Integrated System for Early Fire Detection and Evacuation Based on Arduino
Burgegulov A. Mazakov T. Ziyatbekova G. Jomartova S. Mazakova A.
16 March 2026International Academic Press
Statistics, Optimization and Information Computing
2026#15Issue 42781 - 2795 pp.
The research relevance is determined by the need to create reliable and adaptive fire protection systems capable of quick response to threats and provision of safe evacuation in real time. The study aimed to develop and test an integrated system for early fire detection and safe evacuation based on Arduino with an adaptive route control algorithm. The research methodology consisted of creating an integrated Arduino-based early fire detection and evacuation management system with MQ gas sensors, actuators, and a server data processor, where the Dijkstra algorithm provided dynamic route updates, and the effectiveness of the system was evaluated through testing in simulated scenarios. The study confirmed that calibrated MQ series sensors, combined with signal filtering, provide reliable detection of hazardous gas concentrations and reduce the probability of false alarms, forming a sufficient information base for early detection of fire risks. The adaptive evacuation algorithm effectively responds to dynamic changes in the situation by correcting the building graph and promptly re-planning routes without critical time losses. The warning system demonstrates high consistency with the analytical module: sound and light signals are activated in a timely manner and correctly reflect the current safe routes, reducing the risk of disorientation. Centralised server processing and data visualisation provide comprehensive monitoring in near real time, supporting event analysis and system scaling. Overall, the proposed approach improves response speed, evacuation reliability and the practical suitability of the system for use in real emergencies. The results of the study can be used by fire safety system developers, automation engineers, building and engineering system designers, managers of enterprises and institutions responsible for personnel safety, as well as for scientists researching the integration of IoT and optimisation algorithms in early emergency detection systems. Copyright
Building Safety , Critical Readings , Gas Sensors , Graph Algorithms , Smart City
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Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Kazakhstan
Department of Information Systems, Al-Farabi Kazakh National University, Kazakhstan
Department of Artificial Intelligence and Big Data
Department of Information Systems
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Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026