Researcher(s)
- Alyssa Mohammed, Electrical Engineering, University of Delaware
Faculty Mentor(s)
- Mohsen Badiey, Electrical and Computer Engineering, University of Delaware
Abstract
Commercial underwater acoustic systems are often prohibitively expensive and complex, limiting their accessibility to small-scale or budget-constrained research teams. To address this, we developed a low-cost, open-source underwater acoustic system built around a custom printed circuit board (PCB) featuring an ESP32 microcontroller. Our integrated device transmits pre-programmed acoustic signals through an underwater speaker, records incoming signals with a hydrophone, and logs spatial and temporal metadata—including GPS coordinates and timestamps—to a microSD card. All system functions are controlled via a single button press, minimizing user interaction and making the device easy to deploy in the field.
The system is designed to evaluate underwater acoustic signal propagation in real-world conditions. During testing, a Lubell underwater speaker is placed approximately one meter from the onboard hydrophone, while additional distant hydrophones are deployed elsewhere in the water column. By comparing the received signals at different distances, we can assess how environmental factors such as salinity, temperature gradients, pressure, and turbulence influence signal integrity, delay, and distortion. These insights are critical for improving underwater positioning systems, communication protocols, and environmental monitoring tools.
To extend the platform’s utility, we also developed an above-water variant of the system. This version allows us to investigate how sound behaves in air under varying temperature and humidity conditions. Together, the underwater and above-water setups offer a dual-media acoustic testing framework for comparing how sound propagates through water versus air.
The system’s modular design and integrated PCB significantly reduce size, cost, and assembly complexity compared to traditional systems. Its open-source nature enables easy customization and educational use. Future work will explore real-time signal processing, expanded sensor integration, and robust long-term deployment strategies, making this platform a versatile tool for acoustic research across multiple environments.