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 languageEnglish
Title of host publicationAdjunct Proceedings of the 14th International Conference on Location Based Services
EditorsPeter Kiefer, Haosheng Huang, Nico Van de Weghe, Martin Raubal
PublisherETH Zürich
Pages25-31
Number of pages7
DOIs
Publication statusPublished - 15 Jan 2018
Event14th International Conference on Location Based Services - Zurich, Switzerland
Duration: 15 Jan 201817 Jan 2018
Conference number: 14

Conference

Conference14th International Conference on Location Based Services
Abbreviated titleLBS 2018
CountrySwitzerland
CityZurich
Period15/01/1817/01/18

ID: 51424670