Intelligent Child Safety System: Facial Recognition for Missing Child Identification with Real-time Email Alerts to Authorities

Abstract: Intelligent Child Safety System uses live video monitoring, face recognition, and automated email notifications for rapid child-abduction response. Ongoing feeds are monitored, and a constantly updating database has continuously comparesa number of the children with Dlib's CNN and HOG-based detection methods, combined with another model based on VGG's CNN model for great results in even low-light, obscured faces and varied angles of facial positions. An instant alert is sent by email to law enforcement agencies, child-care agencies, and relevant bodies with an accompanying captured face once the match is made, thus allowing quick action. Also, real-time alerts go to an administrative dashboard, allowing the monitoring of recognition results and adjusting the settings of the alerts. Strong measures for security and privacy, such as access controls to sensitive information, are in place to ensure ethical and secure operation. This automated alert and decision-making facilitate effective real-time monitoring and response while greatly reducing traditional reliance on search. Enhancements for further improvements in accuracy and adaptability include multimodal biometric authentication, voice recognition, and predictive analytics. Under very challenging conditions, the system has high reliability due to its 95.0% accuracy, 93.0% precision, 95.2% recall, and an F1 score of 94.1%. It ensures precise detection of actual cases of missing children by reducing the number of false positive values. It can thereby deliver quick responses reliably since high F1 scores signify an equilibrium between recall and precision. Equipped with facial identification powered through AI, live monitoring, and an automated decision-making mechanism, Intelligent Child Safety is an effective and scalable tool for working through the course of retrieval for missing children.