AI-Driven Child Safety System: Real-Time Fear Detection and Emergency Response using Enhanced Deep Learning Algorithms

AI-Driven Child Safety System: Real-Time Fear Detection and Emergency Response using Enhanced Deep Learning Algorithms is an intelligent child monitoring system designed to improve child safety through real-time emotion analysis and emergency communication. The system uses a Raspberry Pi as the main controller and a web camera to continuously monitor the child's facial expressions. Advanced deep learning algorithms analyze facial features to identify emotions such as fear, distress, panic, or abnormal behavior. When a fear-related or abnormal condition is detected, the system automatically captures an image of the child and sends an email alert to parents or guardians along with the captured image and live GPS location information. An emergency push-button interface is also provided, allowing the child to manually trigger an emergency alert whenever assistance is required. Python is used for image processing, deep learning-based emotion recognition, GPS tracking, and email notification services. The proposed system offers a smart, real-time, and proactive approach to child safety monitoring.