Digital Agriculture: Impact of IoT and AI on Indian Agribusiness

Shivam Satyawan Madrewar; Nimisha Ravindra Khadkikar; Om Vijay Suryawanshi; Jasmin Shakil Mulani; Ajay Rajaram Sagar

doi:10.59890/ijaeam.v2i4.2346

Authors

Shivam Satyawan Madrewar R. C. S. M College of Agriculture, Kolhapur
Nimisha Ravindra Khadkikar R. C. S. M. College of Agriculture, Kolhapur
Om Vijay Suryawanshi I.F.M.R Graduate School of Business, Chennai
Jasmin Shakil Mulani R. C. S. M. College of Agriculture, Kolhapur
Ajay Rajaram Sagar R. C. S. M. College of Agriculture, Kolhapur

DOI:

https://doi.org/10.59890/ijaeam.v2i4.2346

Keywords:

Digital Agriculture, Internetof Things, Artificial Intelligence, Smart Farming, Indian Agribusiness

Abstract

This research explores the impact of IoT and AI on various aspects of Indian agriculture, including crop yield optimization, resource management, and market integration.IoT and AI technologies offer advanced solutions such as precision farming, automated irrigation, and predictive analytics, which can significantly enhance agricultural productivity and sustainability. IoT devices, including soil sensors, weather stations, and drones, provide real-time data that allows farmers to make informed decisions regarding crop management, pest control, and irrigation schedules. AI algorithms process this data to predict crop yields, optimize the use of inputs like water and fertilizers, and streamline supply chain management. This paper draws on data from government reports, including those from the Ministry of Agriculture & Farmers Welfare and the National Sample Survey Office (NSSO), to assess the effectiveness and adoption of these technologies across different regions of India.The findings of this research indicate that regions where IoT and AI technologies have been implemented have seen a noticeable increase in crop yield, ranging from 15% to 20%. These technologies have also led to a significant reduction in water usage, with automated irrigation systems optimizing water resources by up to 30%. Additionally, AI-driven market analytics have improved farmers' access to markets, helping them to secure better prices for their produce by predicting market trends and demands

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