Sanjog Chhetri
Papers
1
Total Citations
2
H-Index
1
About
Sanjog Chhetri is an emerging researcher at the forefront of applying artificial intelligence and the Internet of Things (AIoT) to pressing environmental challenges. His primary research areas include computer vision, deep learning, and sustainable technology, with a focused application in underwater environmental monitoring. Chhetri’s most notable contribution is the development of an innovative underwater trash management system that integrates YOLOv8, a state-of-the-art object detection algorithm, with IoT-enabled segmentation techniques. This work, published in 2024, addresses the critical need for automated solutions to combat marine pollution by enabling real-time detection and classification of underwater debris. While his citation count is currently modest at 2, the timeliness and practical relevance of his research signal strong potential for future impact. Chhetri’s approach exemplifies how cutting-edge AI can be harnessed for environmental sustainability, bridging the gap between advanced machine learning and real-world conservation efforts. His work is particularly valuable for researchers and students interested in the intersection of deep learning, IoT, and ecological applications, offering a blueprint for scalable, automated environmental monitoring systems.
Research Focus
Key Achievements
Top Papers
- 1