Beacon-based context-aware architecture for crowd sensing public transportation scheduling and user habits

Crowd sourcing and sensing are relatively recent paradigms that, enabled by the pervasiveness of mobile devices, allow users to transparently contribute in complex problem solving. Their effectiveness depends on people voluntarism, and this could limit their adoption. Recent technologies for automating context-awareness could give a significant impulse to spread crowdsourcing paradigms. In this paper, we propose a distributed software system that exploits mobile devices to improve public transportation efficiency. It takes advantage of the large number of deployed personal mobile devices and uses them as both mule sensors, in cooperation with beacon technology for geofecing, and clients for getting information about bus positions and estimated arrival times. The paper discusses the prototype architecture, its basic application for getting dynamic bus information, and the long-term scope in supporting transportation companies and municipalities, reducing costs, improving bus lines, urban mobility and planning.