The operational resilience of disaster-prone communities relies on timely and reliable early warning systems. Conventional disaster management systems suffer from critical dependencies on cloud computing and continuous internet connectivity, which often fail during actual catastrophic events such as floods, earthquakes, cyclones, and landslides. This paper introduces a comprehensive Smart Disaster Prediction and Emergency Communication System that integrates Electronics, Communication Technologies, and Edge Artificial Intelligence to enable autonomous, real-time disaster prediction and alert dissemination without relying on centralized cloud infrastructure. The system employs a distributed sensor network comprising water level, temperature, vibration, gas, and humidity sensors deployed across vulnerable regions. Data collected by these sensors is processed locally using Edge AI algorithms deployed on microcontrollers and edge devices, enabling rapid anomaly detection and disaster prediction at the point of sensing. Upon detecting a potential disaster, the system automatically initiates emergency alerts through multiple communication pathways including LoRa, GSM, 5G, and satellite communication, ensuring message delivery even in scenarios of complete internet failure. The key innovation of this work is the decentralization of decision-making intelligence, shifting from cloud-dependent reactive systems to edge based proactive systems suitable for rural and remote disaster-prone areas. This convergence of embedded systems, wireless communications, and predictive AI demonstrates the feasibility of building smart, resilient infrastructure capable of autonomous disaster detection and response. Experimental validation and deployment scenarios confirm the system's effectiveness in providing critical warnings before disaster manifestation, enabling timely intervention and life-saving measures.