Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge

Alexandr Vasenev, Dan Ionita, Frank Bijleveld, Timo Hartmann, Andries G. Doree

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
12 Downloads (Pure)

Abstract

Documenting machinery movements by using positioning technologies, such as global navigation satellite systems (GNSS), is essential to understand and further improve construction processes. However, before measurements can be meaningfully analysed the documented movements should be filtered to exclude outliers. Eliminating outliers manually is a time-demanding process, while automatic filtering can be inaccurate. In particular, path elements may get lost if machine-specific movements are misconceived as noisy data. As a trade-off, we propose an information fusion approach to filter paths of construction machines in a semi-automatic way. The approach allows an expert to relate “hard” sensor and “soft” field records with his or her expectations about how machines can move in real construction projects. Specially developed open-source software illustrates the proposed approach for filtering the documented paths of machines involved in road paving projects. The initial testing of the developed software showed its suitability to filter outliers in GNSS data and identified possibilities for further improvements.
Original languageEnglish
Title of host publicationeg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria
EditorsG. Suter, P. de Wilde, Y. Rafiq
Place of PublicationVienna, Austria
PublisherTU Wien
Pages1-10
Number of pages10
Publication statusPublished - 1 Jul 2013
Event20th International Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2013 - Vienna, Austria
Duration: 1 Jul 20133 Jul 2013
Conference number: 20

Publication series

Name
PublisherTU Wien

Workshop

Workshop20th International Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2013
Abbreviated titleEG-ICE
CountryAustria
CityVienna
Period1/07/133/07/13

Fingerprint

Information fusion
Navigation
Satellites
Sensors
Machinery
Testing

Keywords

  • METIS-297217
  • IR-89443

Cite this

Vasenev, A., Ionita, D., Bijleveld, F., Hartmann, T., & Doree, A. G. (2013). Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge. In G. Suter, P. de Wilde, & Y. Rafiq (Eds.), eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria (pp. 1-10). Vienna, Austria: TU Wien.
Vasenev, Alexandr ; Ionita, Dan ; Bijleveld, Frank ; Hartmann, Timo ; Doree, Andries G. / Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge. eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria. editor / G. Suter ; P. de Wilde ; Y. Rafiq. Vienna, Austria : TU Wien, 2013. pp. 1-10
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title = "Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge",
abstract = "Documenting machinery movements by using positioning technologies, such as global navigation satellite systems (GNSS), is essential to understand and further improve construction processes. However, before measurements can be meaningfully analysed the documented movements should be filtered to exclude outliers. Eliminating outliers manually is a time-demanding process, while automatic filtering can be inaccurate. In particular, path elements may get lost if machine-specific movements are misconceived as noisy data. As a trade-off, we propose an information fusion approach to filter paths of construction machines in a semi-automatic way. The approach allows an expert to relate “hard” sensor and “soft” field records with his or her expectations about how machines can move in real construction projects. Specially developed open-source software illustrates the proposed approach for filtering the documented paths of machines involved in road paving projects. The initial testing of the developed software showed its suitability to filter outliers in GNSS data and identified possibilities for further improvements.",
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Vasenev, A, Ionita, D, Bijleveld, F, Hartmann, T & Doree, AG 2013, Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge. in G Suter, P de Wilde & Y Rafiq (eds), eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria. TU Wien, Vienna, Austria, pp. 1-10, 20th International Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2013, Vienna, Austria, 1/07/13.

Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge. / Vasenev, Alexandr; Ionita, Dan; Bijleveld, Frank; Hartmann, Timo; Doree, Andries G.

eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria. ed. / G. Suter; P. de Wilde; Y. Rafiq. Vienna, Austria : TU Wien, 2013. p. 1-10.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge

AU - Vasenev, Alexandr

AU - Ionita, Dan

AU - Bijleveld, Frank

AU - Hartmann, Timo

AU - Doree, Andries G.

PY - 2013/7/1

Y1 - 2013/7/1

N2 - Documenting machinery movements by using positioning technologies, such as global navigation satellite systems (GNSS), is essential to understand and further improve construction processes. However, before measurements can be meaningfully analysed the documented movements should be filtered to exclude outliers. Eliminating outliers manually is a time-demanding process, while automatic filtering can be inaccurate. In particular, path elements may get lost if machine-specific movements are misconceived as noisy data. As a trade-off, we propose an information fusion approach to filter paths of construction machines in a semi-automatic way. The approach allows an expert to relate “hard” sensor and “soft” field records with his or her expectations about how machines can move in real construction projects. Specially developed open-source software illustrates the proposed approach for filtering the documented paths of machines involved in road paving projects. The initial testing of the developed software showed its suitability to filter outliers in GNSS data and identified possibilities for further improvements.

AB - Documenting machinery movements by using positioning technologies, such as global navigation satellite systems (GNSS), is essential to understand and further improve construction processes. However, before measurements can be meaningfully analysed the documented movements should be filtered to exclude outliers. Eliminating outliers manually is a time-demanding process, while automatic filtering can be inaccurate. In particular, path elements may get lost if machine-specific movements are misconceived as noisy data. As a trade-off, we propose an information fusion approach to filter paths of construction machines in a semi-automatic way. The approach allows an expert to relate “hard” sensor and “soft” field records with his or her expectations about how machines can move in real construction projects. Specially developed open-source software illustrates the proposed approach for filtering the documented paths of machines involved in road paving projects. The initial testing of the developed software showed its suitability to filter outliers in GNSS data and identified possibilities for further improvements.

KW - METIS-297217

KW - IR-89443

M3 - Conference contribution

SP - 1

EP - 10

BT - eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria

A2 - Suter, G.

A2 - de Wilde, P.

A2 - Rafiq, Y.

PB - TU Wien

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Vasenev A, Ionita D, Bijleveld F, Hartmann T, Doree AG. Information fusion of GNSS sensor readings, field notes, and expert's a priori knowledge. In Suter G, de Wilde P, Rafiq Y, editors, eg-ice 2013 20th international workshop: intelligent computing in engineering, July 1 - 3, 2013, Vienna, Austria. Vienna, Austria: TU Wien. 2013. p. 1-10