Research Projects

Precision Agriculture (PA) is a strategy that aims to optimize inputs and reduce inputs in agriculture towards low-input, high-efficiency, and sustainable practices. In India, over 58% of operational holdings have smaller fields, making it crucial for PA implementation. Accurate and timely information on crop acreage estimation, yield forecasting, and disease warnings is essential for policy formulation and management. However, the current agricultural information system faces challenges such as inability to provide accurate, timely, detailed, and easily accessible information. To address these issues, a Village-level Information System (VIS) with emphasis on agriculture data management and analysis is proposed. This system should incorporate on-farm spatial attributes such as soil type, water resource availability, farming activities, land availability, and production. Continuous monitoring and updating of these dynamic components is essential for real-time, precise, and timely decision-making. Automated monitoring of farmland activities and frequent crop attribute extraction is feasible through coupling satellite and drone/UAV images with advanced Artificial Intelligence AI algorithms. Automating the extraction of attributes on high resolution and large scale is complex, but the automated information update feature of VIS can provide analytics capabilities to forecast and capture trends and anomalies in crop statistics and conditions. This project proposes an innovative geospatial framework using advanced techniques and algorithms in Remote Sensing, Computer Vision, AI, and Big Data to build various components of the framework.