Fuzzy-Based Decision Support Systems for Disaster Management in Smart Cities
Yatham Thirumalanayudu,
Shaik Saidabi,
Devireddy Mamatha
In the context of smart cities, effective disaster management is paramount for ensuring public safety
and resilience against natural calamities. This research presents a novel fuzzy-based decision support
system (DSS) designed to enhance disaster response capabilities compared to traditional DSS models. By
integrating real-time data from IoT sensors, social media, and meteorological forecasts, the fuzzy-based
approach adeptly handles uncertainties and ambiguities inherent in disaster scenarios. Experimental
results indicate that the fuzzy-based DSS significantly improves response times, achieving reductions
of up to 55% compared to traditional systems, while also enhancing decision-making accuracy to
rates as high as 92%. Moreover, the fuzzy system demonstrates superior resource allocation efficiency
and garners higher user satisfaction ratings. These findings underscore the efficacy of fuzzy logic in
transforming disaster management practices, positioning it as a critical component for the development
of resilient smart city infrastructures.
