Monitoring RPW Infestation Using Thermal, Hyperspectral and Novel Tracking Techniques
Alper Yusuf Bozkurt
Project runs from 07/01/2018 to 06/30/2020
In this project, we undertake a multi-disciplinary approach, exploiting both remote and in-situ sensing, to identify the potential of these emerging technologies for the early detection of the Red Palm Weevil. Unmanned Aerial Vehicles (UAVs) will be deployed as a mobile and adaptable delivery sensing platform, leveraging their unique characteristics to monitor from tree to plantation scales using specialized sensors. Imagery will be collected through a controlled experiment that seeks to monitor both healthy and infested trees, providing the basis for imagery analysis using machine learning, data integration and related analytical approaches. We will leverage this areal platform with the deployment of ground-based, but wirelessly connected, animals in the field. Through the development of electronic wearables, UAVs will be able to “sense” animals in real time, providing information on their location, biometrics (heart and respiratory rate) and behavior as an indicator of RPW infestation and to inform search and detection outcomes.