Data Management Foundations for Indoor LBS

The purpose of the project is to create a prototype indoor data management system with general, systematic, and solid data management foundations upon which indoor location-based services (LBS) can be built to provide location-dependent information efficiently and effectively to users in a broad range of indoor scenarios.

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indoor LBS has yet to be widely available in practice

A fundamental reason for the gap is that indoor data management is still in its infancy. The recent trend of pervasive instrumentation is improving indoor positioning and accumulating large amounts of real data, which inspires research and applications on indoor data management and enables us to evaluate relevant innovations in real settings—an opportunity for research that we have never had before.

See our efforts!

The Team Members

Hua Lu (PI)

Professor of Computer Science in the Department of People and Technology, Roskilde University.

Huan Li

Assistant Professor in the Department of Computer Science, Aalborg University.

Harry Kai-Ho Chan

Postdoc Researcher in the Department of People and Technology, Roskilde University.

Tiantian Liu

PhD student in the Department of Computer Science, Aalborg University.

Xiao Li

PhD student in the Department of People and Technology, Roskilde University.

Subproject
Indoor Spatial Queries: Modeling, Indexing, and Processing
Subproject
IKAROS: Indoor Keyword-Aware Routing System
Subproject
TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics
Subproject
Continuous Social Distance Monitoring in Indoor Space

Publications

  1. Continuous social distance monitoring in indoor space.
    Harry Kai-Ho Chan, Huan Li, Xiao Li, and Hua Lu.
    Proceedings of the 48th International Conference on Very Large Data Bases (PVLDB), 13 pages, 2022, to appear.
    DOI
    CODE
  2. IKAROS: An indoor keyword-aware routing system.
    Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Lidan Shou, and Jianliang Xu.
    Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE), 4 pages, 2022, to appear. (Demo)
    DOI
    VIDEO
    CODE
  3. Time-constrained indoor keyword-aware routing.
    Harry Kai-Ho Chan, Tiantian Liu, Huan Li, and Hua Lu.
    Proceedings of the 17th International Symposium on Spatial and Temporal Databases (SSTD), pp. 74-84, 2021.
    DOI
  4. Towards indoor temporal-variation aware shortest path query.
    Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Muhammad Aamir Cheema, Hong Cheng, and Jianliang Xu.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 15 pages, 2021.
    DOI
  5. Towards crowd-aware indoor path planning.
    Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, and Lidan Shou.
    Proceedings of the 47th International Conference on Very Large Data Bases (PVLDB), 14(8): 1365--1377, 2021.
    DOI
    EXTENSION
  6. Indoor spatial queries: Modeling, indexing, and processing.
    Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, and Lidan Shou.
    Proceedings of the 24th International Conference on Extending Database Technology (EDBT), pp. 181-192, 2021.
    DOI
    1-MINUTE POSTER
    SLIDES
    EXTENSION
    CODE&DATA
  7. Toward translating raw indoor positioning data into mobility semantics.
    Huan Li, Hua Lu, Gang Chen, Ke Chen, Qinkuang Chen, and Lidan Shou.
    ACM/IMS Transactions on Data Science (TDS), 1(4) No.26: 1-37, 2020.
    DOI
  8. Efficiently processing spatial and keyword queries in indoor venues.
    Zhou Shao, Muhammad Aamir Cheema, David Taniar, Hua Lu, and Shiyu Yang.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 33(9): 3229-3244, 2021.
    DOI
  9. Shortest path queries for indoor venues with temporal variations.
    Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Muhammad Aamir Cheema, Hong Cheng, and Jianliang Xu.
    Proceedings of the 36th IEEE International Conference on Data Engineering (ICDE), pp. 2014-2017, 2020. (Short Paper)
    DOI
    POSTER
  10. Indoor mobility semantics annotation using coupled conditional Markov networks.
    Huan Li, Hua Lu, Muhammad Aamir Cheema, Lidan Shou, and Gang Chen.
    Proceedings of the 36th IEEE International Conference on Data Engineering (ICDE), pp. 1441-1452, 2020.
    DOI
    SLIDES
  11. Indoor top-k keyword-aware routing query.
    Zijin Feng, Tiantian Liu, Huan Li, Hua Lu, Lidan Shou, and Jianliang Xu.
    Proceedings of the 36th IEEE International Conference on Data Engineering (ICDE), pp. 1213-1224, 2020.
    DOI
    SLIDES
    POSTER
    DATA

Benchmarks and Datasets

Indoor Spatial Queries Benchmark Indoor Venue Keyword Dataset

Contact

luhua@ruc.dk

indoorLBS

The project was supported by Independent Research Fund Denmark (Grant No. 8022-00366B).
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