Randhir Dinesh
Papers
2
Total Citations
7
H-Index
1
About
Randhir Dinesh is an emerging researcher at the forefront of applying artificial intelligence and Internet of Things (IoT) to critical real-world challenges, particularly in environmental sustainability and precision agriculture. His work centers on developing autonomous detection systems that leverage advanced computer vision algorithms to address pressing issues in waste management and crop health. Dinesh’s most cited paper, "Waste Detection and Classification Using Yolo Algorithm and Sensors" (2023, 6 citations), tackles India’s staggering daily generation of over 150,000 tonnes of municipal solid waste, proposing an AI-driven solution to improve collection and reduce pollution in densely populated metro cities like Mumbai. More recently, his 2024 study on "Autonomous IoT-Integrated Tomato Plant Disease Detection" harnesses the YOLOv8 algorithm and micro-navigation to protect the vital tomato crop from climate-exacerbated illnesses, showcasing his ability to merge cutting-edge technology with agricultural needs. Though early in his career, Dinesh’s work demonstrates significant potential for societal impact, offering scalable, sensor-integrated solutions that could transform how communities manage waste and safeguard food security.
Research Focus
Key Achievements
Top Papers
- 1Waste Detection and Classification Using Yolo Algorithm and Sensors6 citations · 2023
- 2