Smart Wireless Video Sensor Network for Fire Alarm

Li, Qiulin; Hao, Qun; Zhang, Kai

doi:10.1109/wicom.2010.5601145

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…Ultra Violet ([250, 390] nm), visible ([390, 750] nm), and NIR ([750, 1100] nm). Hot spots, fire or flames can be detected with a CMOS sensor with a NIR filter (Naoult et al 2007)0, 0 (Li et al 2010) (hot spots need to be above 350Cº). Smoke detection is possible too when employing NIR sources (e.g.…”

Section: Fire Detection In the Nir Bandmentioning

confidence: 99%

Fire detection with a frame-less vision sensor working in the NIR band

Leñero‐Bardallo¹,

Fernández-Berni²,

Rodríguez-Vázquez³

et al. 2014

Advances in Forest Fire Research

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This paper draws the attention of the community about the capabilities of an emerging generation of bio-inspired vision sensors to be used in fire detection systems. Their principle of operation will be described. Moreover experimental results showing the performance of an eventbased vision sensor will be provided. The sensor was intended to monitor flames activity without using optic filters. In this article, we will also extend this preliminary work and explore how its outputs can be processed to detect fire in the environment. IntroductionInfrared cameras can easily detect fire and hot spots. Unfortunately, they are expensive, difficult to handle, and fragile (Briz et al. 2003). For this reason, CMOS cameras are still preferred for some applications where it is not strictly necessary operating in the whole infrared band, (Cheon et al. 2009, Naoult et al. 2007, Bendiscio et al. 1998, Fernandez-Berni et al. 2012. Silicon can detect Near Infrared Radiation (NIR) within the band [700 1,100] nm. This property can be exploited to monitor flame and fire activity.Flames have a very characteristic oscillatory behavior. They flicker with certain frequency components that depend on their nature. The study of these frequency components is interesting for industrial processes and applications. Traditionally CMOS cameras with NIR filters have been employed (Yan et al. 2006). As an alternative to this traditional approach, recently we proposed an bio-inspired event-based system to monitor flame activity without using optic filters (Leñero-Bardallo et al. 2013). The idea behind this method was to compare the photocurrents of stacked photodiodes at different depths. The top one was more sensitive to shorter wavelengths and the bottom one was more sensitive to longer wavelengths, having a very good sensitivity within the NIR band. Just comparing the difference between their photocurrents, we were able to determine if the incident radiation was within the NIR band without optic filters. Moreover, we could process with a real-time algorithm the temporal variations of the NIR levels in the visual scene provoked by flames and compute their frequency components values. This paper studies how the prior work to monitor flame activity could be extended to detect fire in the environment and emit an alarm in case. We will show that the previously implemented algorithm outputs can be processed to detect fire with a low computational load. Up

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Section: Fire Detection In the Nir Bandmentioning

confidence: 99%

Fire detection with a frame-less vision sensor working in the NIR band

Leñero‐Bardallo¹,

Fernández-Berni²,

Rodríguez-Vázquez³

et al. 2014

Advances in Forest Fire Research

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show abstract

“…For instance, the system described in [4] performed the continuous monitoring of the waves along the coasts of Louisiana and the Mexican gulf, measuring the wave height, their period, the direction of propagation, the water level, and the direction and speed of the currents. Different kinds of nodes with wireless transmission capabilities can be used (e.g., [21], [25], [29]). …”

Section: B Environmental Datamentioning

confidence: 99%

Privacy and security in environmental monitoring systems

Vimercati

Livraga

Piuri

et al. 2012

2012 IEEE First AESS European Conference on Satellite Telecommunications (ESTEL)

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Abstract-There is today an increasing interest in environmental monitoring for a variety of specific applications, with great impact especially on natural resource management and preservation, economy, and people's life and health. Typical uses encompass, for example, Earth observation, meteorology, natural resource monitoring, agricultural and forest monitoring, pollution control, natural disaster observation and prediction, and critical infrastructure monitoring. While on one hand these systems play an important role in our society, on the other hand their adoption can raise a number of security and privacy concerns, representing a possible obstacle for the development of future environmental applications. In this paper, we analyze the security and privacy issues characterizing both the environmental monitoring infrastructures and the data collected and processed by them. We also provide an overview of possible countermeasures for diminishing the effects of these issues.

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“…Placing a NIR optical filter over them, they become NIR imagers. Hot spots, fire or flames can be detected with a CMOS sensor with a NIR filter [5], [8]. Regions whose temperature is above 350 • C can be identified [5].…”

Section: Introductionmentioning

confidence: 99%

On the Analysis and Detection of Flames With an Asynchronous Spiking Image Sensor

et al. 2018

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We have investigated the capabilities of a custom asynchronous spiking image sensor operating in the Near Infrared (NIR) band to study flame radiation emissions, monitor their transient activity, and detect their presence. Asynchronous sensors have inherent capabilities, i.e. good temporal resolution, high dynamic range, and low data redundancy. This makes them competitive against Infrared (IR) cameras and CMOS frame-based NIR imagers. In the article, we analyze, discuss and compare the experimental data measured with our sensor against results obtained with conventional devices. A set of measurements have been taken to study the flame emission levels and their transient variations. Moreover, a flame detection algorithm, adapted to our sensor asynchronous outputs, has been developed. Results show that asynchronous spiking sensors have an excellent potential for flame analysis and monitoring.

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Smart Wireless Video Sensor Network for Fire Alarm

Cited by 8 publications

References 4 publications

Fire detection with a frame-less vision sensor working in the NIR band

Fire detection with a frame-less vision sensor working in the NIR band

Privacy and security in environmental monitoring systems

On the Analysis and Detection of Flames With an Asynchronous Spiking Image Sensor

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