Semantically enriched spatial modelling of industrial indoor environments enabling location-based services

This paper presents a concept for a software system called RAIL representing industrial indoor environments in a dynamic spatial model, aimed at easing development and provision of location-based services. RAIL integrates data from different sensor modalities and additional contextual information through a unified interface. Approaches to environmental modelling from other domains are reviewed and analyzed for their suitability regarding the requirements for our target domains; intralogistics and production. Subsequently a novel way of modelling data representing indoor space, and an architecture for the software system are proposed.

[1]  Cyril Ray,et al.  Spatial models for context-aware indoor navigation systems: A survey , 2012, J. Spatial Inf. Sci..

[2]  Yubin Xu,et al.  LBS based disaster and emergency management , 2010, 2010 18th International Conference on Geoinformatics.

[3]  Tully Foote,et al.  tf: The transform library , 2013, 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA).

[4]  Qing Zhu,et al.  Problems in indoor mapping and modelling , 2013 .

[5]  Upkar Varshney,et al.  Challenges and business models for mobile location-based services and advertising , 2011, Commun. ACM.

[6]  Umit Isikdag,et al.  A REVIEW OF RECENT RESEARCH IN INDOOR MODELLING & MAPPING , 2016 .

[7]  John Krogstie,et al.  Navigating MazeMap: Indoor human mobility, spatio-logical ties and future potential , 2014, 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS).

[8]  Stuart J. Barnes Location-Based Services: The State of the Art , 2004 .

[9]  Tobias Scherner,et al.  A Multilaterally Secure, Privacy-Friendly Location-Based Service for Disaster Management and Civil Protection , 2005, ICN.