The RC boat to submarine project addresses the critical need for non-invasive, cost-effective monitoring of marine ecosystems by developing a submersible capable of autonomous species identification. By integrating a Raspberry Pi 4 for real-time image processing, the vehicle can detect and categorize marine life based on color and pattern recognition through its acrylic dome, providing researchers with high-fidelity data without disturbing the natural habitat. This matters because traditional manual surveying is often limited by diver depth constraints and the high cost of industrial submersibles, whereas this Pixhawk-stabilized platform offers a scalable solution for long-term biodiversity tracking. This technology directly benefits marine biologists and conservationists by automating the cataloging of indicator species, ultimately aiding in the protection of vulnerable aquatic environments through precise, localized data collection.
Background:
Aquatic environments are essential for environmental monitoring, infrastructure inspection, and scientific research, yet they remain challenging to study due to limited accessibility and demanding operating conditions. Tasks such as tracking invasive species, assessing habitat health, and inspecting submerged structures often rely on manual sampling or diver-based methods, which are time-consuming, costly, and potentially disruptive to sensitive ecosystems. To address these challenges, robotic systems have been developed to operate in aquatic environments and improve data collection efficiency. Remotely operated vehicles (ROVs) provide real-time control but are limited by tethered operation, while autonomous underwater vehicles (AUVs) can execute pre-programmed missions using onboard sensors and navigation systems. Despite their effectiveness, AUVs are often expensive, complex, and impractical for smaller-scale users such as academic institutions or low-budget research teams. Furthermore, most existing systems are designed to function either on the surface or underwater, rather than both, which introduces inefficiencies for missions requiring transitions between these environments.
Advancements in compact electronics, embedded control systems, and low-cost manufacturing techniques such as 3D printing have made it feasible to develop smaller, more affordable hybrid platforms. These systems can integrate manual remote control with autonomous capabilities while maintaining manageable cost and system complexity. By incorporating onboard sensors, microcontrollers, and efficient propulsion systems, a hybrid vehicle can achieve stable surface navigation, controlled submersion, and basic environmental sensing. This presents an opportunity to bridge the gap between high-cost professional systems and limited-function hobby platforms. The objective is to develop a cost-effective, easy-to-deploy solution capable of performing aquatic monitoring tasks without requiring extensive infrastructure or technical expertise, while minimizing environmental disturbance.