Kassaundra Sewa-Santiago was born and raised on the island of O‘ahu. She graduated from Mililani High School in 2023 and is currently pursuing a major in Electrical Engineering with a minor in Computer Science at Hawai‘i Pacific University. Kassaundra plans on getting her Master’s degree in Electrical Engineering and remain in O‘ahu to pursue her career. In her free time, she enjoys meeting new people, hiking, the beach, sports (basketball, cornhole, etc.), and playing music.
Home Island: O‘ahu
High School: Mililani High School
Institution when accepted: Hawai‘i Pacific University
Project Site: USDA ARS Pacific Basin Agricultural Research Center, Hilo, Hawai‘i Island
Mentors: Peishih Liang & Jason Dzurisin
Project title: Integration of Harmonic Radar Technology and Unmanned Aerial Vehicles for Improving Insect Tracking Range and Efficiency
Project Abstract:
For decades, tracking technology has played a crucial role in understanding and monitoring wildlife, mainly utilized for conservation and biological research. At the United States Department of Agriculture’s Agricultural Research Service, Pacific Basin Agricultural Research Center (USDA-ARS-PBARC), scientists are working to understand the behavior, flight patterns, wind-driven dispersal, and the path of insect pests by adapting one of these tracking technologies: harmonic radar. Harmonic radar operates similarly to a boomerang, where a signal is sent out and returned through a transceiver. The transmitted signal strikes an insect tag, composed of a Schottky diode and a superelastic nitinol wire antenna, which in turn reflects a harmonic frequency to the transceiver. However, the current tracking process is done on foot, which results in limited range, difficulties with rapid insect movement, encounters with environmental obstructions, and a time-consuming data collection process. For this project, we are looking to advance current methods by integrating harmonic radar with an unmanned aerial vehicle (UAV). As a result, we can detect targets over a greater range and work more efficiently, collecting more data throughout the day. To make this possible, we prototyped a compact drone mount for the transceiver and an enclosure for the Raspberry Pi, and connected the Raspberry Pi to the UAV telemetry port. The mount includes shielding to protect the transceiver from signal interference from the UAV. Lastly, we developed a Python program for the Raspberry Pi to acquire and process the telemetry data from the UAV and the signals from the harmonic radar transceiver.