Integrated system for early fire detection and evacuation based on Arduino

  • Akyltai Burgegulov Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
  • Talgat Mazakov Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
  • Gulzat Ziyatbekova Department of Information Systems, Al-Farabi Kazakh National University, Republic of Kazakhstan
  • Sholpan Jomartova Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
  • Aigerim Mazakova Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
DOI: https://doi.org/10.19139/soic-2310-5070-3087
Keywords: gas sensors, graph algorithms, smart city, building safety, critical readings

Abstract

In the present study, a system is developed to ensure an efficient and safe evacuation process in case of fire using modern threat detection and evacuation route optimization technologies. During the research, algorithms for analysing data from gas sensors, algorithms for optimizing evacuation routes based on graph theory, and software for integration with an Arduino microcontroller and real-time processing of the obtained data were developed and used. The research resulted in the development of an intelligent fire safety system based on Arduino microcontroller and MQ series gas sensors for early fire detection. The application of graph algorithms allowed determining the optimal evacuation paths, taking into account the building parameters and distribution of people. The system has shown high efficiency in calculating optimal evacuation routes, minimizing risks in emergency situations. It was revealed that the system's integration with mobile applications and other smart city components has the potential to expand functionality and improve emergency coordination.

Author Biographies

Akyltai Burgegulov, Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
Department of Artificial Intelligence and Big Data
Talgat Mazakov, Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
Department of Artificial Intelligence and Big Data
Gulzat Ziyatbekova, Department of Information Systems, Al-Farabi Kazakh National University, Republic of Kazakhstan
Department of Information Systems
Sholpan Jomartova, Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
Department of Artificial Intelligence and Big Data
Aigerim Mazakova, Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Republic of Kazakhstan
Department of Artificial Intelligence and Big Data
Published
2026-01-20
How to Cite
Burgegulov, A., Mazakov, T., Ziyatbekova, G., Jomartova, S., & Mazakova, A. (2026). Integrated system for early fire detection and evacuation based on Arduino. Statistics, Optimization & Information Computing, 15(4), 2781-2795. https://doi.org/10.19139/soic-2310-5070-3087
Issue
Vol 15 No 4 (2026)
Section
Research Articles
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