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Making Pier Data Broader and Deeper:

PDR Challenge and Virtual Mapping Party

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 240)

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.

Keywords

  • Lab-forming fields
  • Field-forming labs
  • Big data
  • Deep data
  • Pier data
  • PDR
  • IoT
  • IoH
  • VR
  • Service engineering

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Acknowledgment

The PDR Challenge in Warehouse Picking was carried out partially with the support of JST OPERA’s “Elucidation of the Mechanism of Cooperation Between Humans and Intelligent Machines and the Creation of Fundamental Technology to Build a New Social System Based on Cooperative Value.” The virtual mapping party was carried out with the support of JST RISTEX’s “Development of a Movement Support System for Visually Impaired People by Multi-Generation Co-Creation.”

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Kurata, T., Ichikari, R., Shimomura, R., Kaji, K., Okuma, T., Kourogi, M. (2018). Making Pier Data Broader and Deeper:. In: Murao, K., Ohmura, R., Inoue, S., Gotoh, Y. (eds) Mobile Computing, Applications, and Services. MobiCASE 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-90740-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-90740-6_1

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