Mapping and Monitoring of Solid Wastes and Their Leakage using Machine Learning

As plastic and solid waste pollution continue to grow as global challenges, this course offers a unique opportunity to explore cutting-edge monitoring techniques using machine learning and geospatial technologies. Participants will learn how to detect and map waste leakage using satellite data, drone imagery, and AI-enabled tools such as object detection and smart CCTV systems. The course includes hands-on training in building basic ML models, visualizing results through dashboards, and designing evidence-based strategies for waste management and policy advocacy. This program is ideal for environmental professionals, smart city planners, and researchers working on urban sustainability and pollution control.

Participants will be guided through the following content-rich modules:

• Module 1 – Understanding Waste Leakage and Monitoring Frameworks
• Module 2 – Satellite and GIS Waste Mapping
• Module 3 – Basic Introduction to Machine Learning
• Module 4 – Introduction to Object Detection – Application in Real-Time Monitoring with AI & CCTV
• Module 5 – Dashboarding, Reporting & Policy Linkage

Key Learning Outcomes

1. 1. Understand the environmental impact and pathways of waste leakage
2. 2. Apply machine learning tools to classify and detect solid waste using imagery
3. 3. Develop monitoring workflows using drones, satellite data, and CCTV systems
4. 4. Create maps and dashboards for data visualization and decision support
5. 5. Evaluate policy implications from spatial waste evidence

For more information or to register, please contact:

Mr. Kona V A Kiran – Program Officer, AIT Extension

📧 konakiran@ait.ac.th | 📞 +66 644 733 220

To explore more similar courses, please visit:
🌐 https://extension.ait.ac.th/content/upcoming-courses