Standard

Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances. / Ligtvoet, Birgit R.; Verbree, Edward; Gorte, Ben G.H.

Adjunct Proceedings of the 14th International Conference on Location Based Services. ed. / Peter Kiefer; Haosheng Huang; Nico Van de Weghe; Martin Raubal. ETH Zürich, 2018. p. 25-31.

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Harvard

Ligtvoet, BR, Verbree, E & Gorte, BGH 2018, Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances. in P Kiefer, H Huang, N Van de Weghe & M Raubal (eds), Adjunct Proceedings of the 14th International Conference on Location Based Services. ETH Zürich, pp. 25-31, 14th International Conference on Location Based Services, Zurich, Switzerland, 15/01/18. https://doi.org/10.3929/ethz-b-000225584

APA

Ligtvoet, B. R., Verbree, E., & Gorte, B. G. H. (2018). Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances. In P. Kiefer, H. Huang, N. Van de Weghe, & M. Raubal (Eds.), Adjunct Proceedings of the 14th International Conference on Location Based Services (pp. 25-31). ETH Zürich. https://doi.org/10.3929/ethz-b-000225584

Vancouver

Ligtvoet BR, Verbree E, Gorte BGH. Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances. In Kiefer P, Huang H, Van de Weghe N, Raubal M, editors, Adjunct Proceedings of the 14th International Conference on Location Based Services. ETH Zürich. 2018. p. 25-31 https://doi.org/10.3929/ethz-b-000225584

Author

Ligtvoet, Birgit R. ; Verbree, Edward ; Gorte, Ben G.H. / Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances. Adjunct Proceedings of the 14th International Conference on Location Based Services. editor / Peter Kiefer ; Haosheng Huang ; Nico Van de Weghe ; Martin Raubal. ETH Zürich, 2018. pp. 25-31

BibTeX

@inproceedings{e6f9a640d9c942569311a1a59a4358c6,
title = "Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances",
abstract = "There has been a steady increase in applications that rely on crowdsensing to gather data for analysis purposes. Crowdsensing enables the use of dynamic sensors to collect data on static objects of interest. However, using dynamic sensors in this way causes a problem. The focus of the collected data is on the position of the sensor, not on the object of interest. This results in difficulties in tracking the object of interest in terms of what part of the data from the dynamic sensor describes the object of interest. To shift the focus from the dynamic sensors to a static object, the virtual sensor is introduced. A virtual sensor enables the grouping of data from different dynamic sensors into a single virtual sensor based on measurement positions. The data from the multiple dynamic sensors can be analyzed to provide information per virtual sensor. The data structure of a visual sensor is close to the SensorThings API data structure, which can be expanded to support virtual sensors by adding an additional entity.",
author = "Ligtvoet, {Birgit R.} and Edward Verbree and Gorte, {Ben G.H.}",
year = "2018",
month = jan,
day = "15",
doi = "10.3929/ethz-b-000225584",
language = "English",
pages = "25--31",
editor = "Peter Kiefer and Haosheng Huang and {Van de Weghe}, Nico and Martin Raubal",
booktitle = "Adjunct Proceedings of the 14th International Conference on Location Based Services",
publisher = "ETH Z{\"u}rich",
note = "14th International Conference on Location Based Services, LBS 2018 ; Conference date: 15-01-2018 Through 17-01-2018",

}

RIS

TY - GEN

T1 - Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances

AU - Ligtvoet, Birgit R.

AU - Verbree, Edward

AU - Gorte, Ben G.H.

N1 - Conference code: 14

PY - 2018/1/15

Y1 - 2018/1/15

N2 - There has been a steady increase in applications that rely on crowdsensing to gather data for analysis purposes. Crowdsensing enables the use of dynamic sensors to collect data on static objects of interest. However, using dynamic sensors in this way causes a problem. The focus of the collected data is on the position of the sensor, not on the object of interest. This results in difficulties in tracking the object of interest in terms of what part of the data from the dynamic sensor describes the object of interest. To shift the focus from the dynamic sensors to a static object, the virtual sensor is introduced. A virtual sensor enables the grouping of data from different dynamic sensors into a single virtual sensor based on measurement positions. The data from the multiple dynamic sensors can be analyzed to provide information per virtual sensor. The data structure of a visual sensor is close to the SensorThings API data structure, which can be expanded to support virtual sensors by adding an additional entity.

AB - There has been a steady increase in applications that rely on crowdsensing to gather data for analysis purposes. Crowdsensing enables the use of dynamic sensors to collect data on static objects of interest. However, using dynamic sensors in this way causes a problem. The focus of the collected data is on the position of the sensor, not on the object of interest. This results in difficulties in tracking the object of interest in terms of what part of the data from the dynamic sensor describes the object of interest. To shift the focus from the dynamic sensors to a static object, the virtual sensor is introduced. A virtual sensor enables the grouping of data from different dynamic sensors into a single virtual sensor based on measurement positions. The data from the multiple dynamic sensors can be analyzed to provide information per virtual sensor. The data structure of a visual sensor is close to the SensorThings API data structure, which can be expanded to support virtual sensors by adding an additional entity.

U2 - 10.3929/ethz-b-000225584

DO - 10.3929/ethz-b-000225584

M3 - Conference contribution

SP - 25

EP - 31

BT - Adjunct Proceedings of the 14th International Conference on Location Based Services

A2 - Kiefer, Peter

A2 - Huang, Haosheng

A2 - Van de Weghe, Nico

A2 - Raubal, Martin

PB - ETH Zürich

T2 - 14th International Conference on Location Based Services

Y2 - 15 January 2018 through 17 January 2018

ER -

ID: 51424670