126 results about "Wild Fires" patented technology

The invention discloses a forest carbon flux statistical method and system under the influence of a wildfire, and the method comprises the steps: obtaining forest multi-dimensional data including fire point data, and constructing a multi-scale collaborative database; constructing a carbon source-carbon sink dynamic coupling model according to the multi-scale collaborative database; obtaining a forest multi-dimensional remote sensing index, and constructing a correlation matrix; correcting the carbon source-carbon sink dynamic coupling model according to the correlation matrix; and generating a forest spatialization decision map based on the multi-scale collaborative database and the carbon source-carbon sink dynamic coupling model. According to the technical scheme provided by the invention, by fusing forest multi-scale data, a nationwide unified grid system is constructed, and large-scale forest fire carbon flux statistics and accurate quantification are realized; a carbon source-carbon sink dynamic coupling model is constructed, a forest multi-dimensional remote sensing index is used for correction, and the monitoring precision of the fire influence is remarkably improved; and the emission factors are dynamically calibrated, so that the inter-region difference is reduced, and the universality of the method is enhanced.

A service inputs building characteristics for a building into a machine learning model configured to output a probability that a given building will be lost should a fire reach the building, and receives as output from the model a building loss factor for the building. The service determines determining an exposure measurement for the building by performing simulations, over a plurality of candidate environmental parameters, of whether a simulated fire would encroach on the building. The service determines a building damage potential measurement based on the building loss factor, the exposure measurement, and an intensity measurement, and generates for display a graphical user interface showing fire risk for the building based on the building damage potential measurement.

The invention discloses a forest fire rapid identification and accurate fire point positioning method based on air-ground cooperation. Comprising the following steps: a forest fire panoramic monitoring and positioning method based on a double-axis holder, a wildfire target intelligent identification algorithm based on multi-modal image fusion analysis, and a low-power-consumption air-ground cooperative communication network oriented to forest fire monitoring. The invention relates to an unmanned aerial vehicle-based forest wildfire target maneuvering inspection and positioning method and an air-ground fusion wildfire target accurate positioning method. According to the invention, 360-degree panoramic image acquisition is realized by using the double-shaft holder, and meanwhile, a fire source position self-adaptive adjustment mechanism is provided; multi-modal image fusion analysis is adopted in the image processing layer to resist interference, blind areas are compensated, and the fire source recognition accuracy is improved; a low-power-consumption air-ground cooperative communication network is constructed, so that the cost is reduced, and flight is continued; and the monitoring limitation is broken through by means of flexible inspection of the unmanned aerial vehicle, a closed-loop system of air-ground cooperation-information complementation-intelligent verification is formed, and the monitoring stability in a complex scene is remarkably enhanced.

The invention discloses a fire spread integrated prediction method and system coupled with smoke and weather feedback effects, and the method comprises the steps: firstly estimating forest fire emission parameters in real time based on satellite remote sensing data, and converting the forest fire emission parameters into spatial-temporal dynamic emission flux which can be recognized by a numerical weather chemistry prediction model WRF-Chem; and matching with a WRF-Chem meteorological chemical grid is realized through grid interpolation. Secondly, simulating a bidirectional coupling process of smoke aerosol and a meteorological field based on WRF-Chem, and generating a dynamic meteorological field containing smoke radiation feedback; and finally, inputting the dynamic meteorological field into a weather-wildfire coupling simulation and weather research forecasting mode WRF-Fire to realize feedback effect simulation of smoke on fire spreading. According to the invention, an aerosol-dominated positive feedback chain is disclosed for the first time: fire discharge provides scientific support for disaster prevention decision-making through the synergistic effect of thermodynamic heating and radiation forcing, so that the emergency response efficiency is improved.

The invention belongs to the field of biological agriculture, and particularly relates to bacillus amyloliquefaciens as well as a fungicide and application thereof. The invention discloses bacillus amyloliquefaciens B26 which is preserved in China General Microbiological Culture Collection Center on November 6, 2024, and the preservation number is CGMCC No.32519. The strain has a broad-spectrum antibacterial effect on fungal diseases and bacterial diseases, particularly has a remarkable antagonistic effect on tobacco wildfire germs, and can be used for preparing a bacillus amyloliquefaciens strain. The bacillus amyloliquefaciens B26 is used for preventing and treating the tobacco wildfire disease, it is found that the strain has an obvious preventing and treating effect on the tobacco wildfire disease, and a fungicide of the bacillus amyloliquefaciens B26 also has a good preventing and treating effect on the tobacco wildfire disease in a pot experiment. And a new scheme is provided for plant disease prevention and treatment, especially for green prevention and treatment of tobacco wildfire.

