Demo Data from VLDB 2026 / reviewers in the wild / expert
Leon Kleiboer
dblp:33/10521
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—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% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Smart cities and intelligent transportation · 100% |
Topics — the 2 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 sensor network
sensor network applications |
0.1 | 1 | 2011 | Industry: using dynamic WSNs in smart logistics for fruits and pharmacy · SenSys 2011 |
Smart cities and intelligent transportation
logistics |
0.0 | 1 | 2011 | Industry: using dynamic WSNs in smart logistics for fruits and pharmacy · SenSys 2011 |
Methods — techniques the papers use, named apart from their topics
remote monitoring · 0.2middleware · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Industry: using dynamic WSNs in smart logistics for fruits and pharmacyabstractIn this paper we describe a smart way to apply dynamic wireless sensor networks (WSN) in logistics. Especially in the temperature controlled supply chain (cold chain), perishable goods like fruits and pharmaceuticals greatly benefit from real-time quality monitoring during storage and transport in order to avoid quality degradation and spoilage. In our system, wireless sensor nodes called SmartPoints monitor the environmental conditions and generate alarms when specific events are detected. Additionally, they calculate the remaining shelf life of the perishable goods they travel with. When there is an Internet-connected WSN available during travel, the shelf-life prediction and associated alarms are directly sent to a back-end server. Alternatively they are logged on the SmartPoints and flushed upon arrival, such that the remaining shelf-life and alarms are immediately clear and a full history will be available later. Our dynamic WSN supports a number of protocols that enable support for the dynamic processes in logistic processes. The Ambient middleware supports real-time monitoring and remote maintenance across the Internet via wired and mobile wireless network access technologies. Additionally, the middleware offers easy integration with third-party applications. Ambient Studio utilizes the middleware for remote WSN configuration and monitoring. Dennis J. A. Bijwaard, Wouter van Kleunen, Paul J. M. Havinga, Leon Kleiboer, Mark J. J. Bijl |
SenSys | 4 |