectively resisted, and the construction period is shortened. Meanwhile, the ecological compatibility of the mechanical property and the plant root system penetration rate is considered.

The utility model provides a monitoring and early warning device for a debris flow gully in a canyon fall section, and relates to the technical field of natural disaster early warning. The device comprises a supporting column, a connecting frame, a sliding rail, a debris flow monitoring module and a rainfall monitoring module. Wherein the supporting columns are embedded and fixed on the two sides of a debris flow gully; the connecting frame is fixedly connected to the upper end of the supporting column. The sliding rail is fixed to the lower end of the middle of the connecting frame and extends in the same direction as the debris flow gully. The debris flow monitoring module is slidably connected to the sliding rail and can follow the debris flow state in the debris flow gully when the debris flow disaster occurs. And the rainfall monitoring module is fixed at the upstream position of the debris flow gully. According to the scheme, the debris flow monitoring module can move along the channel for monitoring through the sliding track, dynamic data collection is achieved in combination with the rainfall monitoring module, the problem that traditional fixed-point monitoring cannot adapt to complex canyon terrains is solved, and the accuracy and timeliness of early warning are improved.

The invention discloses a natural disaster emergency response method and system based on power failure monitoring, and the method comprises the steps: obtaining a set of power failure data, which comprises a power failure influence unit, a power failure public and special variable, a power failure cell and an initial power failure influence user number; and a data processing and analysis algorithm is introduced at the rear end to carry out collaborative analysis on a set of the power failure data, so that the total number of the power failure users is accurately predicted, and corresponding natural disaster emergency response is carried out. Therefore, the intelligence of emergency management and response of natural disasters can be realized, so that the disaster response efficiency is improved, and the loss is reduced.

A system is provided.SOLUTION: A system comprising: means for collecting natural disasters in real time; means for training a generative AI model using the collected natural disasters; means for predicting a probability of occurrence of disasters using the generative AI model; means for reflecting the predicted probability of occurrence of disasters in a map service; and means for providing shelter information and information for preparing for disasters.SELECTED DRAWING: Figure 1

The embodiment of the invention provides a natural disaster risk evaluation method, device and equipment and a computer readable storage medium. The method comprises the steps of determining natural disasters possibly involved in a to-be-evaluated region based on geographical environment information of the to-be-evaluated region; determining each natural disaster risk index based on the survey evaluation data of each natural disaster; based on the natural disaster risk indexes, a total risk index and an overlapping risk index are determined, the total risk index is related to the risk of independent occurrence of each natural disaster, and the overlapping risk index is related to the risk of simultaneous occurrence of all natural disasters; and determining a comprehensive risk index of the to-be-evaluated region based on the total risk index and the overlapping risk index. According to the method, the risk superposition influence of various natural disasters is fully considered, so that the obtained risk assessment result is more suitable for areas influenced by various natural disasters, and scientific and comprehensive data support is provided for comprehensive risk assessment of local disasters, disaster control and emergency rescue work.

The application provides a kind of nuclear power plant dry storage spent fuel emergency evaluation method, system, equipment and medium, applied to dry nuclear horizontal modular storage system, the dry nuclear horizontal modular storage system includes concrete module and storage container, the method comprises: obtaining the information of natural disaster;According to the type and risk parameter of the natural disaster information of the natural disaster;In response to the risk parameter being higher than the response threshold, the radiation dose of the concrete module is obtained;According to the radiation dose, the effective multiplication coefficient of the storage container is obtained;In response to the effective multiplication coefficient being higher than the effective multiplication coefficient threshold, the storage container transfer operation is executed, can be integrated together by natural disaster risk assessment, radiation dose monitoring and effective multiplication coefficient control, form a complete emergency evaluation and response system, improve the overall efficiency of nuclear power plant in response to disaster.

