Prajwal Maski
Papers
2
Total Citations
42
H-Index
2
About
Prajwal Maski is a researcher at the intersection of artificial intelligence, precision agriculture, and ecological conservation. His primary research focuses on developing advanced deep learning algorithms for real-time environmental monitoring and plant disease detection. Maski’s most cited work, “Plant Disease Detection Using Advanced Deep Learning Algorithms: A Case Study of Papaya Ring Spot Disease” (2021, 28 citations), introduces a novel approach to identifying plant pathogens using optical sensors and deep neural networks, significantly improving the speed and accuracy of agricultural diagnostics. This work addresses critical challenges in agricultural robotics, aiming to enhance crop yield and reduce losses. Building on this foundation, his 2023 study “Real-time biodiversity analysis using deep-learning algorithms on mobile robotic platforms” (14 citations) tackles the urgent issue of global biodiversity decline. By integrating mobile robotics with AI, Maski provides a scalable, real-time methodology for quantifying species populations—a breakthrough for conservation initiatives that previously lacked feasible monitoring tools. His contributions bridge the gap between field robotics and ecological data science, offering practical solutions for sustainable agriculture and biodiversity preservation.
Research Focus
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Top Papers
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