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Kuei-Han Li

dblp:95/11186 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—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%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network
sensor deployment
0.112012
TriopusNet: automating wireless sensor network deployment and replacement in pipeline monitoring · IPSN 2012
Internet of things and sensor networks › reliability
sensor network reliability
0.112012
TriopusNet: automating wireless sensor network deployment and replacement in pipeline monitoring · IPSN 2012

Methods — techniques the papers use, named apart from their topics

testbed evaluation · 0.1mobile sensor nodes · 0.1
YearPublicationVenuePosition
2012 TriopusNet: automating wireless sensor network deployment and replacement in pipeline monitoring
abstract
This study presents TriopusNet, a mobile wireless sensor network system for autonomous sensor deployment in pipeline monitoring. TriopusNet works by automatically releasing sensor nodes from a centralized repository located at the source of the water pipeline. During automated deployment, TriopusNet runs a sensor deploy-ment algorithm to determine node placement. While a node is flowing inside the pipeline, it performs placement by extending its mechanical arms to latch itself onto the pipe's inner surface. By continuously releasing nodes into pipes, the TriopusNet system builds a wireless network of interconnected sensor nodes. When a node runs at a low battery level or experiences a fault, the TriopusNet system releases a fresh node from the repository and performs a node replacement algorithm to replace the failed node with the fresh one. We have evaluated the TriopusNet system by creating and collecting real data from an experimental pipeline testbed. Comparing with the non-automated static deployment, TriopusNet is able to use less sensor nodes to cover a sensing area in the pipes while maintaining network connectivity among nodes with high data collection rate. Experimental results also show that TriopusNet can recover from the network disconnection caused by a battery-depleted node and successfully replace the battery-depleted node with a fresh node.
Tsung-Te Lai, Wei-Ju Chen, Kuei-Han Li, Polly Huang, Hao-Hua Chu
IPSN3