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

Birgit R. Ligtvoet; Edward Verbree; Ben G.H. Gorte

doi:10.3929/ethz-b-000225584

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

Birgit R. Ligtvoet, Edward Verbree, Ben G.H. Gorte

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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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.

Original language	English
Title of host publication	Adjunct Proceedings of the 14th International Conference on Location Based Services
Editors	Peter Kiefer, Haosheng Huang, Nico Van de Weghe, Martin Raubal
Publisher	ETH Zürich
Pages	25-31
Number of pages	7
DOIs	https://doi.org/10.3929/ethz-b-000225584
Publication status	Published - 15 Jan 2018
Event	14th International Conference on Location Based Services - Zurich, Switzerland Duration: 15 Jan 2018 → 17 Jan 2018 Conference number: 14

Conference

Conference	14th International Conference on Location Based Services
Abbreviated title	LBS 2018
Country/Territory	Switzerland
City	Zurich
Period	15/01/18 → 17/01/18

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http://www.gdmc.nl/publications/2018/Virtual_sensors_Synthesizing_dynamic_crowdsensing_data.pdf

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@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",

}

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

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 volume › Conference contribution › Scientific › peer-review

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

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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

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PB - ETH Zürich

T2 - 14th International Conference on Location Based Services

Y2 - 15 January 2018 through 17 January 2018

ER -

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

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