Abstract
Rapid proliferation of mobile devices with various sensors have enabled
Participatory Mobile Sensing (PMS). Several PMS platforms provide multiple
functions for various sensing purposes, but they are suffering from the open
issues: limited use of their functions for a specific scenario/case and
requiring technical knowledge for organizers. In this paper, we propose a novel
PMS platform named ParmoSense for easily and flexibly collecting urban
environmental information. To reduce the burden on both organizers and
participants, in ParmoSense, we employ two novel features: modularization of
functions and scenario-based PMS system description. For modularization, we
provide the essential PMS functions as modules which can be easily chosen and
combined for sensing in different scenarios. The scenario-based description
feature allows organizers to easily and quickly set up a new participatory
sensing instance and participants to easily install the corresponding scenario
and participate in the sensing. Moreover, ParmoSense provides GUI tools as well
for creating and distributing PMS system easily, editing and visualizing
collected data quickly. It also provides multiple functions for encouraging
participants' motivation for sustainable operation of the system. Through
performance comparison with existing PMS platforms, we confirmed ParmoSense
shows the best cost-performance in the perspective of the workload for
preparing PMS system and varieties of functions. In addition, to evaluate the
availability and usability of ParmoSense, we conducted 19 case studies, which
have different locations, scales, and purposes, over 4 years with cooperation
from ordinary citizens. Through the case studies and the questionnaire survey
for participants and organizers, we confirmed that ParmoSense can be easily
operated and participated by ordinary citizens including non-technical persons.
Translated title of the contribution | ParmoSense: A Scenario-based Participatory Mobile Urban Sensing Platform with User Motivation Engine |
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Original language | Undefined/Unknown |
Journal | CoRR |
Volume | abs/2102.05586 |
Publication status | Published - Feb 10 2021 |