Graduation Semester and Year
Fall 2025
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Electrical Engineering
Department
Electrical Engineering
First Advisor
Wei-Jen Lee
Second Advisor
Ali Davoudi
Third Advisor
Rasool Kenarangui
Abstract
The global decline in honeybee (Apis mellifera) populations has raised significant concerns for agriculture and ecosystems due to their essential role in pollination. Central to the stability and productivity of a honeybee colony is the health of the queen bee, as she serves as the sole reproductive individual, directly influencing colony dynamics and sustainability. This study proposes a non-intrusive queen bee monitoring system capable of tracking the real-time movement of a hypothetical queen bee and issuing alerts if a decline in her activity is detected. The system consists of a ferromagnetic material tag attached to the back of the queen bee and a matrix of sensor units embedded between each frame of the beehive. To minimize the impact on the colony from electromagnetic interference, the sensors are activated sequentially and do not contain permanent magnetic materials. This dissertation presents the design, implementation, and operational framework of the proposed method, demonstrating its effectiveness in accurately tracking the hypothetical queen bee’s movements. The systems are now capable of providing early warnings to beekeepers based on real-time monitoring results. In the future, as the system is deployed in real-world environments and additional data are collected, these data can be leveraged to analyze queen bee behavior and facilitate research in apiculture and colony health monitoring.
Keywords
Honeybee colony health, Queen bee monitoring, Non-intrusive tracking system, Sensor matrix, Early warning system
Disciplines
Other Electrical and Computer Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Su, Po En, "A NOVEL NON-INVASIVE QUEEN BEE TRACKING SYSTEM" (2025). Electrical Engineering Dissertations. 413.
https://mavmatrix.uta.edu/electricaleng_dissertations/413
Comments
I would like to express my deepest gratitude to my advisor, Professor Wei-Jen Lee, for his consistent support throughout my Ph.D. studies and academic program. His patience, motivation, and immense knowledge have been invaluable to me. His guidance has been instrumental in every stage of my research and in the writing of this dissertation.