Research Intern at Built Environment Lab

Revolutionizing Building Automation with Computer Vision and Machine Learning

Jan 2025 - Mar 2025

At the prestigious Built Environment Lab of IIT Roorkee, I embarked on an innovative journey to bridge the gap between human comfort and building automation. Our mission was to create an intelligent system that could detect and respond to human fatigue levels in real-time, revolutionizing how buildings adapt to their occupants' needs.

Working alongside distinguished researchers, I spearheaded the development of a cutting-edge computer vision system that tracks subtle eye movements and facial patterns to gauge fatigue levels. This wasn't just about writing code; it was about understanding the intricate relationship between human behavior and environmental comfort. By implementing advanced machine learning algorithms, we achieved an impressive 95% accuracy rate in fatigue detection.

The project's key innovation was developing a predictive analytics system that could anticipate and adjust building parameters before fatigue levels became critical. Using technologies like OpenCV, TensorFlow, and scikit-learn, we created a system that reduced energy consumption by 30% while maintaining optimal comfort levels.

Beyond technical development, I created the lab's comprehensive digital presence, building a knowledge hub that showcases research, facilitates information sharing, and fosters collaboration within the scientific community. This platform bridges the gap between academic research and practical applications in building automation.

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