Neural Networks Bio-Inspiration for Disaster Prone Areas for Self-Healing Communication Systems

Disaster zones experience extreme losses in communication networks, calling for robust, self-healing networks. Biologically inspired neural networks provide adaptive solutions to connectivity in disaster zones. Current methods of communication are hindered by network failures, excessive latency, and poor resource utilization, which make them unreliable under disaster conditions. Conventional methods are non-real-time and devoid of dynamic recovery processes. The Bio-Inspired Swarm Intelligence with Neural Networks (B-ISI-NN) framework combines the use of swarm intelligence methods and neural networks for network robustness. Swarm intelligence facilitates decentralized decision-making, and neural networks foretell failures as well as enhance network restoration. Combined, they facilitate real-time self-healing, fault tolerance, and routing adaptation in the disaster area. This allows swift re-establishment of communication links to support continued data flow even when infrastructure damage occurs. The model automatically adapts network parameters in relation to environmental variations for enhanced efficiency and robustness. The results indicate that B-ISI-NN cuts down significantly on downtime, maximizes bandwidth usage, and raises the reliability of networks. Simulation reflects enhanced self-healing ability, making the suggested system a suitable solution for disaster relief and emergency response.