This study presents a multi-sensor activity monitoring system designed to verify daily behaviours and detect physiological anomalies within a controlled home environment. Seven subjects participated in a scripted routine of Activities of Daily Living carried out in a home-like environment. Within the routine, different sensors capture physiological hydration levels and breathing rates of the participant as sensor events, to check whether the measurements were within normal levels. In addition, camera, contact, motion and pressure sensors are used to capture action triggered events within the routine. Sensor data is processed and translated into a time-ordered trace of events. A model is constructed to capture the layout of the controlled environment and the trace of events. Expected behaviours are specified as properties encoded in Linear Temporal Logic and model checking is used to assess whether the sensor-captured events align with these expectations. Through model checking, the captured behaviour can be verified against a set of logical formulae representing properties. The identified deviations from expected behaviours demonstrate the viable application of model checking in the verification of Activities of Daily Living. Cross-sensor data aggregation compensates for occasional sensor inaccuracy, ensuring reliability. The initial results support the system’s potential for use in behaviour and physiological monitoring of people living independently, where accurate and unobtrusive monitoring is crucial.