Sanjana Prasad

Papers

Total Citations

H-Index

About

Sanjana Prasad is a rising researcher at the intersection of agricultural robotics and deep learning, whose work tackles critical challenges in precision farming. Her most cited contribution, "Integrated Robotics System for Ripeness Detection, Tomato Harvesting and Leaf Disease Identification using CNN and YOLOv8" (2024), exemplifies her core focus: deploying computer vision and robotic manipulation to automate complex agricultural tasks. This pioneering system unifies three essential functions—ripeness assessment, selective harvesting, and disease diagnosis—into a single intelligent platform, significantly reducing labor costs and crop waste. By integrating Convolutional Neural Networks with the YOLOv8 object detection framework, Prasad’s work demonstrates how real-time, on-field AI can transform short-lifecycle crop management. Though early in her career, with 4 citations already accrued, her research signals a strong trajectory toward scalable, cost-effective solutions for modern agriculture. Her approach not only advances the field of agricultural automation but also offers a blueprint for future integrated systems that can adapt to diverse crop types and environmental conditions. For students and researchers, Prasad’s work is a compelling example of how deep learning and robotics can converge to address real-world sustainability challenges.