The invention belongs to the technical field of safety early warning, and discloses a 30-60-minute emergency evacuation scheme based on influence of weather change on fire potential, which constructs early warning trigger logic based on weather mutation, dynamically regulates and controls response level and realizes linkage update of minute-level evacuation strategy. According to the method, a high-sensitivity index library of wind speed jump, humidity abrupt drop, lightning stroke ignition and the like is constructed, and the micro-scale meteorological evolution trend and field situation data are combined, so that the emergency evacuation scheme can quickly enter a forced response state 30-60 minutes before rapid expansion of a wildfire, and the effectiveness and timeliness of an evacuation decision are remarkably improved.

A system, method, and device for predicting a risk of wildfire are provided. The system includes a satellite imaging device for collecting data covering a target area and a processing server including an indices module for processing the data to generate key vegetation indices, a map generation module configured to generate weather and static maps, an analysis module configured to analyze historical wildfire data to identify past fire locations in the target area, an integration module configured to integrate the received, generated, and analyzed data to obtain a comprehensive dataset for the target area, and a risk prediction module configured to analyze the comprehensive dataset using a risk prediction model trained to predict the risk of wildfire for the targeted area, the risk prediction model including a machine-learning-based pattern detection model for receiving the comprehensive dataset as an input and generate prediction data describing a predicted risk as an output.

A fabric barrier for containing wildfires can be rapidly deployed in a location within a path of a moving wildfire slow or stop the spread of the fire. The fabric can be rolled up and then deployed by unrolling the fabric and installing support posts at intervals along a length of the barrier. Stakes may be used to secure the installation to the ground. The barrier includes an upright portion that extends above the ground and a lateral portion that is positioned adjacent to the ground. A wheeled cart can be used to unroll and deploy the barrier along a path of deployment.

The invention discloses a wildfire monitoring method based on a multi-source time sequence remote sensing image, and relates to the technical field of remote sensing geoscience application, and the method comprises the steps: obtaining multi-source remote sensing data, constructing a time sequence waveband data set, and constructing a high-temperature thermal anomaly index through the atmospheric top reflectivity of a three-waveband spectrum; based on the high-temperature thermal anomaly index, extracting a first-level fire point pixel, a saturated pixel and a high-radiance pixel from the multi-source remote sensing data, and converting the saturated pixel and the high-radiance pixel into the first-level fire point pixel; extracting saturated pixels and high-radiance pixels from missed fire cluster cores in the multi-source remote sensing data; based on limiting conditions, building coverage area data and a high-frequency ground object mask, noise pixels in the first-level fire point pixels are removed, and second-level fire point pixels are obtained; transmitting to a local client and a cloud geographic space analysis platform, and creating a fire point list. Multi-source long-time sequence optical remote sensing data are combined, and the spatial and temporal distribution of the large-area wildfire is quickly and automatically identified.

The application provides a WUI division method and device based on house wild fire risk, equipment and storage medium, determines the weighted fuel grade of each fuel grid in the region to be divided; for each house in the region to be divided, the building wild fire risk index of the house is calculated and obtained; for each fuel grid, the vegetation danger index of the fuel grid is calculated and obtained; from all the houses in the region to be divided, the houses with building wild fire risk index greater than a preset first threshold value are screened out as risk houses; for each risk house, from all the fuel grids falling within the buffer area corresponding to the risk house, the fuel grids with vegetation danger index greater than a preset second threshold value are screened out as risk fuel grids corresponding to the risk house; for each risk house, the risk house and the risk fuel grid corresponding to the risk house are regionally merged to obtain a plurality of forest town junction domains in the region to be divided. The scheme of the application improves the accuracy of forest town junction domain division.

A system for generation of wildfire suppression asset allocation based on wildfire-related data, including a processor of a fire analysis server (FAS) node configured to host a machine learning (ML) module and connected to at least one fire surveillance device and to at least one command-and-control entity node over a wireless network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire sensory data from a plurality of sensors hosted on the at least one fire surveillance device; parse the sensory data to derive a plurality of key features; acquire available fire suppression assets'-related data from a local storage; query a local fires'-related database to retrieve local historical fires'-related data related to previous fires' suppression engagements based on the plurality of the key features and available fire suppression assets'-related data; generate at least one feature vector based on the plurality of key features, the available fire suppression assets'-related data and the local historical fires'-related data; and provide the at least one feature vector to the ML module configured to generate a predictive model for producing asset allocation parameters for generation of the assets' deployment plan for the at least one least one command-and-control entity node.

