CRII: CSR: RUI: Mobility Coordination of the Crowds in Mobile Crowd Sensing Platforms

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Mobile Crowd Sensing (MCS) seeks to achieve sensing tasks by recruiting individuals who are already roaming in the target mobility field. A crowd-assisted system eliminates the need for a dedicated physical infrastructure, thereby reducing the cost of sensing. Moreover, the use of crowd-sourced resources as part of the system allows for the development of new smart services and applications that would not have been possible otherwise. If MCS participation is purely voluntary, task coverage may be unpredictable. However, with incentive, recruitment of human agents may be improved. This project seeks to coordinate the mobility of participating human agents, and to optimize incentives to achieve sensing goals. In this project, techniques from optimization theory and approximation algorithms will be used to optimize task allocation in a Coordinated-MCS platform while developing efficient routing. These mechanisms are coupled with incentive-compatible payment models to maximize agent participation. Moreover, a backend service will be developed to integrate these mechanisms within Coordinated MCS applications, to evaluate their performance on real crowd.Coordinated mobility depends on, and hence requires research in, two areas; the mechanisms via which tasks/routes are assigned to agents, and the mechanisms via which agents are compensated for conformance, creating a rich set of problems in the fields of optimization problems, graph and data mining, and crowd economics. This project contributes towards the advancement of mobile crowd sensing for solving larger problems, with a great impact on smart cities initiatives, and the advancement of Internet of Things solutions. Moreover, as Wellesley College is a women's college, this project contributes directly to increasing the participation of women in computer science, allowing multiple undergraduate female students to perform advanced research in the field. All code developed in this project and collected data will be stored on a private directory dedicated for the project on the Computer Science department server for the duration of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.