SMART FARM: Crop, Fertiliser and Disease Management through Machine Learning and Deep Learning Applications


Authors : MuttareddyBhavika; Pannala Ashwanth; Valaboju Abhishek

Volume/Issue : Volume 9 - 2024, Issue 7 - July

Google Scholar : https://tinyurl.com/5n7v657r

Scribd : https://tinyurl.com/2mbtk5z6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUL549

Abstract : In the environment of global challenges similar as population growth, climate change, and resource constraints, the agrarian sector faces significant pressure to enhance productivity and sustainability. This paper explores the conception and perpetration of a Smart Farm, which leverages advanced technologies similar as the Internet of effects( IoT), artificial intelligence( AI), big data analytics, and robotics to optimize husbandry practices. The Smart husbandry, automated ministry, and data driven decision-making processes to increase crop yields, reduce resource consumption, and ameliorate environmental stewardship. Case studies punctuate successful operations of these technologies in colorful husbandry surrounds, demonstrating significant advancements in effectiveness and sustainability. The findings emphasize the eventuality of Smart granges to transfigure traditional husbandry into a largely productive, flexible, and sustainable assiduity, able of meeting unborn food security demands.

References :

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  3. Barik, N. 2018. Analysis ofinterventions addressing farmer distress in Rajasthan. https://www. copenhagenconsensus.com/sites/default/files/rajfarmer distress sm.pdf
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In the environment of global challenges similar as population growth, climate change, and resource constraints, the agrarian sector faces significant pressure to enhance productivity and sustainability. This paper explores the conception and perpetration of a Smart Farm, which leverages advanced technologies similar as the Internet of effects( IoT), artificial intelligence( AI), big data analytics, and robotics to optimize husbandry practices. The Smart husbandry, automated ministry, and data driven decision-making processes to increase crop yields, reduce resource consumption, and ameliorate environmental stewardship. Case studies punctuate successful operations of these technologies in colorful husbandry surrounds, demonstrating significant advancements in effectiveness and sustainability. The findings emphasize the eventuality of Smart granges to transfigure traditional husbandry into a largely productive, flexible, and sustainable assiduity, able of meeting unborn food security demands.

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