Date of Completion
5-10-2026
Degree Type
Honors Thesis
Discipline
Engineering (ENGR)
First Advisor
Gustavo Castillo
Second Advisor
Matt Siniawski
Abstract
The Marine AI System, BioScope, is developed to overcome the limitations of traditional environmental monitoring devices that fail in high-humidity and variable-temperature conditions. This project delivers a low-cost, modular, and autonomous platform capable of continuous data collection and onboard AI analysis in the environment. The system includes a 3D-printed housing, NVIDIA Jetson Orin Nano processor, microphone, fish eye and infrared camera, temp and humidity sensor, cooling fan, tripod, battery and solar panel. Designed for autonomous operation, IP65 waterproofing, and wireless communication, the system emphasizes energy efficiency, sustainability, and accuracy. Preliminary training and testing have encouraging results for reliable data capture, thermal stability, and durability in environments, supporting the project’s goal of providing a useful, and accessible monitoring tool that can be used in environmental research.
Recommended Citation
Ellinghuysen, Jaimin; Falope, Elisha; Harvey, Jordan; Slaybaugh, Joseph R.; Castillo, Gustavo; and Siniawski, Matt, "Bioscope: Modular AI Biomonitoring Device" (2026). Honors Thesis. 618.
https://digitalcommons.lmu.edu/honors-thesis/618
Included in
Artificial Intelligence and Robotics Commons, Biotechnology Commons, Environmental Indicators and Impact Assessment Commons, Systems Architecture Commons
