TY - JOUR
T1 - A multivariable detection device based on a capacitive microphone and its application to security
AU - Watanabe, Kajiro
AU - Ishigaki, Tsukasa
AU - Higuchi, Tomoyuki
PY - 2010/7/1
Y1 - 2010/7/1
N2 - Any sensor for detecting a certain physical variable is more or less influenced by other physical variables, which are designated as noise. The objective in conventional sensor design has been to minimize the noise. In this paper, however, we make use of sensing devices that are easily influenced by multiple physical variables and make full use of their multisensing characteristic. We consider such devices as multiple-inputsingle-output sensors. First, the output signal derived from multiple input signals must be dissociated. The input signals resulting from physical phenomena have inherent characteristics and can mathematically be modeled. Application of a Kalman filter realized by such models can provide estimates of the state variables of all input models, and thus, the input signals are dissociated. As an example, a novel sensor based on a microphone is presented. This sensor can detect various variables such as pressure and acceleration in the frequency range of 0.1 Hz to 10 kHz, temperature, and even light emission. We apply the sensor to monitor the symptoms of fire, earthquake, and break-in by an intruder from within a house.
AB - Any sensor for detecting a certain physical variable is more or less influenced by other physical variables, which are designated as noise. The objective in conventional sensor design has been to minimize the noise. In this paper, however, we make use of sensing devices that are easily influenced by multiple physical variables and make full use of their multisensing characteristic. We consider such devices as multiple-inputsingle-output sensors. First, the output signal derived from multiple input signals must be dissociated. The input signals resulting from physical phenomena have inherent characteristics and can mathematically be modeled. Application of a Kalman filter realized by such models can provide estimates of the state variables of all input models, and thus, the input signals are dissociated. As an example, a novel sensor based on a microphone is presented. This sensor can detect various variables such as pressure and acceleration in the frequency range of 0.1 Hz to 10 kHz, temperature, and even light emission. We apply the sensor to monitor the symptoms of fire, earthquake, and break-in by an intruder from within a house.
KW - Disaster
KW - Kalman filter
KW - Multivariable
KW - Security
KW - Smart sensor
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U2 - 10.1109/TIM.2009.2030716
DO - 10.1109/TIM.2009.2030716
M3 - Article
AN - SCOPUS:77953248312
SN - 0018-9456
VL - 59
SP - 1955
EP - 1963
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
IS - 7
M1 - 5280362
ER -