Demo Data from EDBT 2026 / reviewers in the wild / expert
Beiyu Wang
dblp:322/6952
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
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% | |
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 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
wifi sensing |
0.6 | 1 | 2022 | Liquid level detection using wireless signals · MobiSys 2022 |
Ubiquitous computing and smart environments › smart home
smart home sensing |
0.2 | 1 | 2022 | Liquid level detection using wireless signals · MobiSys 2022 |
Methods — techniques the papers use, named apart from their topics
transducer signal processing · 1.1resonance sensing · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Liquid level detection using wireless signalsabstractSensing the liquid level in a container is critical to building many smart home and mobile healthcare applications. This paper presents a liquid level sensing system that is low-cost, high accuracy, widely applicable to different daily liquids and containers, and can be easily integrated with existing smart home networks. Our system uses an existing home WiFi network and a low-cost transducer that is attached to the container to sense the resonance of the container for liquid level detection. We evaluate our system in home environments with various containers and liquids. Preliminary results show that our system achieves an accuracy of 97% for continuous prediction and an F-score of 0.968 for discrete prediction. Yili Ren, Zi Wang 0003, Beiyu Wang, Sheng Tan, Jie Yang 0003 |
MobiSys | 3 |