Detection of human activities by inverse filtration of gas sensor response

In an approach to identifying human activities in an indoor space from the response signals of a combustible gas sensor, an indoor space model was presented in which the response signal and the gas generation due to the human activities were correlated linearly through an indoor gas transfer function. Analysis indicated that: (1) the gas transfer by diffusion can describe essential features of the transfer function in the indoor space, and (2) the inverse filtration based on the space transfer characteristics thus estimated enables one to restore or extract the gas-generation function from the sensor signal output. The model was applied to identify daily human activities in a domestic house. The sensor response output consisted of heavily overlapping signals due to human actions taking place in succession. However, the inverse filtration could eliminate the overlapping (residual) components from the overall output to single out each human action associated with causing gas generation in the indoor space.