Inspired by perception in biological systems,distribution of a massive amount of simple sensingdevices is gaining more support in detectionapplications. A focus on fusion of sensor signals insteadof strong analysis algorithms, and a scheme to distributesensors, results in new issues. Especially in wearablecomputing, where sensor data continuously changes, andclothing provides an ideal supporting structure forsimple sensors, this approach may prove to befavourable. Experiments with a body-distributed sensorsystem investigate the influence of two factors that affectclassification of what has been sensed: an increase insensors enhances recognition, while adding new classesor contexts depreciates the results. Finally, a wearablecomputing related scenario is discussed that exploits thepresence of many sensors.