A Design and Development of the Smoke Detection System Using Infra-red Laser for Fire Detection in the Wide Space

Nowadays, ship’s engine room is fire protected by automatic fire fighting systems, usually controlled from a place located outside the engine room. In order to activate the water mist extinguishing system automatically, at least two different fire detectors have to be activated. One of these detectors is a flame detector that is not hampered by various air flows caused by ventilation or draft and is rapidly activated and the other is smoke detector which is hampered by these flows causing its activation to be delayed. As a consequence, the automatic water mist extinguishing system is also delayed, allowing for fire expansion and its transfer to surrounding rooms. In addition to reliability of the ship’s fire detection system as one of the crucial safety features for the ship, cargo, crew and passengers, using a systematic approach in this research the emphasis is placed on the application of new methods in smoke detection such as the computer image processing and analysis, in order to achieve this goal. This paper describes the research carried out on board ship using the existing marine CCTV systems in early stages of smoke detection inside ship’s engine room, which could be seen as a significant contribution to accelerated suppression of unwanted consequences.

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IEEE 1451-Based Sensor Interfacing and Data Fusion for Fire Smoke Detection

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.613.219 ◽

2014 ◽

Vol 613 ◽

pp. 219-227

Author(s):

Chao Ching Ho ◽

Dan Wen Kuo

Keyword(s):

Video Processing ◽

Detection System ◽

Fire Detection ◽

Sensor System ◽

Sensor Data ◽

Smoke Detection ◽

Fire Smoke ◽

Ieee 1451 ◽

Smart Transducer ◽

Transducer Interface

The performance of a fire sensor has a significant effect on fire detection. Today’s fire alarm systems, such as smoke and heat sensors, however are generally limited to a close proximity to the fire; and cannot provide additional information about fire circumstances. Thus, it is essential to design a suite of low-cost networked sensors that provide the capability of performing distributed measurement and control in real time. In this work, a wireless sensor system was developed for fire detection. The purpose of this paper is to analyze the integration of traditional fire sensors into intelligent fire management systems by using the smart transducer concept. An automated video processing sensor for fire smoke monitoring applications is integrated into an surveillance network as a case study and supported sensor fusion assessment to improve the resistance to nuisance alarms. The proposed sensor system for fire detection was developed to reconcile issues related to proliferation and interoperability, and the architecture can support a smart transducer interface (IEEE 1451). The proposed embedded system for STIM (smart transducer interface module) and NCAP (network capable application processor) will be implemented with DSP. To realize the self-identification of transducers and plug-and-play connections, a transducer electronic data sheet (TEDS) is also stored inside the DSP. The acquired sensor data are pre-processed and applied to discriminate nuisance sources. The IEEE 1451 standard has been integrated into an automatic video-based fire smoke detection system. The proposed architecture has been tested on an experimental setup with the purpose of monitoring fire incidents successfully.

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Simulation Study on the Aspirating Smoke Detection System in Large Space Buildings

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.255-260.1404 ◽

2011 ◽

Vol 255-260 ◽

pp. 1404-1408 ◽

Cited By ~ 1

Author(s):

Zhen Na Zhang ◽

Hong Bing Chen

Keyword(s):

Simulation Study ◽

Detection System ◽

Early Stage ◽

Side Wall ◽

Fire Detection ◽

Smoke Detection ◽

Large Space ◽

Pipe Length ◽

Response Performance ◽

Fire Location

The aspirating smoke detection (ASD) system has been widely used in large space buildings. It plays an important role on fire detection at its early stage. In this paper, the model of large space building was established for the simulation study on the response performance of the ASD system. The investigation on the effect of fire location, sampling hole space and pipe length on the responding time, was carried out. The results showed that the responding time of FIRE B (fire close to side wall) is much delayed than that of FIRE A (fire in centre); the increase of sampling hole space and pipe length leads to the delay of the responding time.

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REAL-TIME FIRE AND SMOKE DETECTION USING CAMERA SEQUENCE IMAGE IN TUNNEL ENVIRONMENT

International Journal of Information Acquisition ◽

10.1142/s0219878907001393 ◽

2007 ◽

Vol 04 (04) ◽

pp. 327-338 ◽

Cited By ~ 2

Author(s):

BYOUNGMOO LEE ◽

DONGIL HAN

Keyword(s):

Image Processing ◽

Real Time ◽

Large Scale ◽

Detection System ◽

Fire Detection ◽

Processing Technique ◽

Image Processing Technique ◽

Smoke Detection ◽

Forest Environment ◽

Exact Position

In this paper, we proposed an image processing technique for automatic real time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurring in the tunnel, it is necessary to have a system to sense and minimize the incident as fast as possible. However it is impossible for human observation of Closed-Circuit Television (CCTV) in tunnel for 24 h. So if the fire and smoke detection system through image processing can warn a fire, it will be very convenient, and it can be possible to minimize damage even when no one is in front of the monitor. The fire and smoke detection is different from forest fire detection as there are elements such as car and tunnel lights and others that are different from the forest environment so an indigenous algorithm has to be developed. The two algorithms proposed in this paper are able to detect the exact position at the earlier stage of incident. In addition, by comparing properties of each algorithm throughout experiment, we have proved the validity and efficiency of proposed algorithm.

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Realization of People Density and Smoke Flow in Buildings during Fire Accidents Using Raspberry and OpenCV

Sustainability ◽

10.3390/su131911082 ◽

2021 ◽

Vol 13 (19) ◽

pp. 11082

Author(s):

Gajanand S. Birajdar ◽

Mohammed Baz ◽

Rajesh Singh ◽

Mamoon Rashid ◽

Anita Gehlot ◽

...

Keyword(s):

Real Time ◽

Web Application ◽

Detection System ◽

Human Life ◽

Fire Detection ◽

Smoke Detection ◽

Urban Buildings ◽

System A ◽

Fire Detection System ◽

Fire Accidents

Fire accidents in residential, commercial, and industrial environments are a major concern since they cause considerable infrastructure and human life damage. On other hand, the risk of fires is growing in conjunction with the growth of urban buildings. The existing techniques for detecting fire through smoke sensors are difficult in large regions. Furthermore, during fire accidents, the visibility of the evacuation path is occupied with smoke and, thus, causes challenges for people evacuating individuals from the building. To overcome this challenge, we have recommended a vision-based fire detection system. A vision-based fire detection system is implemented to identify fire events as well as to count the number people inside the building. In this study, deep neural network (DNN) models, i.e., MobileNet SSD and ResNet101, are embedded in the vision node along with the Kinect sensor in order to detect fire accidents and further count the number of people inside the building. A web application is developed and integrated with the vision node through a local server for visualizing the real-time events in the building related to the fire and people counting. Finally, a real-time experiment is performed to check the accuracy of the proposed system for smoke detection and people density.

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