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Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living | IEEE Conference Publication | IEEE Xplore
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Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living


Abstract:

Recently, ambient assisted living technologies have emerged to improve the quality of life of ageing populations. Identification of health-endangering indoor gases with a...Show More

Abstract:

Recently, ambient assisted living technologies have emerged to improve the quality of life of ageing populations. Identification of health-endangering indoor gases with a hardware-friendly solution may provide an early warning of unhealthy living conditions. Electronic nose technology, using an array of non-selective gas sensors, is a potential candidate to achieve this objective, but state-of-the-art gas classifiers hinder the development of low-cost and compact solutions. In this paper, we introduce a very simple classifier that transforms the multi-gas identification problem into pair-wise binary classification problems. This classifier is based on the resultant sign of the difference between values of the sensors' features for all possible pairs of sensors in each binary classification problem. A classifier qualification metric is defined to evaluate its suitability with given data of the target gases. As a case study, experimental data of four health-endangering gases, namely, formaldehyde, carbon monoxide, nitrogen dioxide and sulfur dioxide, is acquired in the laboratory by developing an array of commercially available gas sensors fabricated by Figaro Inc. and FIS Inc. A classification accuracy of 94.56% is achieved in distinguishing the target gasses with our proposed classifier. This performance is comparable to that of computation intensive state-of-the-art gas classifiers despite our classifier's simple implementation.
Date of Conference: 03-05 October 2016
Date Added to IEEE Xplore: 24 November 2016
ISBN Information:
Conference Location: Edinburgh, UK

I. Introduction

Ambient assisted living (AAL) technologies are primarily developed to provide high-quality health care to ageing populations at an affordable cost. Smart homes are one of the main targets for these technologies because around 90% of elderly people prefer staying at home, meaning they spend more time in their homes than younger people [1] A smart home is defined as “a residential setting equipped with a set of advanced electronics, sensors and automated devices specifically designed for care delivery, remote monitoring, early detection of problems or emergency cases and promotion of residential safety and quality of life” [2], [3]. Different types of sensors, such as cameras, microphones, motion sensors, passive infrared motion sensors, radio frequency identification sensors, smart tiles, magnetic switches etc., are deployed in such homes, and information collected from these sensors is analyzed to monitor the health of residents and provide them increased comfort [4].

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References

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