Agriculture forms the backbone of India’s economy and significantly influences daily life. Its role is evident in the food that people consume, the jobs it generates, and its contribution to economic stability and well-being. However, due to poor yields, the number of farmers is gradually declining. According to existing literature, three key factors affect the yield of cultivated land: effective water management, early detection and diagnosis of plant diseases, and an adequate supply of essential nutrients such as nitrogen, phosphorus, and potassium. To boost production, auto-irrigation systems, nutrient monitoring systems, and disease forecasting tools (apps) have been developed. A field model of an auto-irrigation system has been implemented. An Arduino-based NPK sensor system has been developed to measure soil nitrogen, phosphorus, and potassium levels. Additionally, farmers receive nutrient data through an NPK sensor monitoring app, and a web app provides fertilizer recommendations based on NPK data. Finally, an app will be developed to identify the type of disease affecting a plant and to offer a treatment for that condition. The diseases are identified using a Convolutional Neural Network (CNN) algorithm.