Automatic Fire Detection: A Survey from Wireless Sensor Network Perspective

Automatic fire detection is important for early detection and promptly extinguishing fire. There are ample studies investigating the best sensor combinations and appropriate techniques for early fire detection. In the previous studies fire detection has either been considered as an application of a certain field (e.g., event detection for wireless sensor networks) or the main concern for which techniques have been specifically designed (e.g., fire detection using remote sensing techniques). These different approaches stem from different backgrounds of researchers dealing with fire, such as computer science, geography and earth observation, and fire safety. In this report we survey previous studies from three perspectives: (1) fire detection techniques for residential areas, (2) fire detection techniques for forests, and (3) contributions of sensor networks to early fire detection

Fire and memory: transforming place using fire at henge monuments

Henges — Late Neolithic to Early Bronze Age earthwork monuments — often have long life-histories of reuse and rebuilding over generations. At some sites, fire-lighting and the deposition of fire-altered materials played a significant role in certain phases of the use of the henge. This article reviews the evidence for fire in the life-histories of four henges in Scotland, and interprets the various ways in which fire was employed at different times and at different sites. It argues that fire had a transformational effect, not only upon monuments and materials, but it also characterized and transformed people’s experiences and memories of particular sites, thus creating links between monumental sites and quotidian experience during the Neolithic and Bronze Age in Scotland

Flame Detection for Video-based Early Fire Warning Systems and 3D Visualization of Fire Propagation

Early and accurate detection and localization of flame is an essential requirement of modern early fire warning systems. Video-based systems can be used for this purpose; however, flame detection remains a challenging issue due to the fact that many natural objects have similar characteristics with fire. In this paper, we present a new algorithm for video based flame detection, which employs various spatio-temporal features such as colour probability, contour irregularity, spatial energy, flickering and spatio-temporal energy. Various background subtraction algorithms are tested and comparative results in terms of computational efficiency and accuracy are presented. Experimental results with two classification methods show that the proposed methodology provides high fire detection rates with a reasonable false alarm ratio. Finally, a 3D visualization tool for the estimation of the fire propagation is outlined and simulation results are presented and discussed.The original article was published by ACTAPRESS and is available here: http://www.actapress.com/Content_of_Proceeding.aspx?proceedingid=73

Fire suppression in human-crew spacecraft

Fire extinguishment agents range from water and foam in early-design spacecraft (Halon 1301 in the present Shuttle) to carbon dioxide proposed for the Space Station Freedom. The major challenge to spacecraft fire extinguishment design and operations is from the micro-gravity environment, which minimizes natural convection and profoundly influences combustion and extinguishing agent effectiveness, dispersal, and post-fire cleanup. Discussed here are extinguishment in microgravity, fire-suppression problems anticipated in future spacecraft, and research needs and opportunities

Fire responses of bushland plants after the January 1994 wildfires in northern Sydney

In early January 1994 wildfires burned areas of bushland in northern Sydney (lat 33° 45’ S, long 151° 05’ E) in coastal south-eastern Australia. This paper reports observations of the fire responses for 828 species of bushland plants – 576 native species and 252 exotic species in the Lane Cove River and Narrabeen Lagoon catchment areas. Information recorded includes whether a species was killed by fire or resprouted post-fire, when seedlings were first observed following fire, and the times of first flowering and first fruiting (or spore production) after the fires. The estimated peaks of post-fire flowering or fruiting for a few species are given. It was not practicable to record data in all categories for all of the 828 species due to the logistical challenges involved in recording data across a large area of bushland, over a number of years. The data presented add to the growing body of knowledge on plant fire responses and will assist the management and conservation of bushland in the study areas, as well as the broader Sydney region

'Fire hardening' spear wood does slightly harden it, but makes it much weaker and more brittle

It is usually assumed that 'fire hardening' the tips of spears, as practised by hunter-gatherers and early Homo spp., makes them harder and better suited for hunting. This suggestion was tested by subjecting coppiced poles of hazel to a fire-hardening process and comparing their mechanical properties to those of naturally seasoned poles. A Shore D hardness test showed that fire treatment slightly increased the hardness of the wood, but flexural and impact tests showed that it reduced the strength and work of fracture by 30% and 36%, respectively. These results suggest that though potentially slightly sharper and more durable, fire-hardened tips would actually be more likely to break off when used, as may have been the case with the earliest known wooden tool, the Clacton spear. Fire might first have been used to help sharpen the tips of spears, and fire-hardening would have been a mostly negative side effect, not its primary purpose

Use of AI Techniques for Residential Fire Detection in Wireless Sensor Networks

Early residential fire detection is important for prompt extinguishing and reducing damages and life losses. To detect fire, one or a combination of sensors and a detection algorithm are needed. The sensors might be part of a wireless sensor network (WSN) or work independently. The previous research in the area of fire detection using WSN has paid little or no attention to investigate the optimal set of sensors as well as use of learning mechanisms and Artificial Intelligence (AI) techniques. They have only made some assumptions on what might be considered as appropriate sensor or an arbitrary AI technique has been used. By closing the gap between traditional fire detection techniques and modern wireless sensor network capabilities, in this paper we present a guideline on choosing the most optimal sensor combinations for accurate residential fire detection. Additionally, applicability of a feed forward neural network (FFNN) and Naïve Bayes Classifier is investigated and results in terms of detection rate and computational complexity are analyzed

The provision of fire services in rural areas

Fire services have been neglected in discussions of public service provision in rural areas. The way in which they are provided has a broader significance in terms of current debates about risk management. Fire service policy was transferred away from the Home Office, but the Bain Report provided the major stimulus to change. Early central government attempts to stimulate fire service provision in rural area were hampered by a lack of cooperation between local authorities. Rates of death from fire are influenced by attendance times and are particularly high in remote rural areas. The development of national standards of fire cover was focused on protecting property rather than saving lives with disproportionate funding being provided for urban areas. Social changes in rural areas have made it more difficult to secure sufficient numbers of retained fire fighters. It has proved particularly difficult to provide an adequate service in remote rural areas such as the Highlands and Islands of Scotland, despite recent policy initiatives there. Problems of providing fire cover are particularly acute on isolated islands. The development of integrated risk management plans should offer a more fine grained approach to providing fire cover. However, they may be too sophisticated for the task in rural areas and more traditional democratic mechanisms for expressing perceived community needs may have a greater relevance

Multi-sensor fire detection by fusing visual and non-visual flame features

This paper proposes a feature-based multi-sensor fire detector operating on ordinary video and long wave infrared (LWIR) thermal images. The detector automatically extracts hot objects from the thermal images by dynamic background subtraction and histogram-based segmentation. Analogously, moving objects are extracted from the ordinary video by intensity-based dynamic background subtraction. These hot and moving objects are then further analyzed using a set of flame features which focus on the distinctive geometric, temporal and spatial disorder characteristics of flame regions. By combining the probabilities of these fast retrievable visual and thermal features, we are able to detect the fire at an early stage. Experiments with video and LWIR sequences of lire and non-fire real case scenarios show good results in id indicate that multi-sensor fire analysis is very promising