Environmental Challenge

With the current oyster population, it would require over a year for the entire Chesapeake Bay to be filtered. Oysters filter food through their gills and can remove sediments and other contaminants that pollute the bay. They also consume algae and help to reduce nutrients like nitrogen and phosphorus which set the stage for several environmental issues [1].

Using underwater ROVs to map oyster populations for more efficient planting and harvesting has the potential for wide-reaching consequences. Such a device could significantly impact local oyster populations and ecosystems, with potential benefits for global climate health and the aquaculture industry.

Industry Need

Currently, a number of organizations are working to restore the total oyster population back to its peak, but unlike agriculture, aquaculture is rooted in outdated methods of farming with little modern technology in use. With an affordable underwater ROV, oyster farms or restoration sites using bottom culture would be able to scale their operations much more efficiently.

With several sensors, ROVs could be used to collect a wide range of data to help farms make better decisions regarding their planting and harvesting. Using imaging sensors, data could be gathered to find hard surfaces where oysters could thrive without being buried in sediment. Imaging could also be used to evaluate the health and maturity of oysters.

Economic Impact

Oyster restoration has the potential to significantly grow aquaculture in the economies surrounding the Chesapeake Bay. With continued investment in restoration and maintenance of the oyster population, a wide range of jobs have been created. For example, in a single oyster reef restoration project in the Northern Gulf of Mexico, nearly 90 jobs were created [2]. Additionally, an increase in the oyster population would allow for higher capacity of several popular aquaculture species in an industry already worth more than $30 million [3].

Telemetry System

RS485 modules with twisted tether cable for signal integrity and interference reduction over long distances. Implementation based on Arduino RS485 library documentation and standard industrial communication protocols.

Control Interface

PlayStation controller integration with custom PWM range identification for precise joystick control and signal processing. Controller mapping and PWM interpretation developed through Arduino documentation and community resources.

Photogrammetry System

GoPro mounting and positioning for underwater 3D modeling and environment documentation. Photogrammetry processing using RealityCapture software following established underwater photography techniques.

Sensor Programming

Arduino-based sensor integration for pressure, temperature, and conductivity measurements with real-time data processing. Sensor libraries and calibration procedures adapted from manufacturer documentation and Arduino community examples.

3D Printed Electronics Housings

Custom-designed waterproof enclosures for electronic components using SolidWorks and additive manufacturing. This represents my most original design work, creating custom housings to fit specific component layouts and waterproofing requirements.

Areas for Improvement

As I continue working on this project, there are several main areas I plan to address. First is optimizing the current design - the pressure sensor requires further calibration for more accurate depth calculations. The soldering and PVC construction in some locations needs improvement, and to ensure a longer lifespan, the ROV will likely require replacement using the skills I've developed throughout this project.

Revisions to the water sampling mechanisms may be necessary depending on researcher consultation and determining how the bilge pump may alter water samples. The sensor package could be enhanced with an increased budget or creative designs, including additional sensors to collect more detailed information about the ROV's surroundings.

I plan to incorporate machine learning into the ROV to address photogrammetry challenges. With proper programming, the ROV may be able to learn how to navigate around features and optimize imagery collection to better suit existing photogrammetry software needs.

Learning Outcomes

Throughout this project, I've improved my computer-aided design, circuit design, electrical engineering knowledge, soldering skills, and understanding of environmental science. The numerous challenges in both construction and programming strengthened my perseverance and problem-solving abilities for future projects. I've learned to plan for setbacks and adapt accordingly. Additionally, I've gained understanding of how to undertake larger research projects and apply knowledge and skills from my education to address real-world problems. This project has been an invaluable experience that I expect will benefit my engineering career.