Cloud-Assisted Mobile Crowd Sensing for Traffic Congestion Control

With the development of mobile cloud computing, wireless communication techniques, intelligent mobile terminals, and data mining techniques, Mobile Crowd Sensing (MCS) as a new paradigm of the Internet of Things can be used in traffic congestion control to provide more convenient services and alleviate the traffic problems. In this paper, we propose a cloud-assisted MCS architecture for urban transportation system. Then, we make the case for cloud-assisted MCS traffic congestion control by sensing data obtained continuously from a large set of smartphones carried by drivers. In this case, we consider a Mechanism of more Contributions and more Feedback Services (MCFS) to recruit, engage, and retain the participants. Finally, we pay close attention to the issues and challenges, including system architecture, resource limitations, and security and privacy.