• Harsh Kolarkar
• Harsh Patil

The project aims to enhance home security, convenience, and energy efficiency. The system utilises OpenCV, a popular open-source computer vision library, and Dlib, a powerful machine learning toolkit, to recognise and authenticate individuals based on their facial features. By analysing the real-time video feed from a camera, the system identifies registered users and performs predefined actions tailored to their profiles. The proposed home automation system offers a wide range of functionalities, including personalised access control, energy management, and smart device integration. Users can unlock doors, adjust lighting and temperature settings, and control appliances through facial recognition. Furthermore, the system adapts to users' preferences and learns their patterns to optimise energy consumption and provide a seamless user experience. Experimental results demonstrate the system's high accuracy in facial recognition with low false-positive rates. The project showcases the potential of OpenCV and Dlib in developing robust and reliable home automation systems based on facial recognition. The implementation offers promising avenues for future research and development in the field of smart homes, paving the way for safer, more convenient, and energy-efficient living environments.

Facial recognition, Home automation, Image processing, and Machine learning

"Smart Home Automation Using Facial Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.f110-f112, November-2023, Available :http://www.jetir.org/papers/JETIR2311511.pdf

"Smart Home Automation Using Facial Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppf110-f112, November-2023, Available at : http://www.jetir.org/papers/JETIR2311511.pdf