International Journal of Science, Engineering and TechnologyAuthors: Amit Kumar, Deep Samanta, Arnab Bhunia,, Atish Kumar Sah, Kabeeta Chaudhary
Abstract: Agriculture faces challenges of resource inefficiency, climate variability, and the need for sustainable food production. This paper introduces Farming Tech Solutions, a precision agriculture framework integrating IoT, artificial intelligence, and data analytics to support smarter farming practices. The system employs real-time sensors for soil and crop monitoring, predictive models for weather and yield estimation, and machine learning techniques for crop recommendation and disease detection. A prototype is developed and assessed on scalability, accuracy, and responsiveness. Results demonstrate improved irrigation efficiency, early detection of crop stress, and reduced manual intervention. The study highlights the potential of digital farming ecosystems to empower farmers with actionable insights and promote sustainable agricultural growth.
