AI-Driven Wildfire Detection with Integrated Air Quality and Machine Learning Vision Systems Powered by an Accelerator for Early Action

Wildfires are causing tremendous threats to human lives, infrastructure, the environment, and human health, entail innovative approaches for prompt detection and control.This research presents a state-of-the-art wildfire detection system that integrates an AI accelerator with air quality data and machine learning systems to identify potential fire danger.Utilizing realtime ecosystem data, including humidity, PM, VOC, RH/T, and NO, the system predicts the likelihood of wildfire ignitions.Upon a potential wildfire identification, the AI accelerator activates vision-based systems.Combining the power of AI accelerator and Google Colab, this approach achieves an efficient, and scalable solution for wildfire detection.By integrating air quality monitoring and AI-driven vision systems, this research provides a scalable, real-time wildfire detection solution.