Efficient communication is vital in emergency situations, and leveraging modern technologies can significantly enhance response capabilities. The proposed work introduces a system that enables communication through hand gestures mapped to Morse code symbols. The system integrates advanced computer vision techniques, utilizing the MediaPipe framework for real-time hand gesture recognition. Hand gestures are classified into Morse code symbols using a feedforward neural network (FNN), allowing users to input text through gestures. Additionally, the system incorporates a binary tree structure for Morse code decoding and integrates an automated emergency notification feature, sending SMS alerts upon recognizing distress signals. It proves beneficial in emergency scenarios by enabling silent signaling and remote alerts. In industrial settings, it facilitates hands-free communication in noisy environments and provides quick emergency alerts. In healthcare, it assists non-verbal patients and supports silent notifications. The system can be integrated with existing systems and devices, enhancing its utility and adaptability.