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Discovering Influential Positions in RFID-Based Indoor Tracking Data
| Content Provider | MDPI |
|---|---|
| Author | Jin, Ye Cui, Lizhen |
| Copyright Year | 2020 |
| Description | The rapid development of indoor localization techniques such as Wi-Fi and RFID makes it possible to obtain users’ position-tracking data in indoor space. Indoor position-tracking data, also known as indoor moving trajectories, offer many new opportunities to mine decision-making knowledge. In this paper, we study the detection of highly influential positions from indoor position-tracking data, e.g., to detect highly influential positions in a business center, or to detect the hottest shops in a shopping mall according to users’ indoor position-tracking data. We first describe three baseline solutions to this problem, which are count-based, density-based, and duration-based algorithms. Then, motivated by the H-index for evaluating the influence of an author or a journal in academia, we propose a new algorithm called H-Count, which evaluates the influence of an indoor position similarly to the H-index. We further present an improvement of the H-Count by taking a filtering step to remove unqualified position-tracking records. This is based on the observation that many visits to a position such as a gate are meaningless for the detection of influential indoor positions. Finally, we simulate 100 moving objects in a real building deployed with 94 RFID readers over 30 days to generate 223,564 indoor moving trajectories, and conduct experiments to compare our proposed H-Count and H-Count* with three baseline algorithms. The results show that H-Count outperforms all baselines and H-Count* can further improve the F-measure of the H-Count by 113% on average. |
| Starting Page | 330 |
| e-ISSN | 20782489 |
| DOI | 10.3390/info11060330 |
| Journal | Information |
| Issue Number | 6 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-06-20 |
| Access Restriction | Open |
| Subject Keyword | Information Transportation Science and Technology Rfid Indoor Space Indoor Position-tracking Data Indoor Moving Trajectory Influential Position H-count |
| Content Type | Text |
| Resource Type | Article |
