Beyond Where to How: A Machine Learning Approach for Sensing Mobility Contexts Using Smartphone Sensors
Abstract
This paper presents the results of research on the use of smartphone sensors (namely, GPS and accelerometers), geospatial information (points of interest, such as bus stops and train stations) and machine learning (ML) to sense mobility contexts. Our goal is to develop techniques to continuously and automatically detect a smartphone user's mobility activities, including walking, running, driving and using a bus or train, in real-time or...
Paper Details
Title
Beyond Where to How: A Machine Learning Approach for Sensing Mobility Contexts Using Smartphone Sensors
Published Date
Apr 28, 2015
Journal
Volume
15
Issue
5
Pages
9962 - 9985
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History