Academic Innovations

This project, a collaboration between TIH-IoT and ICAR-NRCG, aims to develop and validate an IoT and machine learning-based decision support system for grape farmers. The system leverages real-time data on soil conditions, weather, leaf wetness, and vineyard microclimate to provide actionable advisories on optimized water and fertilizer use, and early detection and management of diseases.Using SAMBHAV and SAMADHAN systems developed by TIH-IoT, the project will monitor key environmental and plant parameters at selected farmers’ locations. This data, combined with disease-trigger conditions developed by ICAR-NRCG, will feed into ML models that generate precise advisories, delivered via the i-SARATHI mobile app. The solution will be field-tested at two vineyard sites to assess its effectiveness compared to conventional practices, aiming to improve berry yield and quality while reducing input costs. The insights gained will be used to refine the i-VineMS platform and promote sustainable grapevine management under tropical conditions.