Modified crop health monitoring and pesticide spraying system using NDVI and Semantic Segmentation: An AGROCOPTER based approach

Abstract

The technology in agriculture, can help farmers especially in the time of COVID pandemic, where there is shortage of labor and increasing demand for food. The technology solution can effectively and reliably improve crop yield through automated process and Agrocopter. The Agrocopter, an autonomous drone with modular systems and on-board image processing helps in holistic crop management throughout the farm. Agrocopter comes with targeted crop spraying, nutrient dropping and seed sowing modules, that can work in sync with the process of crop life cycle from sowing till harvesting. The drone with edge computing module performs periodic farm surveillance and plant health analysis using combination of NDVI (Normalized difference vegetation index) and semantic segmentation based classification to take targeted actions. It makes use of filter banks and SVM (Support Vector Machine) classifier algorithm to carry out pixel wise stitched image analysis to compute plant health indices in real time. Being very easy to operate and maintain, it can seamlessly be integrated into the farm systems and work along-side humans. It also has a completely modular design with plug and play architecture. What sets Agrocopter apart is its wide variety of applications, reliability and precision all at an affordable cost. Hence, Agrocopter is the perfect aerial farm assistant for today’s farmer.