AI and Automation in Environmental Hazard Detection
International Workshop on Smart Technologies for Environmental Monitoring and Disaster Risk Reduction
About This Course
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.
Aim
To train participants in leveraging Artificial Intelligence (AI), Machine Learning (ML), and automation technologies for real-time detection, prediction, and mitigation of environmental hazards, from floods and wildfires to chemical leaks and air pollution.
Workshop Objectives
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Introduce advanced AI and automation tools for environmental applications
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Bridge gaps between climate data, sensors, and AI models
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Promote interdisciplinary collaboration between tech and environmental fields
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Enable participants to contribute to climate adaptation and disaster preparedness
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Provide open-access tools and datasets for continued innovation
Workshop Structure
📅 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
Who Should Enrol?
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Environmental scientists and disaster management professionals
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Data scientists and engineers working in sustainability
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Urban planners, civil engineers, and remote sensing experts
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Government agency representatives and NGO workers
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UG/PG/PhD students in environmental science, AI, or geoinformatics
Important Dates
Registration Ends
07/03/2025
IST 4 PM
Workshop Dates
07/03/2025 – 07/05/2025
IST 5:30 PM
Workshop Outcomes
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Understand the role of AI in real-time environmental monitoring
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Apply ML models to real-world environmental datasets
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Build simple automated alert systems using IoT and AI
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Analyze satellite and sensor data for environmental insights
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Contribute to sustainable development and early warning innovations
Fee Structure
Student Fee
₹1999 | $50
Ph.D. Scholar / Researcher Fee
₹2999 | $60
Academician / Faculty Fee
₹3999 | $70
Industry Professional Fee
₹5999 | $90
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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