37th Annual Student Research Conference
AI-Powered Approach of illegal Dumping Detection: Supporting Sustainable waste management practices
Sadik Yamin
Dr. Kafi Rahman, Faculty Mentor
Abstract:
This research proposes an interdisciplinary AI-powered framework to address the pervasive issue of illegal dumping, focusing on roadside waste detection and recycling promotion. By leveraging drone-based aerial imagery and deep learning algorithms, the system autonomously identifies garbage hotspots, facilitating prompt intervention by stakeholders. Through collaboration with local waste management agencies and utilization of the Google Cloud AI platform, the project aims to develop a real-time monitoring system capable of detecting and classifying various waste types. The proposed methodology encompasses data collection, AI model development, system design, pilot testing, and evaluation. Ultimately, the integration of technology with sustainable waste management practices not only mitigates environmental hazards but also fosters economic viability and job creation within the recycling sector. This research offers a scalable solution applicable to diverse geographic regions, emphasizing the synergy between AI, environmental science, and social responsibility in addressing global sustainability challenges.
Keywords: Illegal dumping detection, Drone-based monitoring, Deep learning algorithms, Sustainable waste practices
Topic(s):Computer Science
Presentation Type: Oral Presentation
Session: 208-4
Location: MG 1098
Time: 11:15