Publication Date: 2022/11/25
Abstract: Agriculture plays a crucial role in the overall growth of the nation. Around 70% of the population is directly or indirectly dependent on irrigation, while about one-third of the country’s (India) revenue is obtained from agriculture. Even so, the demand for food is increasing day by day and may continue to do so for decades. To solve this exceeding demand a feasible solution would be to use smart-farming techniques to enhance effectiveness and productivity and reduce manual labour, latency and overall expenses. But the farmers in the developing nation mainly rely on the traditional farming methods as they smart-farming techniques are expensive. Our paper addresses this issue of affordability by incorporating IoT and machine learning-based design that will help farmers monitor the soil quality based on the moisture content present. This paper proposes a system which will monitor the environmental factors using IoT and determine the moisture content of the soil. With the help of the data accumulated, machine learning is used to predict the future soil moisture. And lastly, a basic GUI is implemented to take environmental parameters as input and output of the soil moisture.
Keywords: Agriculture, Soil Moisture, IoT, Machine Learning, GUI
DOI: https://doi.org/10.5281/zenodo.7359208
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT22NOV902.pdf
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