Systems and methods for natural disaster damage analysis. Aerial images are converted into a set of property images. The property images are then clustered using vector embedding. Clustering the property images includes classifying the property images into separate categories, determining a symmetric similarity between the property images in each category, and clustering the property images based on the similarity. A first artificial intelligence agent extracts damage information from a set of representative members of the clustered property images, where the damage information includes damage level information and damage reasoning information. The damage information is then stored in a datastore with at least two databases, where at least one of the databases stores damage reasoning information and at least one other one of the databases stores damage level information.

The invention discloses a multi-modal disaster relief information analysis and task intelligent planning method and device, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the structural processing of multi-modal disaster information after a natural disaster, and generating multi-modal structural data; the preset large language model generates a current disaster relief task planning strategy based on a preset task prompt content generation algorithm and the multi-modal structured data; wherein the preset task prompt content generation algorithm comprises any one of a preset task prompt word template and a preset dynamic evolution prompt graph model composed of multiple reasoning nodes, and the multiple reasoning nodes at least comprise a disaster situation recognition node, a rescue priority judgment node, a resource constraint node and a path planning node; the reasoning nodes are connected through a preset dependency relationship, a preset reasoning sequence constraint and a preset conflict resolution rule to form a preset dynamic evolution prompt graph model. The scheme solves the problem that in the prior art, it is difficult to dynamically cope with constantly changing disaster relief sites.

To provide a circuit board unit that detects sudden natural disasters such as rockfalls, rockfalls, landslides, mudslides, and debris flows in real time, and a disaster detection device equipped with this circuit board unit. [Solution] The substrate unit 20 includes a circuit board 25 on which an electronic circuit is formed, a switch 25d that opens and closes the electronic circuit by the displacement of an external switch operating part, a case body 21 having a substrate housing part that encloses and houses the circuit board 25, and a cover body 22 that closes the substrate housing part of the case body 21. The disaster detection device includes the substrate unit, a main body device in which the substrate unit is housed and which is provided with a switch operating part that displaces in conjunction with the detection body when a predetermined amount of kinetic energy or more is applied to the detection body and it is displaced and / or deformed, and a detection body supported on the ground by the main body device.

The invention discloses a natural disaster prediction method, system, device and program, and relates to the technical field of disaster prediction, and the method comprises the steps: collecting a bio-electricity signal; establishing an entropy-flow field coupling model based on the bio-electricity signal; performing prediction through the entropy-flow field coupling model, and outputting a predicted shear stress field; and calculating gradient energy density based on the predicted shear stress field, and judging whether natural disaster early warning is issued or not. According to the processing scheme disclosed by the invention, the underground shear stress which cannot be directly measured can be converted into the observable biological response function by collecting the bio-electricity signal and establishing the entropy-flow field coupling model, so that high-precision prediction of natural disasters is realized.

The invention relates to a rapid emergency decision-making method and system for an electric power sudden natural disaster, and belongs to the technical field of electric power disaster emergency decision-making. The method comprises the following steps: deducing disaster intensity by superposing early warning information and a real-time state of a power grid, obtaining a predicted fault probability set, obtaining empirical data by matching historical cases, and generating a defensive plan; feature extraction is carried out on multi-source heterogeneous monitoring data collected in real time, a diagnosed fault equipment set is obtained based on evidence fusion, and then the real-time situation of a power grid is constructed in combination with a CIM model; and performing plan primary selection on the defensive plan and the real-time situation of the power grid through multi-dimensional quantitative comparison, performing processing decision based on a matching result, and outputting an emergency disposal scheme after simulation verification. Based on digital twinning and multi-source data fusion, equipment-level disaster damage prediction, minute-level situation awareness and second-level scheme generation are realized, and the power grid disaster prevention and rapid recovery capability is continuously improved through adaptive optimization.

