Scalable urban mobile crowdsourcing: Handling uncertainty in worker movement

• Main Authors: CHENG, Shih-Fen, CHEN, Cen, KANDAPPU, Thivya, LAU, Hoong Chuin, MISRA, Archan, JAIMAN, Nikita, DARATAN, Randy Tandriansyah, KOH, Desmond
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: participatory sensing; Mobile crowdsourcing; uncertainty modeling; context-aware; empirical study; spatial crowdsourcing; user behavior; Artificial Intelligence and Robotics; Computer Sciences; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3888; https://ink.library.smu.edu.sg/context/sis_research/article/4890/viewcontent/ScalableUrbanMobileCrowd__tist_final_web.pdf
• Institution: Singapore Management University

In this article, we investigate effective ways of utilizing crowdworkers in providing various urban services. The task recommendation platform that we design can match tasks to crowdworkers based on workers’ historical trajectories and time budget limits, thus making recommendations personal and eff...