The application discloses a kind of wild fire smoke cluster and its boundary vector automatic identification method, system, storage medium and electronic equipment, belong to satellite remote sensing and disaster monitoring technical field.Method includes: obtaining satellite active fire point, fire event and UVAI data;Fire source area is positioned based on fire event geographic location and initial plume pixel is marked;The spatially continuous smoke cluster connected domain is identified by iterative region growing algorithm;According to the specific distribution form of connected domain pixel in satellite pixel matrix, the accurate closed boundary vector is automatically generated using matching geometric algorithm;Finally, using multiple criteria, the spatial isolated independent smoke cluster is screened out.The application avoids the defects that traditional image method is easily disturbed by environment from physical principle, realizes fully automated processing without training data, and can output vector boundary that can be directly used for diffusion and emission evaluation, significantly improves the accuracy, automation degree and application value of wild fire smoke cluster monitoring.

A fire retardant formulation includes a first flame retardant agent consisting of corn syrup, com molasses, sorghum molasses, pomegranate molasses, carob molasses, date molasses, a waste concentrate of alcohol distilling industry, sacharinic acid, a lignosulfonate, steepwater solubles formed using a wet milling process for corn, whey, a wine-making residue, brewers' condensed solubles, desugared corn symp, desugared com molasses, desugared (brown) rice syrup, desugared maple symp, desugared sorghum molasses, desugared agave symp, desugared pomegranate molasses, desugared carob molasses, desugared date molasses and admixtures thereof exhibiting flame retardant properties, and a second agent selected from a group consisting of a flame retardant colorant, an additional flame retardant agent and mixtures thereof. A method of suppressing a wild fire or forest fire includes the step of applying an effective amount of the fire retardant formulation to (a) the wild fire, (b) the forest fire, (c) an area to be protected from the wild fire or the forest fire or (d) combinations thereof.

There is provided a networked based coordinated wildfire management system for the protection of a community of structures from a wildfire. The systems have hydration plans that provide for the minimal use of water to protect the structures for the wildfire. The hydration plans can be automated adaptive hydration plans that the control system develops to address a specific wildfire threat, and these plans are developed in real time. The systems can have sprinkler towers that are place along roadway and near structures to implement the hydration plan and protect evaluation routes. The systems provide an integrated approach to protection an entire community.

This invention discloses a method for predicting unsteady runoff response considering forest disturbance. The method includes data decomposition of the unsteady runoff sequence to obtain a basic runoff sequence and a disturbed runoff sequence; time-varying coefficient regression to obtain a basic runoff mapping function; correlation analysis and sensitivity analysis; using the correlation analysis results to correct the sensitivity analysis results to obtain optimized disturbance sensitivity; constructing a disturbed runoff prediction model; inputting the watershed characteristics and disturbance data of the watershed to be predicted into the basic runoff mapping function and the disturbed runoff prediction model respectively to obtain predicted basic runoff and predicted disturbed runoff; and superimposing these to obtain the predicted unsteady runoff. This method can quantify the disturbed runoff resulting from the interaction of wildfire disturbance, logging disturbance, vegetation adjustment disturbance, and conventional climate disturbance, and incorporates a competition-cooperative improved double cumulative curve (C-MDMC) to quantify the interaction effects between disturbances, outputting disturbed runoff prediction results. This provides a refined decision-making basis for watershed multi-scenario adaptive water resource management.

An apparatus and method are provided for reducing methane emissions from ruminant animals by combusting methane gas extracted from the rumen. The system comprises a conduit configured to transport methane from the animal's rumen to a combustion module mounted externally or implanted partially or fully in a subdorsal position. The combustion module includes a pressure-activated valve, air intake, ignition system, and combustion chamber enclosed by a heat-absorbing roof structure. A control unit monitors internal gas pressure and triggers a spark ignition circuit when combustion conditions are satisfied. An upward-facing camera inhibits ignition if flammable obstructions are detected above the module. A water-filled thermal buffer integrated into the chamber roof moderates exhaust temperature, reducing wildfire risk. Power is supplied by a solar panel and rechargeable battery. The system intermittently converts methane into carbon dioxide and water vapor, significantly mitigating the greenhouse gas impact of enteric fermentation in ruminant livestock.

