Any sensor to detect a certain physical variable is influenced to some degree by other physical variables designated as "noise". The objective in conventional sensor design is to minimize such noise. In this study, conversely we welcome sensing devices that are easily influenced by many physical variables and make full use of their multi-sensing characteristic. We consider such devices as multiple-inputs and single-output sensors. The output signal derived from multiple input signals must be dissociated. The input signals resulting from physical realities have inherent characteristics and can be mathematically modeled. Application of a Kalman filter realized by such models can provide estimates of state variables of all input models, and thus the input signals can be dissociated. As an example, a novel sensor based on a microphone is presented. It 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 use the sensor to monitor the symptoms of fire, earthquake and break-in by intruders from within a house.