Ian Wei Xuen Foong

Jun 2026

To design and implement a low-cost edge AI system capable of detecting and monitoring crowd density in real time using computer vision, enabling early detection of congestion and improving situational awareness in public spaces. The system aims to operate on embedded hardware with low latency and continuous real-time performance. KEY SKILLS DEMONSTRATED Computer Vision Python Programming Machine Learning (Object Detection) Embedded Systems Development Edge AI Deployment OpenCV Real-Time System Optimization Flask Web Development Data Visualization

May 2026

[!TIP] Define clear, measurable outcomes for the project. Business/Project Goals Achieve a retail price point of under $85 USD. Target initial manufacturing run of 5,000 units by Q4. Build an open-source firmware ecosystem to encourage community mods. Technical Goals Reach operating temperature (350°C) from room temperature in < 5 seconds. Maintain temperature accuracy within ±2°C. Support USB-C Power Delivery (PD 3.0) up to 100W (20V/5A). 4. Requirements 4.1. Functional Requirements FR-01: The device must negotiate USB-C PD protocols to draw maximum available power (up to 100W). FR-02: The s

May 2026