See as a Bee: UV Sensor for Aerial Strawberry Crop Monitoring
This addresses precision agriculture for strawberry farmers by enabling more efficient crop monitoring, but it is incremental as it builds on existing remote sensing and deep learning techniques.
The paper tackled strawberry flower detection by designing a UV-reflectance sensor inspired by bee vision for aerial monitoring, demonstrating that the UV-G-B image detector outperforms an RGB-based method, though specific performance numbers are not provided.
Precision agriculture aims to use technological tools for the agro-food sector to increase productivity, cut labor costs, and reduce the use of resources. This work takes inspiration from bees vision to design a remote sensing system tailored to incorporate UV-reflectance into a flower detector. We demonstrate how this approach can provide feature-rich images for deep learning strawberry flower detection and we apply it to a scalable, yet cost effective aerial monitoring robotic system in the field. We also compare the performance of our UV-G-B image detector with a similar work that utilizes RGB images.