System Architecture for Large-Scale AI Data Collection

This project was conceived to solve a critical data infrastructure problem for a major international AI research initiative. The success of any AI venture, whether commercial or governmental, depends on access to vast, high-quality datasets. This system was built to provide that foundation.

The Challenge

High-stakes AI applications require training data that is diverse, clean, and captured at a scale that is impossible to achieve manually. The challenge was to design a cost-effective, automated, and reliable system to generate this data.

My Solution

I architected a full-stack, multi-robot framework using Python and C++. The system managed a fleet of autonomous robots that could navigate complex environments and capture over 80 hours of high-fidelity audio data (13,000+ samples). My role included designing the system architecture, developing the software for robot coordination and data synchronization, and ensuring the integrity of the final dataset.

Tech & Skills

• Languages: Python, C++
• Frameworks: Robot Operating System (ROS)
• Core Competencies: Systems Architecture, Data Engineering, Robotics, Automation