Year: 2025
Type: article
Abstract: Urban rivers in India, such as the Mula-Mutha in Pune, are increasingly burdened by surface-level garbage pollution due to rapid urbanization and inadequate waste management. Our project presents an integrated, technology-driven solution to address this issue through real-time monitoring, detection, and community-driven action. We employ the YOLOv8 deep learning model for object detection to identify and localize surface garbage in real-time images captured from the Mula-Mutha River. The model is trained on a custom dataset to ensure high accuracy in detecting floating waste. These insights are then used to trigger cleanup actions facilitated through a decentralized, blockchain-based crowdfunding platform. The platform allows local citizens to contribute funds transparently and securely, while NGOs, schools, and volunteers are invited to participate in scheduled cleanliness drives. Additionally, a dedicated website has been developed to share updates, event schedules, impact statistics, and encourage greater community participation. This project demonstrates the power of combining artificial intelligence, blockchain technology, and civic engagement to tackle urban environmental challenges in a scalable and transparent manner.
Author: Prof. Ujwala Wanaskar
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410958534