Intelligent Machine Learning Modelling for Soil Analysis and pH Prediction

Traditional laboratory testing for soil samples from various sites is frequently expensive and time-consuming. This study suggests replacing traditional lab testing with quick, precise answers using new technologies like the Internet of Things (IoT), sensors, and machine learning. The study specifically investigates the use of a portable Internet of Things device with sensors to examine soil samples in various areas of Haldwani in the Uttarakhand region. To categorize and forecast soil pH levels, this paper provides a foundation for an artificial neural network (ANN). The ANN model's outcomes demonstrate an astounding level of accuracy, coming in at 91%. This study demonstrates the potential of IoT-based strategies and machine-learning techniques for effective soil analysis and recommends practical ways to integrate them into existing soil testing procedures.