TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics
Summary: TRIPS translates raw indoor positioning data into mobility semantics via a configurable end-to-end pipeline. It unifies multi-source inputs, cleans data, and exports semantics with traceable intermediate data and a flexible viewer for expert inspection. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Huan Li
- 2. Hua Lu
- 3. Feichao Shi
- 4. Gang Chen
- 5. Ke Chen
- 6. Lidan Shou
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,501 | Towards Crowd-aware Indoor Path Planning | 2021 | VLDB | 4.1905499e-05 |
| 11,610 | IMO: A Toolbox for Simulating and Querying "Infected" Moving Objects | 2020 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,821 | STMaker - A System to Make Sense of Trajectory Data | 2014 | VLDB | 6.726077e-05 |
| 4,288 | Vita: A Versatile Toolkit for Generating Indoor Mobility Data for Real-World Buildings | 2016 | VLDB | 6.2824978e-05 |
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