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Article

AdViSED: Advanced Video SmokE Detection for Real-Time Measurements in Antifire Indoor and Outdoor Systems

Department of Information Engineering, University of Pisa, Via G. Caruso 16, 56127 Pisa, Italy
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Author to whom correspondence should be addressed.
Energies 2020, 13(8), 2098; https://doi.org/10.3390/en13082098
Received: 16 March 2020 / Revised: 14 April 2020 / Accepted: 20 April 2020 / Published: 23 April 2020
This paper proposes a video-based smoke detection technique for early warning in antifire surveillance systems. The algorithm is developed to detect the smoke behavior in a restricted video surveillance environment, both indoor (e.g., railway carriage, bus wagon, industrial plant, or home/office) or outdoor (e.g., storage area or parking area). The proposed technique exploits a Kalman estimator, color analysis, image segmentation, blob labeling, geometrical features analysis, and M of N decisor, in order to extract an alarm signal within a strict real-time deadline. This new technique requires just a few seconds to detect fire smoke, and it is 15 times faster compared to the requirements of fire-alarm standards for industrial or transport systems, e.g., the EN50155 standard for onboard train fire-alarm systems. Indeed, the EN50155 considers a response time of at least 60 s for onboard systems. The proposed technique has been tested and compared with state-of-art systems using the open access Firesense dataset developed as an output of a European FP7 project, including several fire/smoke indoor and outdoor scenes. There is an improvement of all the detection metrics (recall, accuracy, F1 score, precision, etc.) when comparing Advanced Video SmokE Detection (AdViSED) with other video-based antifire works recently proposed in literature. The proposed technique is flexible in terms of input camera type and frame size and rate and has been implemented on a low-cost embedded platform to develop a distributed antifire system accessible via web browser. View Full-Text
Keywords: IoT (Internet of Things); distributed smoke/fire alarm systems; embedded video processing; Kalman filter; industrial antifire system; mobility antifire system IoT (Internet of Things); distributed smoke/fire alarm systems; embedded video processing; Kalman filter; industrial antifire system; mobility antifire system
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MDPI and ACS Style

Gagliardi, A.; Saponara, S. AdViSED: Advanced Video SmokE Detection for Real-Time Measurements in Antifire Indoor and Outdoor Systems. Energies 2020, 13, 2098. https://doi.org/10.3390/en13082098

AMA Style

Gagliardi A, Saponara S. AdViSED: Advanced Video SmokE Detection for Real-Time Measurements in Antifire Indoor and Outdoor Systems. Energies. 2020; 13(8):2098. https://doi.org/10.3390/en13082098

Chicago/Turabian Style

Gagliardi, Alessio, and Sergio Saponara. 2020. "AdViSED: Advanced Video SmokE Detection for Real-Time Measurements in Antifire Indoor and Outdoor Systems" Energies 13, no. 8: 2098. https://doi.org/10.3390/en13082098

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