Innovative Multidisciplinary Journal of Applied Technology Ҷилди 3 № 10 (2025) · Саҳифаҳои 144-149
Digital-Based Fire Risk Classification for Preventive Fire Safety Management in Developing Countries Topic Information
Habibovna, Razoqova Mahfiza
Аннотатсия
Preventive fire safety management is continually challenging in developing countries, which is a global consequence of spontaneous urban growth, excessive infrastructure density, and overworked supervisory resources. Fire risk classification is fundamental for ensuring inspections are prioritized and incidents are minimized, however, many regulatory frameworks still depend on static criteria and isolated reporting. This study presents an approach for a digital based fire risk classification framework, aiming to improve preventive fire governance in developing settings, with a particular case of Uzbekistan. However, the main knowledge gap is the low level of conversion of officially collected inspection data into systematic, multi criteria risk models that would enable for evidence-based supervision. This research utilizes a mixed method design that integrates regulatory analysis, a systematic analysis of digital inspection data, and algorithmic modeling. To transform compliance indicators, patterns of violations, characteristics of the object into the weighted risk scores, a multi criteria classification algorithm is developed. We employ simulation testing to evaluate the proposed digital and apply comparisons with age-old classification practices. Results show that utilizing digital categorization not only improves prioritization accuracy and reduces inspections subjectivity but also increase preventive control transparency. The results show that data driven classification allows for more efficient allocation of supervisory resources and increase on the fire safety management predictive capacity. Pragmatic implications are that institutional accountability can be more firmly entrenched, and that regulatory modernization can scale up more readily in other developing countries with similar administrative bottlenecks. This study lays the groundwork for future research on real time monitoring systems, machine learning analytics, and interoperable safety databases. Digital risk allows for adaptive, preventive fire governance that responds to changing urban and industrial risk environments; we demonstrate this approach as one way forward.
digital fire risk classificationpreventive fire safety managementdeveloping countriesrisk-based supervisionalgorithmic inspection systems
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