Abstract : In critical situations such as medical emergencies, domestic violence, or fire incidents, people, particularly those with speech or physical impairments, may not be able to seek help by conventional means. This work presents a gesture-based real-time emergency alert system that uses AI-driven technologies integrated within an edge-cloud architecture. The system runs on a lightweight edge device, such as a Raspberry Pi, and captures live video to detect predefined emergency gestures using a computer vision-based approach with landmark extraction and gesture classification. Upon confident detection, the system triggers automated alerts through SMS or voice calls using a cloud back-end hosted on AWS. To improve reliability, it incorporates confidence smoothing, gesture conflict resolution, and filtering mechanisms to reduce false positives. The proposed framework offers a scalable, low-cost and accessible enhancement to existing emergency response systems.