Crowd-Based Smart Parking: A Case Study for Mobile Crowdsourcing

• Published in: Mobile Wireless Middleware, Operating Systems, and Applications pp. 16 - 30
• Main Authors: Chen, Xiao, Santos-Neto, Elizeu, Ripeanu, Matei
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: collaborative sensing; mobile crowdsourcing; smart parking
• ISBN: 9783642366598; 3642366597
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-642-36660-4_2

An increasing number of mobile applications aim to enable “smart cities” by harnessing contributions from citizens armed with mobile devices that have sensing ability. However, there are few generally recognized guidelines for developing and deploying crowdsourcing-based solutions in mobile environments. This paper considers the design of a crowdsourcing-based smart parking system as a specific case study in an attempt to explore the basic design principles applicable to an array of similar applications. Through simulations, we show that the strategies behind crowdsourcing can heavily influence the utility of such applications. Equally importantly, we show that tolerating a certain level of freeriding increases the social benefits while maintaining quality of service level offered. Our findings provide designers with a better understanding of mobile crowdsourcing features and help guide successful designs.