Skip to main content Jan 2025 - now Jan 2025 - now AMBER Affordable Multimodal Sensor-Based Environmental Risk Detector AI/ML ›
- Engineered a wearable industrial helmet, with 6 multimodal sensors & edge computing to detect environmental hazards
- Developed a custom data pipeline and TLV-based sensor communication protocol in python, optimizing sensor fusion
- Soldered and wired electronic components, ensuring durable sensor connectivity and efficient signal processing
Jan 2025 - May 2026 Jan 2025 - May 2026 Undergraduate Researcher McComish Dept of Electrical Engineering and Computer Science, SDSU AI/ML ›
- Awarded $5,000 Future Innovators grant to develop AMBER: Python-based real-time hazard detection system with edge computing
- Researching sensor fusion and ML-based risk assessment models using Python, OpenCV for hardware prototyping and testing
- Investigating low-latency risk detection integrating Raspberry Pi 5 edge devices with multimodal sensor fusion