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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-input-single-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.