eDesigning an IoT-Supported Tsunami Preparedness Model Using Sensor Data, Local Wisdom, and Community Communication Channels

The coastal zones of Indonesia are still highly vulnerable to the threat of tsunamis especially where technical early warning systems are not well integrated with community awareness and response. This research developed an IoT-supported tsunami preparedness model that combines sensor information, local wisdom, and community communication channels to improve last-mile disaster communication in Bandar Lampung. This study used a qualitative exploratory case study approach based on expert-based focus group discussion information and a structured readiness assessment involving stakeholders in disaster management, local governance, social inclusion, risk communication, community leadership and IoT engineering. The result shows that the tsunami preparedness system of Bandar Lampung is in the moderate readiness category. Existing strengths include communication pathways through local government, RT/RW networks, mosque loudspeakers, community leaders and the emergent use of IoT-based environmental monitoring. However, there are a number of gaps including sensor reliability, maintenance procedures, public understanding of IoT signals, two- way feedback, vulnerable groups, evacuation drills and standardisation of warning messages. The proposed hub-and-spoke model allows IoT sensors to send environmental informasi to a local decision-support hub, where the informasi are converted into actionable messages and disseminated through trusted community channels such as kentongan and traditional leaders. This study advocates for people-centered coastal resilience as per SDG 11 and SDG 13.