A multi-modal combustion interruption system comprises a detection subsystem configured to identify combustion events, an electromagnetic emission subsystem having pulsed energy source and directional emission structure, a control processor implementing adaptive modulation based on measured combustion response, and a safety enforcement subsystem configured to control emission activation based on presence detection. The system may be configured in various modes from baseline electromagnetic emission through enhanced configurations incorporating optional ionization enhancement, particle generation, and acoustic energy subsystems. Adaptive modulation enables parameter selection based on measured combustion response rather than predetermined values. The modular architecture enables configuration selection based on deployment type and application requirements. Fixed installations may utilize grid power for industrial facility protection. Mobile platforms may employ onboard power for emergency response or wildfire intervention. Configuration selection may consider environmental compatibility including omission of particle generation for water-sensitive equipment environments or incorporation of multiple enhancement subsystems for demanding applications.

Machine-learning-based methods and systems for vegetation treatment project design. The approach autonomously creates, evaluates, and optimizes wildfire risk mitigation activities to intelligently reduce wildfire risk to communities in a resource-constrained environment. The methods and / or systems are accompanied by a cloud-enabled user interface that provides decision support to vegetation management specialists charged with implementing wildfire risk reduction measures.

The present application relates to the technical field of prediction, in particular to a seasonal wild fire susceptibility evaluation method, first, historical wild fire samples are collected and screened, then a CF wild fire susceptibility model of the whole season is constructed by using a CF algorithm, based on which a negative sample selection area is demarcated and positive and negative samples are integrated; secondly, the positive and negative samples in different periods are divided into training set and test set, an annual and different seasonal wild fire susceptibility prediction model is constructed based on an XGBoost model, and the rationality and prediction performance thereof are compared and analyzed by using multiple evaluation indexes; finally, the SHAP global interpretability method is used to analyze the difference in the influence degree of factors in the susceptibility model of different seasons, the probability of wild fire occurrence in different seasons and possible reasons are understood, so that corresponding preventive measures are taken in advance, so as to reduce the occurrence rate and harm of wild fire, and overcome the problems that the existing machine learning method has poor model interpretability and it is difficult to determine the dominant factors when predicting the wild fire susceptibility of each season.

An intelligent sewage system designed for use in municipalities around the Wildland Urban Interface incorporates a decentralized network of wastewater treatment units to process wastewater from a plurality of parcels. The decentralized wastewater treatment units spread a Biological Oxygen Demand (BOD) reduction of the wastewater throughout the system and effluent is delivered efficiently through a pressure sewage system. Non-potable and potable water supplies are generated and delivered to individually separable water distribution zones throughout the municipality. The system also provides an auxiliary high-pressure, high-flow non-potable water supply to compensate during depressurization events and bolster the water distribution zones in the event of a wildfire emergency event. The intelligent sewage system also incorporates a comprehensive wildfire defense network and a supervisory control and data acquisition system which work in concert to harden the municipality against wildfire risks and combat active wildfires.

A system, method, and device for predicting a risk of wildfire are provided. The system includes a satellite imaging device for collecting data covering a target area and a processing server including an indices module for processing the data to generate key vegetation indices, a map generation module configured to generate weather and static maps, an analysis module configured to analyze historical wildfire data to identify past fire locations in the target area, an integration module configured to integrate the received, generated, and analyzed data to obtain a comprehensive dataset for the target area, and a risk prediction module configured to analyze the comprehensive dataset using a risk prediction model trained to predict the risk of wildfire for the targeted area, the risk prediction model including a machine-learning-based pattern detection model for receiving the comprehensive dataset as an input and generate prediction data describing a predicted risk as an output.

Environmentally-clean wildfire inhibitor liquid biochemical solutions produced from an aqueous mixture of alkali metal salt derived from a non-polymerized saturated carboxylic acid such as oxalic acid, and dissolved in water along with a dispersing and coalescing agent, realized as an ester of a non-polymerized saturated carboxylic acid, and dissolved in the water to provide a liquid fire inhibitor solution that can be sprayed on combustible surfaces to form thin alkali metal salt crystalline coatings on the combustible surfaces when and as water molecules in the liquid fire inhibitor evaporate to the environment during drying operations, to inhibit fire ignition, flame spread and smoke development.

