Smart e‐bike monitoring system: real‐time open source and open hardware GPS assistance and sensor data for electrically‐assisted bicycles. Issue 2 (1st March 2016)

• Record Type: Journal Article
• Authors: Kiefer, Chris; Behrendt, Frauke
• Is Part Of: IET intelligent transport systems. Volume 10:Issue 2(2016)
• Page Start: 79
• Page End: 88
• Publication Date: 2016-03-01
• Subjects: motorcycles -- computerised monitoring -- data acquisition -- condition monitoring -- data analysis -- public domain software -- Global Positioning System -- source code (software) -- electric vehicles -- power engineering computing; smart e‐bike monitoring system -- real‐time usage data acquisition -- electrically assisted bike -- rider control data -- location monitoring -- custom sensor input -- SEMS -- online interface -- data analysis -- social media -- source code -- general public license -- networked fleet -- real‐time open source -- open hardware global positioning system; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2014.0251
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : The smart e‐bike monitoring system (SEMS) is a platform for the real‐time acquisition of usage data from electrically‐assisted bikes (also called pedelecs or e‐bikes). It is autonomous (runs off the bike battery), replicable (open source and open hardware), scalable (different fleet sizes) and modular (sensors can be added), so it can be used for further research and development. The system monitors location (global positioning system), rider control data (level of assistance) and other custom sensor input in real time. The SEMS data feeds an online interface for data analysis, for riders to view their own data and for sharing on social media. The basic system can be replicated by other researchers and can be extended with modules to explore various issues in e‐bike research. The source code and hardware design are publicly available, under the General Public License, for non‐commercial use. SEMS was implemented on 30 bikes and collected data during 10 months of real‐word trials in the UK. This study details the design and implementation of the hardware and software, discusses the system use and explores features for future design iterations. The SEMS turns singular e‐bikes into a networked fleet and is an example of the internet of things in the cycling context.