AI Enabled Seismic Sentinel Initiative: Integrating Predictive Analytics, GPS Guided Evacuation, and Compliance Frameworks to Strengthen University Based Earthquake Resilience and Community Protection
DOI:
https://doi.org/10.5281/zenodo.20338315Keywords:
AI enabled disaster resilience, Seismic Sentinel Initiative, Predictive analytics, GPS guided evacuation, Compliance frameworks, Community resilienceAbstract
Urban universities in Metro Manila face heightened seismic risks due to dense populations, aging infrastructure, and limited evacuation routes. This study evaluates the AI‑Enabled Seismic Sentinel Initiative, a disaster resilience program developed in compliance with Republic Act No. 10121, CHED Memorandum Order No. 9, and Manila Ordinance No. 8323. The initiative integrates predictive analytics, GPS‑guided evacuation, multilingual communication, and compliance frameworks into a cohesive university‑based disaster management ecosystem. A mixed‑method design analyzed system logs, SMS delivery records, compliance audits, and user feedback to assess reliability, behavioral change, and policy alignment. Results show a 70.6% SMS success rate, predictive alarms with an average 15.3‑second lead time, and 80% immediate evacuation participation. Community indicators reveal 85% satisfaction and trust, alongside 70% adoption of evacuation plans. By embedding AI‑driven monitoring and compliance integration into institutional protocols, the initiative advances beyond procedural compliance to establish a transformative model of resilience, positioning Universidad de Manila as a leader in disaster‑ready universities.
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