Demo Data from SIGIR 2026 / reviewers in the wild / expert
Tzu-Ting Lin
dblp:179/3232
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Wireless sensing and localization · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization
indoor localization |
0.2 | 1 | 2016 | Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human Tracking · IPSN 2016 |
Wireless sensing and localization
bluetooth beacon |
0.1 | 1 | 2016 | Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human Tracking · IPSN 2016 |
Methods — techniques the papers use, named apart from their topics
radio fingerprinting · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human TrackingabstractIndoor positioning is one of the key technologies for enabling location-aware applications. To the best of our knowledge, existing indoor positioning technologies are aimed at providing very high-accuracy location information, but are hindered by the need of a infrastructure with high installation and maintenance costs. In addition, their accuracy is usually highly variable and vulnerable to environmental changes or external interference. Thus, for applications of indoor human tracking, the practical considerations of choosing a suitable indoor positioning technique should be to provide adequate accuracy while also being economical. Based on this observation, our study presents an indoor, room-level tracking method characterized by an infrastructure with low costs to build and maintain. The user carries a mobile device that can determine his/her location with the help of Bluetooth beacons installed at the intersections between rooms and hallways. In contrast to traditional radio-fingerprint map and proximity approaches, in this study the mobile device tracks the user's moving direction and the temporal variation of the radio signal strength from nearby Bluetooth beacons, to determine when the device enters or leaves a given room or hallway. Therefore, by determining the sequence of a user's movements, his/her moving path can be recorded for indoor tracking or navigation. Tzu-Ting Lin, Chun-Ju Lin, Chia-Min Su, Yi-Chun Lin, Warren Huang-Chen Lee |
IPSN | 1 |