The application relates to a tropical cyclone disaster loss assessment method and system, and relates to the technical field of natural disaster risk assessment. The method is executed by a computer device and comprises the following steps: acquiring historical cyclone paths, wind field parameters and social and economic statistical data; performing uniform spatial resolution and coordinate reference alignment processing on population and economic spatial distribution data; calculating a hazard intensity index P; determining a cyclone influence range, extracting population exposure PE and economic exposure G; selecting a population and economic vulnerability index set, constructing a population vulnerability index PV and an economic vulnerability index EV; adopting Poisson regression to construct a death assessment model with P, PE and PV as independent variables; and adopting gamma regression to construct an economic loss assessment model with P, G and EV as independent variables. The application realizes double-dimensional and comparable collaborative attribution analysis of historical tropical cyclone event economic loss and population death, and outputs the relative contribution degrees of hazard, exposure and vulnerability to the two types of losses.

The invention relates to the technical field of meteorological monitoring, in particular to a whistle natural disaster early warning alarm which comprises a shell, a control mainboard arranged in the shell and the following functional units electrically connected with the control mainboard: a power supply and power supply management unit which comprises a battery, a Type-C power supply interface and a charging indicator lamp; the wireless communication and satellite positioning unit comprises a 4G antenna, an SIM card slot, a Beidou satellite module and a Beidou antenna; the multi-mode early warning output unit comprises a loudspeaker, an alarm lamp interface used for being connected with an external alarm lamp, an equipment state lamp and a Mini HDMI interface used for outputting audio and video signals; the data storage unit comprises a TF card slot; and the user interaction unit comprises a power switch, a plurality of functional keys and a key board. The device can be fixed at a specified position, sends a real-time position, receives early warning information of a current position through a network, and carries out early warning reminding of sound, light and voice broadcast through a loudspeaker and a multicolor LED lamp strip which are arranged in the device.

The utility model discloses a tower pole inclination monitoring device based on natural disasters, which relates to the technical field of tower pole inclination monitoring and comprises a tower body, a connecting piece, an elastic piece, an induction piece and a monitoring terminal. Wherein the tower body is used for supporting a high-voltage cable, supporting legs are arranged at the bottom of the tower body and fixed to the ground, the connecting pieces are arranged on the supporting legs and used for being connected with the elastic pieces, the elastic pieces are connected between the connecting pieces and the induction pieces, and the induction pieces are used for inducing stress of the elastic pieces. At the moment, the sensing piece receives the elastic force of the elastic piece and electrically transmits information to the monitoring terminal, and the monitoring terminal analyzes the information and then calculates the inclination direction and angle of the tower body. According to the utility model, whether the tower pole is inclined can be continuously monitored through the mode, so that the inclination of the tower pole in a high mountain, a canyon and other areas which are difficult to be manually monitored in a natural environment can be sensed in the first time, and the safety of high-voltage power transmission is improved.

1. Name of the product in this design: Tracked Robot (Natural Disaster Prevention). 2. Application of this design: This design is intended for use as an intelligent robot for emergency rescue, inspection, and other purposes. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The utility model provides a kind of environmental monitoring and natural disaster monitoring and early warning device and system that unmanned aerial vehicle can be deployed, belong to disaster monitoring and early warning technical field. Including: bearing frame;Leveling structure is set on bearing frame, for adjusting the levelness of bearing frame;Monitoring structure is set on bearing frame, for obtaining natural disaster early warning monitoring data and environmental monitoring data;Data transmission and control management terminal are connected with leveling structure and monitoring structure, for sending natural disaster early warning monitoring data and environmental monitoring data to early warning center;Mounting structure is set on the top of bearing frame, for being connected with unmanned aerial vehicle to realize mounting transport.The utility model sets up mounting structure on bearing frame to realize mounting transport, can increase the scope of application, leveling structure is set simultaneously, the levelness of bearing frame is adjusted, the stability of overall structure can be guaranteed, installation process is simplified, the levelness of bearing frame is guaranteed, so that monitoring result is more accurate.

