Authors :
Seema Patil; Viren Patel; Shreyan Yoge; Sumedh Kamble; Harsh Pandey
Volume/Issue :
Volume 7 - 2022, Issue 11 - November
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3AInkKG
DOI :
https://doi.org/10.5281/zenodo.7359208
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
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
