Reshma Kumari

Papers

Total Citations

H-Index

About

Reshma Kumari is at the forefront of agricultural robotics, pioneering intelligent automation to address critical challenges in modern farming. Her research masterfully integrates computer vision, deep learning, and robotic manipulation to create practical, end-to-end solutions for crop management. Her most-cited work, "Integrated Robotics System for Ripeness Detection, Tomato Harvesting and Leaf Disease Identification using CNN and YOLOv8" (2024), exemplifies this holistic approach. In this study, she developed a unified robotic system capable of simultaneously performing three essential tasks: assessing fruit ripeness, executing precise harvesting, and identifying leaf diseases in real-time. By combining Convolutional Neural Networks with the YOLOv8 object detection framework, Kumari’s system achieves remarkable accuracy and efficiency, directly addressing the agricultural sector's pressing need to reduce labor costs and operational waste. Though early in its citation impact, this work represents a significant leap toward fully autonomous, data-driven agriculture. Kumari’s contributions are particularly notable for their practical applicability to short-lifecycle crops, promising to enhance food security and sustainability. Her research stands as a compelling model for how robotics and AI can transform traditional farming into a precision-driven, resource-efficient industry.