Classification of Soil Moisture Content with the Application of Deep Learning

India is an agricultural-oriented nation where soil moisture plays a vital role in the growth of plants and crops. Measuring soil moisture and maintaining a balance in the soil moisture content help sustain water resources. The traditional method for calculating the soil moisture content is to calculate the weight of moisture soil and dry soil differences. With time passage, different techniques are introduced based on different sensors. Recently, machine learning and deep learning have emerged as powerful tools and can be used for the classification of different levels of soil moisture. Convolution Neural Network is a technique used in the field of deep learning for the classification of images. This algorithm is used to analyze the images on various factors like texture, color, hue, and shapes. In this research, images have been collected from the internet image search and stored in separate folders according to their class. CNN is applied to the created dataset and after tuning the hyperparameters model reaches an accuracy of 73%.