[2603.24850] Towards automatic smoke detector inspection: Recognition of the smoke detectors in industrial facilities and preparation for future drone integration

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.24850 (cs) [Submitted on 25 Mar 2026] Title:Towards automatic smoke detector inspection: Recognition of the smoke detectors in industrial facilities and preparation for future drone integration Authors:Lukas Kratochvila, Jakub Stefansky, Simon Bilik, Robert Rous, Tomas Zemcik, Michal Wolny, Frantisek Rusnak, Ondrej Cech, Karel Horak View a PDF of the paper titled Towards automatic smoke detector inspection: Recognition of the smoke detectors in industrial facilities and preparation for future drone integration, by Lukas Kratochvila and 8 other authors View PDF HTML (experimental) Abstract:Fire safety consists of a complex pipeline, and it is a very important topic of concern. One of its frontal parts are the smoke detectors, which are supposed to provide an alarm prior to a massive fire appears. As they are often difficult to reach due to high ceilings or problematic locations, an automatic inspection system would be very beneficial as it could allow faster revisions, prevent workers from dangerous work in heights, and make the whole process cheaper. In this study, we present the smoke detector recognition part of the automatic inspection system, which could easily be integrated to the drone system. As part of our research, we compare two popular convolutional-based object detectors YOLOv11 and SSD widely used on embedded devices together with the state-of-the-art transformer-based RT-DETRv2 with the bac...