This invention discloses an integrated prediction method and system for fire spread coupled with smoke and meteorological feedback. The method first estimates forest fire emission parameters in real time based on satellite remote sensing data and converts them into spatiotemporal dynamic emission fluxes identifiable by the numerical weather chemistry (WRF-Chem) model. Grid interpolation is then used to match the WRF-Chem meteorological and chemical grid. Secondly, based on WRF-Chem simulations, the bidirectional coupling process between smoke aerosols and the meteorological field is simulated to generate a dynamic meteorological field incorporating smoke radiation feedback. Finally, the dynamic meteorological field is input into the weather-wildfire coupled simulation and the WRF-Fire weather research and forecasting model to simulate the feedback effect of smoke on fire spread. This invention reveals for the first time an aerosol-dominated positive feedback chain: fire emissions, through the synergistic effect of thermodynamic heating and radiative forcing, provide scientific support for disaster prevention decision-making and improve emergency response efficiency.

A directed energy firefighting device is disclosed to extinguish fires with light, comprising a structured light generator and a directed energy controller for detecting and extinguishing fires remotely and at the speed of light. The device employs structured directed light energy capable of inducing atmospheric avalanche breakdown, generating at least one of sound waves and shockwaves, and dynamically forming space-time acoustic arrays for precise fire suppression. The system may integrate one or more energy sources, including gyrotrons, traveling wave tubes, klystrons, free electron lasers, and others, to produce diffraction-resistant and dynamically structured beams that penetrate through the atmospheric and non-metalic solid physical obstructions. Key features also may include safety mechanisms and artificial intelligence for real-time optimization. Other applications include power beaming, environmental monitoring, medicine, disaster response, and orbital debris clearing are also discussed. A key feature is the ability for arbitrary manipulation of light over large areas.

A service inputs wind data and utility data corresponding to a utility component into a first machine learning model to determine an outage risk prediction representing a probability that the utility component will have an outage. The service determines a probability of ignition at a vicinity of the utility component, and determines a set of wildfire impact measurements by simulating a wildfire in the vicinity of the utility component. The service inputs the outage risk prediction, the probability of ignition, and the set of wildfire impact measurements into a second machine learning model, and receives as output from the second machine learning model, a catastrophic wildfire risk score corresponding to the utility component. The service outputs a graphical representation on a dashboard representing the catastrophic wildfire risk score.

Provided are a device and a method for detecting a wildfire. The wildfire detecting device may include: an image data acquisition module acquiring image data captured by a shooting device; an image data storage module storing the image data acquired through the image data acquisition module in a storage space; a wildfire detection module performing wildfire detection by using a deformable convolution based deep learning model to which smoke characteristics widely diffused are reflected by dynamically adjusting a filter position by using a learnable offset from the image data; and a wildfire direction and position estimation module estimating a direction and a position of the wildfire with respect to a case where it is determined that the wildfire occurs by the wildfire detection module.

A wildfire defense system includes a first tank for storing a first fluid, a second tank for storing a second fluid, a mixing valve, two pumps, a controller, and one or more sprayers. The wildfire defense system is controllable remotely allowing property owners to protect structures prior to wildfires without having to be on their property. The first pump pumps the first fluid from the first tank to the mixing valve, and the second pump pumps the second fluid from the second tank to the mixing valve. The controller controls the operations of the pumps and the mixing valve. The mixed fluid is sprayed over a selected geographic region through the sprayers. The apparatus can be remotely activated and the ratio of the first fluid to the second fluid in the mixed fluid is configurable. The system is transportable, allowing for easy relocation or fixed in a dedicated location.

This patent is about fighting Wildfires and Large fires. Wildfires start from small fires. By the time people know a wildfire is burning in a remote area, it has grown so big that it is difficult to control or to extinguish. There are two steps to fight wildfires: to know it faster or earlier while the wildfire is small and to fight the fire efficiently. Large fires are explosions causing a factory or a train to burn. They are difficult to control by ordinary fire fighting techniques. An entity will have to monitor an area in real time using information from satellites and strategically placed monitoring thermal imaging devices and cameras near or in forests. Once a wildfire is confirmed, helicopters, airplanes and / or drones will be used to spread pellets or powder of dry ice on the fires. If necessary, water will be sprayed or spread after that.