Design of Intelligent Home Security Handling System based on Face Recognition and IoT Assisted Technology

Security concerns pose significant challenges for residential homes, offices, and institutions, necessitating the deployment of trained personnel to ensure safety. However, human error remains a possibility, potentially compromising security measures. In response, the advancement of facial recognition systems has emerged, proving valuable for home door locking systems. These systems are user-friendly, accurate in identifying residents, and offer a convenient security solution. Facial recognition technology has evolved notably, with Convolutional Neural Networks (CNNs) playing a pivotal role. This method has proven effective in various applications, including object recognition. The study focuses on utilizing the AlexNet facial recognition system within a door locking system. The proposed model stands out with a remarkable sensitivity score of 96.745%, highlighting its exceptional precision in identifying positive cases. Notably, the system delivers accurate results for both authorized and unauthorized access attempts. This functionality addresses security concerns effectively.