Published Paper Details:

Agriculture is a vital sector that significantly contributes to the economy and food security of many countries, including India. However, traditional farming methods often depend on manual observations and experience, leading to inefficient use of resources such as water, fertilizers, and pesticides. To address these challenges, this project proposes an AI-Driven Decision Support System (DSS) for Smart Agriculture using Internet of Things (IoT) sensors. The system continuously monitors environmental and soil parameters, including temperature, humidity, soil moisture, pH level, and rainfall, through a network of IoT sensors. The collected data is transmitted to a cloud platform, where Machine Learning algorithms analyze the information and generate intelligent recommendations for irrigation scheduling, crop selection, fertilizer application, and early disease prediction. By integrating IoT, Artificial Intelligence, and Decision Support Systems, the proposed framework enables real-time monitoring, predictive analytics, and data-driven decision-making for farmers. The system aims to improve crop productivity, optimize resource utilization, reduce operational costs, and promote sustainable and precision farming practices.