A sensor-network-based analysis and / or prediction method for protection from natural hazards includes receiving and collecting electronic sensor data from distributedly arranged sensor modules of an outdoor sensor network in an external analysis and / or prediction unit. The sensor data includes outdoor corrosion measurement data, impact sensor data and / or rope force sensor data. The sensor data includes tropospheric measurement data. One or more tropospheric measurement dataset is, in particular geographically, allocated to each outdoor corrosion measurement dataset. The analysis and / or method also includes storing the received sensor data of the outdoor sensor network in a memory unit of the external analysis and / or prediction unit; analyzing the received sensor data for a determination of a natural hazard risk in respective application areas of the sensor modules by the external analysis and / or prediction unit; and providing the natural hazard risk determined by the external analysis and / or prediction unit to an authorized user group.

This invention discloses a land natural disaster early warning and control system based on UAV mapping, belonging to the field of land resource early warning management technology. It includes a UAV swarm and a local control terminal for UAV swarm control and data analysis and processing. The local control terminal includes: a mapping planning module for planning the distribution and flight paths of UAVs within the mapping area; a data processing module for identifying, marking, and recording the locations of disaster hazard points in various terrains based on image data acquired by the UAVs and radar monitoring data; and an analysis and early warning module for conducting fixed-point inspections of the hazard-marked areas at different time intervals, calculating the migration speed and migration value of two sets of monitoring data, and conducting risk assessment and early warning based on the comparison of migration speed and migration value. This system efficiently and comprehensively acquires and processes data, avoiding losses caused by untimely and inadequate responses due to the inability to assess the safety of personnel and property in the risk warning area.

The invention provides a damage assessment method and device, equipment and a storage medium. The damage assessment method comprises the steps that global description information of a to-be-assessed area and attribute information of each target object in the to-be-assessed area are extracted from a remote sensing image of the to-be-assessed area, and the attribute information comprises the category, the position and the preliminary damage rating of the target object; the global description information at least comprises attribute features of various types of land parcels in the to-be-evaluated region; constructing first input content for guiding a target model based on the attribute information, the global description information and a preset knowledge base; and based on the first input content and the target model, generating a global damage assessment report for the to-be-assessed region. The damage assessment method provided by the invention is suitable for various application scenes such as natural disasters, emergencies and battlefield situations, and the scene adaptability and accuracy of the damage assessment method are improved.

The invention provides a natural disaster-oriented building damage brain-like intelligent detection method, and the method comprises the steps: carrying out the alignment processing of a semantic feature, a first disaster region feature generated by a classification sub-model based on the semantic feature, and a first disaster category feature, and obtaining a target semantic feature, a target disaster region feature, and a target disaster category feature; determining a segmentation result of the post-disaster image data based on the target semantic feature, the target disaster area feature and the target disaster category feature through a segmentation sub-model; and based on the segmentation result of the segmentation sub-model and the classification result of the classification sub-model, determining the overall identification result of the disaster abnormity and damage collaborative identification model. According to the embodiment of the invention, the target disaster area features and the target disaster category features are combined in the segmentation process of the segmentation sub-model, so that the segmentation precision of the segmentation sub-model can be improved, and dual tasks of disaster category qualification and building damage positioning are cooperatively completed through single image data.

The present application relates to a kind of quantitative-qualitative self-adaptive natural disaster prevention and control capability evaluation method and application based on data quality score, qualitative index system and quantitative index system are respectively constructed;After obtaining the to-be-evaluated data corresponding to the evaluation object, the comprehensive data quality score is calculated from four dimensions of data completeness, data timeliness, data accuracy and data consistency;According to the comparison result of the comprehensive data quality score and the first threshold and the second threshold, it is determined to adopt quantitative evaluation mode, qualitative evaluation mode or quantitative-qualitative fusion evaluation mode.The present application realizes the adaptive matching of natural disaster prevention and control capability evaluation method and data basic condition by data quality driven evaluation mode selection, improves the scientificity, applicability and reliability of evaluation result.