Disasters herald significant threats to lives, livelihoods, and infrastructure for vulnerable sectors such as the fisherman communitiesCommunities and healthcare systems. Traditional disaster managementDisaster management often does not show speed, accuracy, and real-time decision-making. This paper discusses developing sector-specific resilienceResilience hubsSector-Specific Resilience Hubs (SSRH) (SSRHs) supported by Internet of Things (IoT)-driven disaster predictionIoT-driven disaster prediction models and artificial intelligenceArtificial intelligence (AI)-based response systemsAI-based response systems toward support for communitiesCommunities. The integration of environmental sensors, real-time data analysis, and predictive models in the SSRH would allow for an early warning of disasters, fewer economic losses, and better preparedness in medicine. Simulations using Matrix Laboratory (MATLAB) show that this methodology is effective for predicting storm surges, tsunamisTsunamis, and medical crises, creating a roadmap to real-world application.