ABSTRACT
In early days, farmers farmed in a very mundane way by figuring the ripeness of the soil as well as considering the area type. They didn’t ponder regarding the water level, climatic conditions, or humidity. Agriculture has always played a vital role in our country, India. Issues concerning agriculture have become a matter of prime importance. Over the last ten years, there has been huge progress in science and technology-related domains. This technology can benefit the agricultural field in many ways such as predicting the suitable crop based on Nitrogen, Phosphorus, and Potassium content in the soil, water conservation, increase in yield production, increase in quality and quantity of the yield, remote monitoring, etc. The Internet of things (IoT) has provided us with better ways of farming by installing various sensors and motors. In this paper, an IoT-based smart farming model is used. Machine learning-related algorithm is used to predict the yield of the crop as per the sources. This is equipped with so many sensors for measuring and calculating environmental conditions required for farming. It consists of NodeMCU and so many sensors for calculating and analyzing the entire process. It helps the farmers to collect accurate data about the weather and soil conditions so that they can make accurate decisions about farming. This constructive model will help farmers by executing tasks like soil moisture sensing, humidity sensing, water level detection, temperature measurement, detection of animal intrusion along with the total gain of the crop is predicted in the farm automatically. Based on the conditions switching on/off the motors is very helpful for them, when they are in the field as they need not bother about the dryness or excess moisture in the fields. Therefore, this model of IoT synced with machine learning algorithm is very helpful in farming.
