APPLICATION OF INTERNET OF THINGS AND MACHINE LEARNING IN SMART FARMING FOR EFFICIENT RESOURCE MANAGEMENT
DOI:
https://doi.org/10.29121/shodhkosh.v5.i1.2024.1910Keywords:
IoT, Machine Learning, Smart Farming, Smart IrrigationAbstract [English]
A new field of study termed as “smart farming” which uses machine learning (ML) and the internet of things (IoT) for maximizing agricultural resource management. With a growing world population and desire to achieve sustainable food production, it is crucial to improve farming techniques in order to make good use of limited resources such as fertilizers, electricity, and water. This research work examines the employment of IoT plus ML in smart farming so that various components are discussed like cloud computing, data collection, sensor networks as well as decision-making algorithms. Some instances are given where internet of things devices such as soil moisture monitors and temperature sensors present real-time data on crop conditions and water requirements, insect infestations among other relevant information. In this case, farmers can utilize machine learning algorithms to analyze this data against various prediction models for effective resource allocation purposes. Efficient resource management in smart farming helps minimize wastage, reduce environmental impact, and increase agricultural productivity. IoT and ML technologies enable real-time monitoring and control, enabling farmers to optimize water and fertilizer usage based on crop needs and environmental conditions. Smart irrigation systems automatically adjust watering schedules, while precision agriculture techniques employ ML algorithms to determine optimal planting patterns and apply targeted pest control measures, reducing the need for chemical use. This paper examines the advantages, difficulties, and potential applications of IoT and ML technologies in smart farming for effective resource management through a thorough examination of case studies and research projects in the agricultural sector. It underscores the potential of these technologies to revolutionize traditional farming practices and promote sustainable agricultural practices.
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Copyright (c) 2024 Dr. Umakant Butkar, Dr. Rupesh Mahajan, Dr. Devidas S. Thosar, Dr. Sweety Mahajan
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