Citation

AlOrabi WAR, Rahman SA, Barachi ME, Mourad A. Procedia Comput. Sci. 2016; 83: 345-352.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.procs.2016.04.135

PMID

unavailable

Abstract

With the increased need for mobility and the overcrowding of cities, the area of Intelligent Transportation aims at improving the efficiency, safety, and productivity of transportation systems by relying on communication and sensing technologies. One of the main challenges faced in Intelligent Transportation Systems (ITS) pertains to the real time collection of traffic and road related data, in a cost effective, efficient, and scalable manner. The current approaches still suffer from problems related to the energy consumption of mobile devices and overhead in terms of communications and processing. We have previously proposed the concept of Mobile Sensing as a Service (MSaaS), in which mobile owners can offer the sensing capabilities of their phones as services to other users. This ability to offer sensory data to consumers on demand can bring significant benefits to ITS and can constitute an efficient and flexible solution to the problem of real-time traffic/road data collection. In this paper, we adapt the concept of MSaaS to the area of transportation, and present an on-demand vehicular sensing framework. This framework enables a data consumer to send a sensing trigger request to a vehicular sensing platform, which matches it with the most suitable set of data collectors that would perform the sensing task, and return the data to the platform for validation and processing. The collected data is then used to infer intelligence about the city and send the required traffic information to the data consumer, in a timely manner. The proposed model and architecture were validated using a combination of prototyping and traffic simulation traces, and the obtained results are very promising.

Language: en