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

Alessio Gagliardi,Sergio Saponara

doi:10.3390/en13082098

Abstract

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.

Highlights

Recent reports of the NFPA (National Fire Protection Association) show that the average number of fires per year is about 1.3 million in the US alone, with a high cost in terms of lives and economic losses—the cost for fire losses is estimated to be about 55 billionUS Dollars (USD) per year [1]
There is an improvement of all the detection metrics when comparing Advanced Video SmokE Detection (AdViSED) with other video-based antifire works recently proposed in literature
The video signal is a wide monitor of the area under investigation and often closed-circuit television (CCTV) systems for surveillance purpose are already installed in smart buildings, in public places in smart cities, or onboard passenger vehicles of public transport systems

Summary

Introduction

Recent reports of the NFPA (National Fire Protection Association) show that the average number of fires per year is about 1.3 million in the US alone, with a high cost in terms of lives (more than 3000 civilian fire fatalities) and economic losses—the cost for fire losses is estimated to be about 55 billionUS Dollars (USD) per year [1]. Recent reports of the NFPA (National Fire Protection Association) show that the average number of fires per year is about 1.3 million in the US alone, with a high cost in terms of lives (more than 3000 civilian fire fatalities) and economic losses—the cost for fire losses is estimated to be about 55 billion. With the advent of the Internet of Things (IoT) and the growing interest about safety in public places, an early fire-smoke detection system should be implemented for the benefit of all citizens. To this end, a video-based approach based on the recognition of fire smoke is a promising method.

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