Smart Agriculture Using Iot and Machine Learning

Abstract

 In recent years, farmers have had to deal with a lot of problems. Some of these problems include scarcity of water, improper crop selection, lack of knowledge on modern farming techniques, improper irrigation control etc. Even today, a large section of the farmers are dependent on the traditional farming techniques. It involves the use of an approximation of the amount of manure, fertilisers and irrigation needed, which does not guarantee maximum harvest output. In order to address these issues and to ensure a better yield, an attempt is made to develop an application that can predict the fertiliser content and the type of crop that would be most suitable for the selected area based on the environmental factors and can also implement an automatic irrigation system remotely. To do this, the trained submodels of the main system are used to process the environmental factors that affect plant growth and the water level is considered for irrigation purposes. Smart agriculture that is enabled by the Internet of Things (IoT) allows farmers and growers to maximise productivity while minimising waste in areas such as the amount of fertiliser used, the number of trips made by farm vehicles, and the efficient use of resources such as water and electricity. IoT smart agricultural solutions are systems that track crop fields and automate irrigation systems. It makes use of various sensors, devices, software etc. which help increase the yield.