Yamanaka Takao

Gas sensors have been widely used for various applications, such as gas leak detection, fire alarm systems, and odor-sensing systems. A problem of the gas sensors has been the selectivity to a target gas: background gases interfere with the measurement of the target gas. In the human olfaction, sensitivity to background odors is decreased by adaptation to the odors. Recently, several bio-inspired signal-processing methods mimicking the adaptation mechanism have been proposed for improving the selectivity of the gas sensors. In this chapter, the studies on the bio-inspired background suppression methods are reviewed. Furthermore, a case study of the bio-inspired background suppression is introduced. In the case study, a perceptron neural network with anti-Hebbian learning was used for realizing the adaptation to the background gas, and was implemented into a digital circuit for real-time gas sensing.

The authors of this chapter study the odor reproduction system synchronously with a movie. The system is made up of an odor sensing system and an olfactory display. The fruit flavors were recorded with movies using a digital video camera and the odor sensing system. The results of the sensory tests showed that the odor information recorded using the proposed method is appropriate for the smell regeneration associated with the movie. Next, the authors propose a tele-olfaction system synchronous with visual information. The olfactory display system was placed remotely from the odor sensing system, and both of them were connected via Internet. In addition to the olfactory system, a Web camera captures image around the sniffing point and that image appears at the computer display connected to the olfactory display at remote site. Moreover, the mobile stage with its sniffing point and the Web camera remotely controlled by a user was introduced so that he/she could interactively approach a smelling object. The questionnaire survey at the exhibition revealed that a user can enjoy smell synchronous with movie in real time even if he/she stays at the remote site. © 2011, IGI Global.

In this study, a new method for suppressing the background odor effect is proposed. Since odor sensors response to background odors in addition to a target odor, it is difficult to detect the target odor information. In the conventional odor sensing systems, the effect of the background odors are compensated by subtracting the response to the background odors (the baseline response). Although this simple subtraction method is effective for constant background odors, it fails in the compensation for time-varying background odors. The proposed method for the background suppression is effective even for the time-varying background odors. © 2008 The Institute of Electrical Engineers of Japan.