Poonam Pawar
Papers
1
Total Citations
2
H-Index
1
About
Poonam Pawar is an emerging researcher at the intersection of agriculture and artificial intelligence, with a primary focus on leveraging IoT and machine learning for precision farming. Her work addresses a critical challenge in modern agriculture: the efficient detection and management of weeds, which can reduce crop yields and increase production costs. In her most cited study, "A Study of Weed Management in Agricultural Plants using IoT and Machine Learning" (2024), Pawar introduces a novel framework that combines sensor-based IoT data with machine learning algorithms to accurately identify and classify weed species in cultivated lands. This approach not only distinguishes between beneficial and harmful weeds but also enables real-time, targeted interventions, reducing the need for blanket herbicide applications. Although early in her career, with her work already garnering citations, Pawar’s contributions are paving the way for more sustainable, cost-effective, and data-driven weed management strategies. Her research holds significant promise for smallholder farmers and large-scale agricultural operations alike, positioning her as a rising voice in the field of smart agriculture and environmental sustainability.
Research Focus
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Top Papers
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