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Based on recent experimental discoveries about a link between the length of exposure to formaldehyde and cancers of the lymphatic and hematopoietic systems, we present a low-cost and compact solution for monitoring formaldehyde in the environment by using electronic nose technology. This solution is centered on an array of gas sensors and a regression method. It has the potential to be deployment...
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...
Finding a rapid gas identification algorithm with high accuracy and a closed-form solution that does not require any manual tuning of parameters is the major challenge to overcome in adopting electronic nose technology in daily life applications. Recently, bio-inspired rank-order-based classifiers have been proposed to meet this challenge by transforming multidimensional sensitivity vectors into temporally...
Motivated by the recent experimental findings about odor identification with the unique spiking patterns of neurons in the biological olfactory system, rank-order-based classifiers have been proposed for gas identification in electronic nose applications. These classifiers rely on one-to-one mapping between the target gas and the temporal sequence of spiking sensors in an electronic nose. However,...
Recently, implementation friendly bio-inspired coding schemes have been developed for an electronic nose system to recognise different gases. In these schemes, a logarithmic timedomain encoding technique is used to covert the response vector of the sensor array in an electronic nose into a latency pattern. These schemes assume a unique temporal sequence of latencies, referred to as a rank order, for...
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