AI and Automation in Environmental Hazard Detection

This workshop explores how AI is transforming environmental risk monitoring by integrating remote sensing, IoT sensor networks, satellite imagery, and predictive analytics to enhance public safety and ecological resilience. Participants will gain hands-on experience with tools and platforms such as Google Earth Engine, YOLO/Deep Learning for image detection, scikit-learn for environmental datasets, and automated alert systems using Arduino/Raspberry Pi.

• Introduce advanced AI and automation tools for environmental applications

• Bridge gaps between climate data, sensors, and AI models

• Promote interdisciplinary collaboration between tech and environmental fields

• Enable participants to contribute to climate adaptation and disaster preparedness

• Provide open-access tools and datasets for continued innovation

📅 Day 1: Introduction to AI in Environmental Hazard Detection

🔹 Environmental Hazards & AI’s Role

• Overview of hazards (pollution, natural disasters)
• AI’s transformative capabilities in detection & prediction

🔹 AI & Machine Learning Fundamentals

• Key ML techniques for hazard analysis
• Data preprocessing & algorithm selection

🔹 🛠️ Hands-On Lab: AI Tools for Hazard Detection

• Setting up AI environments
• Building basic predictive models

📅 Day 2: Advanced AI Techniques for Hazard Detection

🔹 Remote Sensing & AI for Monitoring

• Leveraging satellite/drone data + GIS integration
• AI-powered hazard tracking

🔹 Deep Learning for Hazard Detection

• Optimizing CNNs & RNNs for environmental threats
• Model training & performance tuning

🔹 🛠️ Hands-On Lab: Remote Sensing Data for Detection

• Processing real-world satellite imagery
• Training deep learning models

📅 Day 3: Automation & Real-Time Monitoring

🔹 AI & IoT for Real-Time Monitoring

• Sensor networks + AI for instant hazard alerts
• Edge computing for rapid response

🔹 Automating Hazard Detection & Response

• AI-driven decision pipelines
• Case studies in wildfire/flood prediction

🔹 🛠️ Hands-On Lab: Building a Real-Time System

• Developing an automated detection prototype
• Simulating emergency alert scenarios

• Environmental scientists and disaster management professionals

• Data scientists and engineers working in sustainability

• Urban planners, civil engineers, and remote sensing experts

• Government agency representatives and NGO workers

• UG/PG/PhD students in environmental science, AI, or geoinformatics