Performance Evaluation Of Mobile Crowdsensing For Event Detection

Crowdsensing offers a cost effective way to collect large amounts of sensor data. However, in contrast to fixed sensor deployments, the spatial distribution of the sensors can hardly be influence, as the sensors are carried by participants of the crowdsensing system. This in turn raises the question about the performance of such systems with respect to the detection probability and detection time of spatial events. In order to address this question, we analyze the performance of such a crowdsensing system by means of simulation. We use the traffic infrastructure of a small size city in Germany and simulate the inhabitants' movement patterns with the well established SUMO mobility generator. Our results show that even if only a small share of inhabitants participates in crowdsensing, events, which have locations that are correlated with the population density, can be easily and quickly detected using such a system. On the contrary, events whose locations are uniformly randomly distributed are much harder to detect using a crowdsensing approach.