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AI-Based Wildfire Prevention, Detection and Suppression System

JSHS · 2022

Prisha Shroff, Debbie Nipar · Hamilton High School, Chandler, AZ

Overview

Wildfires pose a serious threat to the world’s environment. The global wildfire season length increased by 19% and severe wildfires besieged nations globally. Every year, wildfires burn forests, causing vast amounts of carbon dioxide to be released into the atmosphere, contributing to climate change. There is a need for a system which prevents, detects and suppresses wildfires. The AI-based Wildfire Prevention, Detection and Suppression System (WPDSS) is a novel, AI-based solution that effectively detects hotspots and wildfires, and deploys drones to spray fire retardant, preventing and suppressing wildfires. WPDSS consists of four steps. 1. Pre-processing: Loads real-time satellite and meteorological data from NASA and NOAA of vegetation, temperature, precipitation, wind, soil moisture and land cover for prevention. For detection, it loads real- time data of Land Cover, Humidity, Temperature, Vegetation, Burned Area Index, Ozone and CO2. 2. Learning: AI model consists of a random forest classifier which uses a series of decision trees to make an accurate decision and is trained using a labeled dataset of hotspots/wildfires and not-hotspots/not- wildfires. 3. Identification: Runs real-time data through the model to automatically identify hotspots and wildfires. 4. Drone Deployment: Drone flies to hotspot and wildfire locations. WPDSS attained a 98.6% accuracy in identifying hotspots and 98.7% accuracy in detecting wildfires. WPDSS will reduce the impacts of climate change, protect ecosystems and biodiversity, avert huge economic losses and save human lives. The power of WPDSS developed can be applied to any location globally to prevent and suppress wildfires, reducing climate change.

Competition history

  • JSHS 2022 Category not listed

Resources

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