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Md. Tanbir Hassan

dblp:179/3268 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
0009-0002-7233-3966ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1Human-computer interaction and ubiquitous computing · 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
Wireless sensing and localization · 56% Internet of things and sensor networks · 36% Network optimization and economics · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › device-free sensing
device-free localization
0.212016
Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization · IPSN 2016
Wireless sensing and localization › indoor localization
fingerprint-based localization
0.212016
Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization · IPSN 2016
Internet of things and sensor networks › wireless sensor network
sensor deployment
0.212016
Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization · IPSN 2016
Network optimization and economics › network design
deployment cost minimization
0.112016
Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization · IPSN 2016
Internet of things and sensor networks
wireless sensor network
0.112016
Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization · IPSN 2016

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

fingerprinting · 0.2
YearPublicationVenuePosition
2017 Redundancy reduction for indoor device-free localization
Jinjun Liu, Ning An 0001, Md. Tanbir Hassan, Min Peng 0001
Pers. Ubiquitous Comput.3
2016 Poster Abstract: Node Deployment Mechanism for Quick, Indoor, and Device-Free Localization
abstract
Radio frequency based device-free passive localization has been actively studied. An important issue with this technique is that a large amount of sensor nodes are usually deployed in localization environments, causing high deployment cost, high computation complexity and other drawbacks. To reduce the number of nodes while maintaining high localization accuracy, this paper proposes a fingerprint-based node deployment mechanism, which saves hardware cost, speeds up node deployment process as well as maintains a similar accuracy. The experiments are conducted in two environments with considerably different sizes of 150 m2and 25 m2. Maintaining the accuracies above 95%, the proposed mechanism can efficiently reduce the total number of nodes in large room by 54.55% and in small room by 68.75%. Especially, the localization response time sharply reduces by 93.08% in the large room and 79.87% in the small room.
Jinjun Liu, Ning An 0001, Md. Tanbir Hassan, Guilin Chen, Yanyong Zhang
IPSN3