Research Article
Making Pier Data Broader and Deeper:
@INPROCEEDINGS{10.1007/978-3-319-90740-6_1, author={Takeshi Kurata and Ryosuke Ichikari and Ryo Shimomura and Katsuhiko Kaji and Takashi Okuma and Masakatsu Kourogi}, title={Making Pier Data Broader and Deeper:}, proceedings={Mobile Computing, Applications, and Services. 9th International Conference, MobiCASE 2018, Osaka, Japan, February 28 -- March 2, 2018, Proceedings}, proceedings_a={MOBICASE}, year={2018}, month={5}, keywords={Lab-forming fields Field-forming labs Big data Deep data Pier data PDR IoT IoH VR Service engineering}, doi={10.1007/978-3-319-90740-6_1} }- Takeshi Kurata
Ryosuke Ichikari
Ryo Shimomura
Katsuhiko Kaji
Takashi Okuma
Masakatsu Kourogi
Year: 2018
Making Pier Data Broader and Deeper:
MOBICASE
Springer
DOI: 10.1007/978-3-319-90740-6_1
Abstract
Big data can be gathered on a daily basis, but it has issues on its quality and variety. On the other hand, deep data is obtained in some special conditions such as in a lab or in a field with edge-heavy devices. It compensates for the above issues of big data, and also it can be training data for machine learning. Just like a platform of pier supported by stakes, there is structure in which big data is supported by deep data. That is why we call the combination of big and deep data “pier data.” By making pier data broader and deeper, it becomes much easier to understand what is happening in the real world and also to realize Kaizen and innovation. We introduce two examples of activities on making pier data broader and deeper. First, we outline “PDR Challenge in Warehouse Picking”; a PDR (Pedestrian Dead Reckoning) performance competition which is very useful for gathering big data on behavior. Next, we discuss methodologies of how to gather and utilize pier data in “Virtual Mapping Party” which realizes map-content creation at any time and from anywhere to support navigation services for visually impaired individuals.
