Agri-IoT data and RGB images
Description
This dataset was collected as part of a research study evaluating the application of an Agri-IoT system for monitoring and managing potato crops under a drip irrigation system. The study assessed the capability of existing Agri-IoT sensors to support irrigation scheduling, monitor environmental conditions associated with disease development, and facilitate disease management. The study also demonstrated that environmental and soil sensors alone have limited capability to directly characterize crop growth and physiological condition. To address this limitation, reduced nitrogen availability was experimentally imposed to create contrasting crop-growth conditions, and RGB images were collected to monitor canopy growth dynamics and assess crop health. The repository contains two years of Agri-IoT sensor data and one year RGB images collected from field experiments conducted under drip irrigation. The Agri-IoT dataset includes measurements relevant to soil and environmental conditions, while the RGB image dataset provides visual information on potato canopy development throughout the crop growth period.
Files
Institutions
- Indian Institute of Technology KharagpurWest Bengal, Kharagpur