IoT-Driven Precision Farming with microdrone assisted field intelligence
Principal Investigator
Prof. Ayon Chakraborty
Objective
- Develop an IoT-enabled precision farming platform using microdrones, edge AI, and a physics-informed digital twin to enable real-time crop monitoring, early stress detection, and resource-efficient agriculture.
Description
- The project integrates IoT ground sensors, autonomous microdrones, edge AI, and a digital twin to continuously monitor field conditions, generate actionable insights, and provide irrigation and disease-risk advisories for precision farming.
Impact
- Improves water efficiency, reduces chemical usage, enables early disease detection, enhances crop traceability, and supports sustainable, AI-driven agriculture for Indian farming conditions.