A Community-Based AI Framework for Fire Disaster Risk Reduction in Urban Areas

DOI

10.2991/978-94-6239-754-5_17How to use a DOI?

Keywords

Digital Transformation; Community Resilience; Disaster Risk Reduction; Artificial Intelligence; Social Innovation

Abstract

Residential fire incidents remain a persistent challenge in many urban areas of Indonesia, leading to significant social and economic losses. Conventional mitigation efforts are often constrained by limited public awareness, delayed emergency reporting, and the absence of effective early warning systems. This study presents the SI APIC (Siaga Api Cerdas) initiative as a community-based digital transformation model that integrates artificial intelligence (AI), digital reporting platforms, and community empowerment to strengthen local disaster resilience. A qualitative case study approach was employed to examine the implementation of the program in Padang Sambian, Denpasar, Bali. Data were collected through observation, documentation review, participant assessments, and stakeholder feedback, and analyzed using thematic analysis with methodological triangulation. The program involved 395 community members and demonstrated measurable improvements in community preparedness. More than 90% of participants achieved high comprehension scores in post-training assessments, and the majority reported increased confidence in responding to fire emergencies. The deployment of AI-enabled CCTV provided real-time early detection capabilities, while integration with digital reporting systems improved coordination with emergency services. This study contributes to the literature by proposing an integrated digital resilience framework that combines AI-based early warning systems, digital platforms, and structured community engagement. The findings highlight that aligning digital technologies with social innovation and stakeholder collaboration can produce sustainable and scalable disaster risk reduction outcomes in urban communities.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Oky Iyan Pratama
AU  - Febrian Sukma Wardhana
AU  - Daniel David Hartama Sitompul
PY  - 2026
DA  - 2026/09/02
TI  - A Community-Based AI Framework for Fire Disaster Risk Reduction in Urban Areas
BT  - Proceedings of the International Conference on Digital Transformation in Business and Organisations (ICDTBO 2026)
PB  - Atlantis Press
SP  - 187
EP  - 197
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-754-5_17
DO  - 10.2991/978-94-6239-754-5_17
ID  - Pratama2026
ER  -