Viraj Anand

Worked with the Applied AI & Product Innovation team on applied Gen-AI and automation workflows (using various AI tools & AI first programming frameworks & languages).

The internship project focuses on the development of an autonomous vehi cle prototype utilizing the ESP32-S3 microcontroller for on-device percep tion through a lightweight YOLO (You Only Look Once) object detection model. The system integrates real-time environmental sensing, processing, and decision-making to enable autonomous navigation in controlled environ ments. By leveraging the ESP32-S3’s dual-core architecture and hardware acceleration capabilities, the project optimizes a tailored YOLO model for efficient object detection, including obstacles, lane markers, and traffic signs. The implementation includes sensor fusion with cameras and ultrasonic sen sors, ensuring robust perception under constrained computational resources. The project aims to demonstrate the feasibility of deploying advanced com puter vision algorithms on low-cost, resource-limited hardware, paving the way for scalable and energy-efficient autonomous vehicle solutions. Perfor mance metrics, such as detection accuracy, processing latency, and power consumption, are evaluated to assess the system’s effectiveness for real-world applications

Nights and Weekends Season 5