Crop Growth Prediction Based on Environmental Factors Using IoT & Machine Learning

Crop Growth Prediction Based on Environmental Factors Using IoT & Machine Learning

Tanvi D. Chaudhari1, Sujeetkumar Singh2, Harshada Barve3, Sakshi Aher4, Mr. Amol Gosavi5

1, 2,3,4 UG Student, Batchelor of Computer Engineering, MET’S, BKC, IoE, Nasik, India.

5Assistant Professor, Department of Computer Engineering, MET’S, BKC, IoE, Nasik, India.

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Abstract - Agribusiness growing rapidly day by day. As soil is an important factor in agriculture; Healthy soil is playing an important role in crop yield. Soil fertility level and its parameter measurement is a tedious task for farmers. It becomes challenging for farmers to fulfil the requirement of the living being. Some of the big challenges face by the farmers are Dealing with soil fertility issues as they are cultivating same crop year and year. As soil and its micronutrient is an important factor for agriculture. There are several kinds of soil. Each type of soil can have different kinds of features and different kinds of crops grow on different types of soils. Environmental factors like temperature, rainfall, soil pH and Humidity also affects crop growth.

In the proposed paper We developed a technique with the Internet of Things (IoT) and Machine Learning that enhance the soil problem. Which enhances farmer's position after taking all of these problems into consideration. IoT and Machine learning is a game-changer for the agricultural industry. With the advent of collected data from smart sensors and available standard datasets. We suggest the crop using machine learning algorithms and this precision technique.

Keywords: IoT, rainfall, pH, Humidity, Random Forest, Decision Tree, Machine Learning