@inproceedings{ieee_itsc_mimosense,
title = {MiMoSense: An Open Crowdsensing Platform for Micro-Mobility},
author = {Zengyi Han and Hong Duc Nguyen and Shunsuke Aoki and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://2021.ieee-itsc.org/},
doi = {10.1109/ITSC48978.2021.9564524},
year = {2021},
date = {2021-09-19},
booktitle = {2021 IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages = {1-6},
publisher = {IEEE},
abstract = {The use of micro-mobility (e.g., bicycle and scooter) and their data for urban sensing and rider assessment is becoming increasingly popular in research. However, different research topics require different sensor setups; no general data collecting tools for the micro-mobility makes the researcher who wishes to collect data has to build their own collecting system from scratch. To this end, we present MiMoSense, an open crowdsensing platform for micro-mobility. MiMoSense consists of two components: (1) MiMoSense server, which is set up on the cloud, and used to manage sensing studies and the collected data for research and sharing. (2) MiMoSense client, uses micro-mobility carrying various sensors and IoT devices to collect multiple kinds of data during traveling. As a reusable open-source software, MiMoSense shifts the researcher's focus from software development to sensing data analysis; it can help researchers quickly develop an extensible platform for collecting micro-mobility's raw sensing data and inferring traveling context. We have evaluated MiMoSense's battery consumption, message latency and discuss its use.},
keywords = {e-scooter, Micro-Mobility, Mobile Sensing Toolkit},
pubstate = {published},
tppubtype = {inproceedings}
}