Microwave-based object detection for monitoring individual grain kernels

In agriculture, header losses, indicating the loss of grains at the combine harvester’s header, usually contribute the most of harvesting losses. While not entirely avoidable, their impact can be significantly reduced through careful monitoring of the harvesting process. In this proposed project, the intern aims to explore microwave-based
object detection technology as a solution to address the existing challenge. The primary goal of this initiative is to develop cost-effective proof-of-concept microwave monitoring system, accurately detecting individual grain kernels in specific agricultural areas and environments. The intern plans to enhance and adapt an ultra-high quality microwave resonator previously developed by their supervisor’s research group, achieving highly sensitive detection of detection of grain presence and movement. Simultaneously, the partner organization will provide valuable insights into monitoring and control systems for grain harvesting, ensuring that the intern’s research aligns closely with real-world application and could quantify losses occurring at the combine header.

Faculty Supervisor:

Can-Ming Hu

Student:

Partner:

JCA Technologies

Discipline:

Physics

Sector:

Agriculture and Food; Information and Communications Technology

University:

University of Manitoba

Program: