Paper Contents
Abstract
Smart farming is a paradigmatic change in agricul- tural practice through the application of state-of-the-art technolo- gies like the Internet of Things (IoT) and Artificial Intelligence (AI) towards productivity, efficiency, and sustainability. In this research study, an intelligent farm system is exemplified that aims to address some of the most significant challenges in conventional agriculture, like water shortage, pest control, and unforeseen climatic conditions. The system uses IoT sensors such as temperature, humidity, and soil moisture sensors through a NodeMCU microcontroller to obtain real-time environmental and soil conditions. The information is sent to a cloud platform and displayed on a responsive web application developed using the MERN stack technology(MongoDB, Express.js, React.js, Node.js), allowing farmers to monitor their field conditions remotely from anywhere. To further complement crop health management, the system includes AI(Artificial Intelligence)-based predictive models that examine past and real-time sensor data to predict future plant diseases. Additionally, image processing is used for early blight and late blight detection in plant leaves so that farmers can implement effective preventive measures at the right time. An automated irrigation system is utilized to ensure maximum use of the available water, which only switches on when the water level in the soil drops below a set limit, thus conserving water. The system also gives com- puterized advice on the maximum application of fertilizers and pesticides, aimed at the precise needs of specific crops. Besides on-field monitoring and automation, the system also comprises an AI-driven market price analysis module through which farmers are able to make well-decided choices about selling crops so as to bring maximum profitability. Through IoT-based automation, AI-driven analytics, and cloud-based monitoring, the system promotes precision farming, minimizes the reliance on human resources, and saves resources. The paper thoroughly discusses the system architecture, implementation issues, and major advantages like increased crop yield, minimizing cost, and encouraging sustainable agricultural practices.The integration of diverse technologies enables seamless data collection and real- time insights for better crop planning. Farmers can track trends over time, allowing them to predict seasonal outcomes with higher accuracy. This technological approach empowers local growers to compete in broader markets with confidence. Future expansion of the system includes drone field monitoring for bulk monitoring, blockchain for supply traceability, and extending AI models to include other crops. This project shows how applications of smart farming technologies can transform conventional farming to provide scalable and efficient solutions to farming challenges today with environmental sustainability and economic viability to farmers.Index TermsSmart Farming, IoT, AI, Disease Prediction, Automated Irrigation, MERN Stack, Precision Agriculture
Copyright
Copyright © 2025 Hitesh Chandrashekhar Bhosale. This is an open access article distributed under the Creative Commons Attribution License.
