IoT based Classification Techniques for Soil Content Analysis and Crop Yield Prediction
R. Reshma, V. Sathiyavathi, T. Sindhu, K. Selvakumar, L. SaiRamesh
Abstract
Agriculture aided by IoT is called Smart Agriculture and it gives rise to precision farming. Soil Monitoring combined with Internet of Things (IoT) technology aids in the enhancement of agriculture by increasing yield through gauging the exact soil characteristics such as Moisture, Temperature, Humidity, PH, and Nutrition content/Fertility. This data is then gathered in cloud storage and with the appropriate data operations; it enabled us to optimize farming strategies and helped create a trend analysis. This, then, allows us to precisely utilize resources and steer the farming methods in prudent ways to optimize yield. The proposed IoT system is composed of pH sensors, Humidity and temperature sensors, Soil moisture sensors, soil nutrient sensors (NPK) probes, microcontroller/microprocessor equipped with WiFi and Cloud storage. When the sensors are implemented, they measure the corresponding characteristics and transmit time-stamped live data to the cloud server. These sensors work together and provide wholesome data to the analyst. For the recommending system, the SVM and Decision Tree algorithm is proposed to get the crop suitable for the given soil data and helps to enhance the growth using an optimized farming process.