C5.0: Advanced Decision Tree (ADT) classification model for agricultural data analysis on cloud

Agriculture plays a crucial role in India’s economy and around 70% of people earn their income through it and also provides large employment opportunities. The technological advancement has led to remarkable achievements in developing Agricultural based software applications to get faster information. But, many farmers are still applying the traditional methods of farming and hence the result of productivity becomes very low. Agriculture prediction process for organic and inorganic farms is an open issue and it depends upon weather, soil fertility, water, seasons and commodity prices, etc. Soil fertility factor is paramount important to maintain the crop growth and increase the production. The soil fertility levels help the farmers to identify the deficiencies in the soil, namely nutrient content, soil type, pH value, EC (Electrical Conductivity) value and soil texture and to choose the right crops to increase the production. In this work, as a novelty, the soil fertility level is predicted by analyzing the Virudhunagar District Soil information and recommendations are offered for crop selection and sowing by using C5.0: Advanced Decision Tree (ADT) classifier algorithm. Using this technique, an Android-based mobile phone applications named as Design of Smart Information System (DSIS) application has been developed. The proposed application activates the Global Positioning System (GPS) to identify the user location. The performance of proposed model is analysed and it is compared with the existing classification model for agricultural data.