초록

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Abstract ▼ AI-Helper

We introduce a system that detects smoking in a specific area. The proposed system is implemented on a wireless ad hoc network consisting of Raspberry Pi boards. It is more economical owing to low-cost device than commercial smoking monitoring system and is scalable than the existing system with sin...

We introduce a system that detects smoking in a specific area. The proposed system is implemented on a wireless ad hoc network consisting of Raspberry Pi boards. It is more economical owing to low-cost device than commercial smoking monitoring system and is scalable than the existing system with single Raspberry Pi. In this paper, the probability density function of carbon monoxide concentration during smoking and non-smoking is approximated as Gauusian distribution, respectively, using data measured from sensors for a long time. Based on this, a maximum likelihood detection technique is adopted to estimate the smoking status by observing the concentration of carbon monoxide. We aim at improving the reliability by estimating the smoking status using the collected values from multiple sensors connected to the ad hoc network.