# Project export: AquaGuard: Solar-Powered Water Monitoring Robot

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## Project metadata

- Hackathon: CruzHacks 2026
- Tagline: A solar-powered floating robot that monitors water quality in rivers & lakes, detects pollutants, and sends real-time alerts to protect communities and environment.
- Devpost: https://devpost.com/software/aquaguard-solar-powered-water-monitoring-robot-xsu5cg
- GitHub: not linked
- Demo: https://ab2882489-hue.github.io/AquaGuard-Solar-Powered-Water-Monitoring-Robot/
- Video: https://www.youtube.com/embed/dipvcBaNTP0?enablejsapi=1&hl=en_US&rel=0&start=&version=3&wmode=transparent
- Result: winner (Best Hardware Hack – Powered by ROBOTIS, Joby Aviation, OpenMV, PCBWay)
- Team: contributor stats unavailable

## Devpost submission (written by the team)

### Inspiration

Water pollution in rivers and lakes is a growing global concern. Communities, wildlife, and ecosystems are often affected before problems are detected. We wanted to create an automated, eco-friendly solution that provides real-time insights and helps protect water bodies.

### What it does

AquaGuard is a solar-powered floating robot that monitors water quality in real-time. It detects chemicals, pH levels, oil layers, and floating trash, and sends live alerts to a mobile/web dashboard for immediate action.

### How we built it

We designed a floating platform powered by solar panels and controlled by an Arduino/Raspberry Pi microcontroller. The robot is equipped with sensors for pH, chemicals, oil, and trash detection. Data is transmitted via Wi-Fi, LoRa, or GSM to a cloud-based dashboard with mobile notifications.

### Challenges we ran into

Ensuring stable movement and floating on water surfaces. • Integrating multiple sensors for accurate readings. • Maintaining reliable communication in remote areas. • Managing power consumption while using solar energy.

### Accomplishments we're proud of

Fully autonomous and solar-powered design. • Real-time water quality monitoring and alert system. • Scalable solution that can cover large water bodies efficiently.

### What we learned

We gained hands-on experience with IoT systems, sensor integration, and sustainable robotics. We also learned about designing for real-world environmental challenges and creating user-friendly dashboards.

### What's next

Future plans include AI-based pollution trend prediction, fleet coordination for larger rivers and lakes, and potential automatic trash collection in addition to monitoring.

## README (from the GitHub repository)

No README available.

## Detected evidence (automated analysis)

No repository was indexed for this project. Claimed technologies below could not be checked against code.
- JavaScript (language) — claimed on Devpost, not found in the code

## Codebase structure

No repository index available.

## Key source files

No repository index available; no source files included.