Deepak Sundriyal
Papers
1
Total Citations
6
H-Index
1
About
Deepak Sundriyal is a researcher at the forefront of applying artificial intelligence to critical environmental challenges, with a primary focus on waste management and smart sensing systems. His most cited work, "Waste Detection and Classification Using Yolo Algorithm and Sensors" (2023), addresses the pressing issue of improper waste disposal—particularly in densely populated Indian metro cities like Mumbai, which generate over 150,000 tonnes of municipal solid waste daily. Sundriyal’s key contribution lies in integrating the YOLO object detection algorithm with sensor-based systems to enable real-time, automated waste classification and collection. This work has garnered 6 citations, reflecting its growing relevance in the fields of computer vision and environmental sustainability. By targeting the inefficiencies in current waste management practices—where only a tiny fraction of garbage is properly collected—Sundriyal’s research offers a scalable, technology-driven solution that can significantly reduce health risks and environmental degradation. His work exemplifies the practical application of deep learning to societal problems, making him a notable figure in the intersection of AI and sustainable urban infrastructure.
Research Focus
Key Achievements
Top Papers
- 1Waste Detection and Classification Using Yolo Algorithm and Sensors6 citations · 2023