Search results for "Fire detection"
showing 5 items of 5 documents
Infrared image processing and its application to forest fire surveillance
2007
This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…
Misfire Detection System based on the Measure of Crankshaft Angular Velocity
2007
Misfire detection systems are becoming increasingly important in automotive market due to recent environmental issues (Euro rules). An early misfire diagnosis also allows to prevent damages to the exhaust emission system and consequent costs for the user. Today few low cost methods exists in order to precisely detect single misfires in real time, the majority in fact require the use of expensive sensors (e.g. pressure sensors) or dedicated circuits (e.g. ionization current sensing). This work describes a method and electronic system capable of detecting misfires with good accuracy, using parameters such as the speed sensor signal, already available in commercial engines. The proposed method…
Naive Bayes classier-based fire detection using smartphone sensors
2014
Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 For many years, smoke detectors have been used as the most crucial _re detection sensors.Although smoke detectors do their job very well, they are not perfect and may causefalse or late alarms. This is because they only rely on one of the _re signs which is smoke.Fire has many other signs as well such as heat and light. It also a_ects its environmentalparameters such as temperature and humidity. But typically, buildings are not equippedwith sensors capable of sensing these changes. Recently, a few smartphone manufacturershave added temperature, humidity, and barometer sensors to their products which c…
Deep Convolutional Neural Networks for Fire Detection in Images
2017
Detecting fire in images using image processing and computer vision techniques has gained a lot of attention from researchers during the past few years. Indeed, with sufficient accuracy, such systems may outperform traditional fire detection equipment. One of the most promising techniques used in this area is Convolutional Neural Networks (CNNs). However, the previous research on fire detection with CNNs has only been evaluated on balanced datasets, which may give misleading information on real-world performance, where fire is a rare event. Actually, as demonstrated in this paper, it turns out that a traditional CNN performs relatively poorly when evaluated on the more realistically balance…
Machine learning in remote sensing data processing
2009
Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.