Lean and Robust Phenomenon Boundary Approximation

Carsten Buschmann; Daniela Krüger; Stefan Fischer

doi:10.1109/EFTA.2007.4416918

Lean and Robust Phenomenon Boundary Approximation

Carsten Buschmann, Daniela Krüger, Stefan Fischer

Institute of Telematics

Abstract

We present an algorithm for computing a compact polygonal boundary of physical phenomena that nodes in a wireless sensor network can detect. It works strictly local and is robust against measurement errors and packet loss. It can deal with non-convex shapes and assumes nothing but location awareness at the nodes and a loose time synchronization. Other than different schemes described in literature our algorithm does not rely on a hierarchical clustered communication structure. After discussing related approaches and introducing our boundary approximation scheme in detail, we show through an extensive set of simulations that it is robust and accurate.

Original language	English
Title of host publication	2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007)
Number of pages	8
Publisher	IEEE
Publication date	01.12.2007
Pages	1202-1209
Article number	4416918
ISBN (Print)	978-1-4244-0825-2, 978-1-4244-0826-9
DOIs	https://doi.org/10.1109/EFTA.2007.4416918
Publication status	Published - 01.12.2007
Event	12th IEEE International Conference on Emerging Technologies and Factory Automation - Patras, Greece Duration: 25.09.2007 → 28.09.2007 Conference number: 72709

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EFTA.2007.4416918

Cite this

@inproceedings{14ce9213c1b145bdb7940db0f4b0ff65,

title = "Lean and Robust Phenomenon Boundary Approximation",

abstract = "We present an algorithm for computing a compact polygonal boundary of physical phenomena that nodes in a wireless sensor network can detect. It works strictly local and is robust against measurement errors and packet loss. It can deal with non-convex shapes and assumes nothing but location awareness at the nodes and a loose time synchronization. Other than different schemes described in literature our algorithm does not rely on a hierarchical clustered communication structure. After discussing related approaches and introducing our boundary approximation scheme in detail, we show through an extensive set of simulations that it is robust and accurate.",

author = "Carsten Buschmann and Daniela Kr{\"u}ger and Stefan Fischer",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/EFTA.2007.4416918",

language = "English",

isbn = "978-1-4244-0825-2",

series = "IEEE International Conference on Emerging Technologies and Factory Automation, ETFA",

publisher = "IEEE",

pages = "1202--1209",

booktitle = "2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007)",

note = "12th IEEE International Conference on Emerging Technologies and Factory Automation <br/>, ETFA 2007 ; Conference date: 25-09-2007 Through 28-09-2007",

}

Buschmann, C, Krüger, D & Fischer, S 2007, Lean and Robust Phenomenon Boundary Approximation. in 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007)., 4416918, IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, IEEE, pp. 1202-1209, 12th IEEE International Conference on Emerging Technologies and Factory Automation
, Patras, Greece, 25.09.07. https://doi.org/10.1109/EFTA.2007.4416918

Lean and Robust Phenomenon Boundary Approximation. / Buschmann, Carsten; Krüger, Daniela; Fischer, Stefan.
2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007). IEEE, 2007. p. 1202-1209 4416918 (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

TY - GEN

T1 - Lean and Robust Phenomenon Boundary Approximation

AU - Buschmann, Carsten

AU - Krüger, Daniela

AU - Fischer, Stefan

N1 - Conference code: 72709

PY - 2007/12/1

Y1 - 2007/12/1

N2 - We present an algorithm for computing a compact polygonal boundary of physical phenomena that nodes in a wireless sensor network can detect. It works strictly local and is robust against measurement errors and packet loss. It can deal with non-convex shapes and assumes nothing but location awareness at the nodes and a loose time synchronization. Other than different schemes described in literature our algorithm does not rely on a hierarchical clustered communication structure. After discussing related approaches and introducing our boundary approximation scheme in detail, we show through an extensive set of simulations that it is robust and accurate.

AB - We present an algorithm for computing a compact polygonal boundary of physical phenomena that nodes in a wireless sensor network can detect. It works strictly local and is robust against measurement errors and packet loss. It can deal with non-convex shapes and assumes nothing but location awareness at the nodes and a loose time synchronization. Other than different schemes described in literature our algorithm does not rely on a hierarchical clustered communication structure. After discussing related approaches and introducing our boundary approximation scheme in detail, we show through an extensive set of simulations that it is robust and accurate.

UR - https://www.scopus.com/pages/publications/47849088503

U2 - 10.1109/EFTA.2007.4416918

DO - 10.1109/EFTA.2007.4416918

M3 - Conference contribution

SN - 978-1-4244-0825-2

SN - 978-1-4244-0826-9

T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA

SP - 1202

EP - 1209

BT - 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007)

PB - IEEE

T2 - 12th IEEE International Conference on Emerging Technologies and Factory Automation <br/>

Y2 - 25 September 2007 through 28 September 2007

ER -

Lean and Robust Phenomenon Boundary Approximation

Abstract

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this