Reducing False Alarms in Buildings with UAV-Based Fire Detection and Monitoring through a Cloud-Integrated Approach

DOI

10.2991/978-94-6463-884-4_15How to use a DOI?

Keywords

UAV; Fire Detection System; Cloud Computing; IoT; Computer Vision

Abstract

Fire is a formidable force of nature, and its effects range from loss of life and property damage to severe disruptions to economic and social systems. However, conventional fire detection systems often trigger false alarms, disrupt emergency responses, and result in operational inefficiency. A growing proportion of reported fire alarms are false, and current regulations focus primarily on imposing penalties for false reports, with limited provisions addressing other aspects. For instance, the study showed unwanted automatic fire alarm (AFA) activations annually, constituting approximately 97% of all call-outs. This study introduces a novel fire detection and monitoring framework integrating IoT-enabled smoke detectors with cloud computing platforms. The system utilizes a UAV to capture real-time data along optimized flight paths. Upon smoke detector activation, the UAV launches and focuses on the affected area, transmitting real-time data to a cloud-based platform for thermal-image analysis. Cloud computing models validate fire events using computer vision algorithms to cross-reference smoke motion, smoke density recognition, and fire classification data, thereby significantly reducing false alarms. This information is transmitted to emergency responders and building management systems to provide real-time visuals, actionable insights, and evacuation guidance. The system also facilitates post-event evaluation through extensive data collection and storage. Through repeated exposure to fire incidents, drones undergo an iterative learning process, gradually refining their operational capabilities. To effectively execute missions and meet performance criteria, efforts have been made to reduce false alarm rates and enhance the probability of successful detection. This approach highlights the integration of UAVs with cloud technologies to improve fire safety in modern buildings, resulting in detection accuracy and emergency response efficiency.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, 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 changes were made.

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TY  - CONF
AU  - Estiak Ahmed
AU  - Alinda Bhattacharjee
AU  - Afia Anzum
PY  - 2025
DA  - 2025/11/18
TI  - Reducing False Alarms in Buildings with UAV-Based Fire Detection and Monitoring through a Cloud-Integrated Approach
BT  - Proceedings of the 8th International Conference on Engineering Research, Innovation, and Education 2025 (ICERIE 2025)
PB  - Atlantis Press
SP  - 120
EP  - 127
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-884-4_15
DO  - 10.2991/978-94-6463-884-4_15
ID  - Ahmed2025
ER  -