pp. 3063-3091
S&M3023 Research Paper of Special Issue https://doi.org/10.18494/SAM3961 Published: August 2, 2022 ParmoSense: Scenario-based Participatory Mobile Urban Sensing Platform with User Motivation Engine [PDF] Yuki Matsuda, Shogo Kawanaka, Hirohiko Suwa, Yutaka Arakawa, and Keiichi Yasumoto (Received April 30, 2022; Accepted June 16, 2022) Keywords: civic computing, ubiquitous computing, mobile computing, participatory sensing, smart city, urban sensing, gamification, incentive mechanism
The rapid proliferation of mobile devices with various sensors has enabled participatory mobile sensing (PMS). Several PMS platforms suffer from open issues including the limited use of their functions to a specific scenario/case and the necessity of technical knowledge for organizers. This paper proposes a novel PMS platform named ParmoSense for easy and flexible data collection. To reduce the burden on both organizers and participants, we employ two novel features. First, essential PMS functions implemented as modules can be easily chosen and combined for sensing in different scenarios. Second, the scenario-based description feature allows organizers to easily and quickly prepare a new instance of PMS and enable people to easily participate in the sensing. It also provides multiple functions to motivate participants for sustainable operation. Through a performance comparison with existing PMS platforms, we confirmed that ParmoSense shows the best cost performance in terms of the workload for preparation and the variety of functions. In addition, to evaluate the availability and usability of ParmoSense, we conducted 19 case studies over four years with ordinary citizens. As the result of a questionnaire survey carried out during the case studies, we confirmed that ParmoSense can be easily operated by ordinary citizens without technical skills.
Corresponding author: Yuki MatsudaThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Yuki Matsuda, Shogo Kawanaka, Hirohiko Suwa, Yutaka Arakawa, and Keiichi Yasumoto, ParmoSense: Scenario-based Participatory Mobile Urban Sensing Platform with User Motivation Engine, Sens. Mater., Vol. 34, No. 8, 2022, p. 3063-3091. |