ETRI WEBZINE

A group of South Korean researchers has developed an intelligent fire detection technology that drastically reduces the false alarm incidents, which go off in the absence of a real fire (hereinafter “unwanted alarm¹⁾”), and is on the verge of commercializing it. This technology is expected to considerably reduce the social cost incurred from unwanted alarms.

Electronics and Telecommunications Research Institute (ETRI) announced the development of an AI sensor for unwanted alarm prevention that distinguishes between smoke caused by a fire and non-fire aerosol²⁾ particles by measuring particle light scattering characteristics, which varies by the wavelength of light.

For the existing photoelectric smoke detector, an infrared light source and a light-sensing photodiode³⁾ are placed in opposite directions inside the detector. When particles, such as smoke, enter the detector, the photodiode captures the scattered light⁴⁾ generated as the smoke hits the light source, and the alarm is activated if the scattered light exceeds a certain level.

However, aerosolized particles, such as dust and moisture, generated by routine cooking, cigarette smoke, etc. can flow into the detector, setting off an unwanted alarm, which is in turn triggered by photoelectric detectors that detect scattered light.

According to the National Fire Agency, the number of fire engine dispatches between 2021 and July 2022 was as many as 258,220, and 96.6% of them were due to alarm malfunctions.

Alternatively, the AI sensor for unwanted alarm prevention developed by ETRI measures the distinct scattering properties of each aerosol particle based on the different wavelengths of light, and thus can accurately determine a real fire outbreak.
1) Unwanted alarm: An alarm set off when a fire detection system is triggered by factors other than those resulting from a fire outbreak, such as heat, smoke and flame
2) Aerosol: Small particle in a solid or liquid state that is suspended mid-air
3) Photodiode: A semiconductor component that converts optical (light) signals to electrical signals
4) Scattered Light: Light that scatters in all directions after hitting a substance or particle, changing its direction of travel

Intelligent aspirating smoke detector research prototype (left, center), sensor module for particle scattering measurement (bottom right), fire intelligence learning model for distinguishing between a real fire and unwanted alarm (top right)

The ETRI researchers have built a database by projecting light of different wavelengths onto aerosol particles and measuring the scattering of each particle. Combining this with artificial intelligence (AI) technology, they have developed an AI sensor for unwanted alarm prevention that distinguishes whether a particular aerosol particle is caused by fire or not before deciding to activate a fire alarm.

ETRI plans to first apply the AI sensor for unwanted alarm prevention to the aspirating smoke detectors. The aspirating smoke detector works on a similar principle to that of a photoelectric detector by drawing in air with a fan and swiftly detecting smoke. Although it detects smoke faster than a photoelectric detector, it is prone to malfunction due to dust and moisture. Therefore, it is installed and used in limited spaces such as semiconductor clean rooms and server rooms.

In particular, most of the aspirating smoke detectors currently available on the market are expensive imported products. In addition, since they lack a feature to distinguish whether a fire outbreak occurs or not, if a domestic product equipped with this technology is released, it would be highly competitive in the domestic and foreign fire detector markets.

ETRI Director Kang Bok Lee of the Defense & Safety Intelligence Research Section explained, “After it is commercialized, this technology will significantly reduce the number of false alarms caused by non-fire incidents, thus reducing the cost of fire engine dispatches and wasteful use of firefighting resources that are estimated at KRW 20 billion annually.”

Based on the scattering spectrum measurement, this technology is also capable of applications in cosmetic, medical, environmental and other industrial fields. ETRI is currently in discussion with relevant companies for commercializing this technology.

The research was conducted through the “Smoke Particle Spectrum Analysis-based Intelligent Fire Detector Development” project undertaken as part of the “ETRI R&D Support Project” funded by the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP).

Kyu Won Han, Senior Researcher
Defense & Safety Intelligence Research Section
(Tel. 82-42-860-5688, wally.han@etri.re.kr)