Intelligent Wildfire Prediction and Prevention (IFP2) by EnvironAI leverages Artificial Intelligence to help predict the probabilities for wildfires and assist firefighters in planning for and containing blazes. Our solution provides machine learning models that predict a forest fire and its path. A central hub orchestrates satellite imagery, weather and other data into Intelligent and predictive analytics services. We use our sensor data combined with satellite and weather to create a state of predictive opportunity which promotes prevention rather than cure.
We seek to leverage Artificial Intelligence to help predict the probabilities for wildfires and assist firefighters in planning for and containing blazes. We seek to lead the implementation for an AI solution that use ML data modeling for technologies that prove useful. We want to focus on being proactive, on predictability to solve issues urban, atmospheric, human, environmental causes for wildfires.
Our solution addresses this problem in the following ways:
Machine learning models that provide the ability to predict a forest fire and its path.
A central hub that orchestrates satellite imagery, weather data, etc.
Intelligence and predictive analytics services.
We use our sensor data combined with satellite and weather that aims to create a state of predictive opportunity which promotes prevention rather than cure.
Dashboard Analytics: To help battle against forest fire destruction, using the same partnerships to help local, state and federal government entities via subscription and licensing fee model. Provide up to date monitoring in using network of Ground Devices connected to Google IOT cloud. The analytics dashboard incorporates the results from the machine learning models.
Proactive Planning: Preventative actions in partnership with government entities under service agreement will use the historic analysis, construct near real-time predictions models used for future planning on prioritization of Timber Harvesting Plans (THP for Logging), Clearing Defensible Spaces, Planned Prescribed Control Burns, Fuel Hazard Vegetation Management and Reforestation Planting Programs.
We use AI modeling to improve predictable future dynamics. Our approach is a more realistic attempt to account for all factors, as our models are based on conditional data that leads to predicting where and how fast a fire is most likely to spread.