Fire risk zone analysis system using a predictive model for time and resource optimization

Suca J.C.C.; Medina D.J.T.; Oliden D.A.S. · Proceedings of the 2021 IEEE Sciences and Humanities International Research Conference, SHIRCON 2021 (2021) · DOI: 10.1109/shircon53068.2021.9652390

Resumen

In this paper, we propose a predictive solution to optimize the time of analysis for the identification of fire risk areas. This proposal consists of two applications: mobile and web. Both applications have functionalities that allow the user to obtain information about the identified risk areas: (1) Fire Register, (2) Risk Zone Register, (3) Display of available resources, (4) Display of fire risk zones, (5) Consultation of emergencies attended to in the last 24 hours and (6) Notification in the event of proximity to a risk zone. The proposal is described in three sections: (1) the optimization of the current process of analysis and identification of fire risk zones, (2) the functionalities of the web and mobile solution, (3) the implementation of the predictive analysis and (4) the designed technological architecture. The validation of the proposal consisted of two parts (1) Validation of the web application in conjunction with INDECI members, with data and records of fires that we obtained from the institution for the analysis of risk areas and (2) Validation of the mobile application that was conducted with 20 users to identify the time of search for risk areas. The results showed that the time of the analysis process was optimized by 75%, while the search time by 90.6%, which mainly generates a social benefit to the citizens by ensuring the quick and efficient identification of fire risk zones, based on a predictive analysis.

Instituciones: Universidad Peruana de Ciencias Aplicadas