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

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SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production

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10.1109/EFTA.2007.4416918

Cite this

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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.",

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

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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

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AU - Fischer, Stefan

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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.

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ER -

Lean and Robust Phenomenon Boundary Approximation

Abstract

UN SDGs

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