Demo Data from VLDB 2026 / reviewers in the wild / expert
S. N. Aishwarya
dblp:161/9640
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1
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 |
Internet of things and sensor networks · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › wireless body area network
health monitoring |
0.2 | 1 | 2015 | CleanHands: an integrated monitoring system for control of hospital acquired infections · IPSN 2015 |
Methods — techniques the papers use, named apart from their topics
state-following algorithm · 0.4BLE beacon tracking · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | CleanHands: an integrated monitoring system for control of hospital acquired infectionsabstractA leading cause of mortality of hospitalized patients are hospital acquired infections (HAI). Unclean hands of healthcare personnel (HCP) are the most common factor contributing to HAI, but their strict compliance to hand hygiene protocols is difficult to supervise. In this work, we propose CleanHands: a simple, low-cost and scalable monitoring and alerting system to ensure adequate thoroughness of disinfection. CleanHands uses a combination of low-cost Bluetooth low energy (BLE) beacon tags and mobile phones for HCP tracking. It integrates infection control models and state-following algorithms for alarming in the event of noncompliance to hand hygiene. Our preliminary experiments in a mockup, small scale intensive care unit (ICU) facility shows promising results with less than 5% false positives. Prasant Misra, Vasanth Rajaraman, S. N. Aishwarya, Bharat Dwivedi, Jay Warrior |
IPSN | 3 |