University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Enabling Query of Frequently Updated Data from Mobile Sensing Sources

Zhou, Y, De, S, Wang, W and Moessner, K (2014) Enabling Query of Frequently Updated Data from Mobile Sensing Sources In: 13th IEEE International Conference on Ubiquitous Computing and Communications (IUCC 2014), 2014-12-19 - 2014-12-21, Chengdu, China.

[img]
Preview
Text
CameraReady_IUCC paper147_SDe.pdf - ["content_typename_Accepted version (post-print)" not defined]
Available under License : See the attached licence file.

Download (633kB) | Preview
[img]
Preview
PDF (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

The Internet of Things (IoT) paradigm connects everyday objects to the Internet and enables a multitude of applications with the real world data collected from those objects. In the city environment, real world data sources include fixed installations of sensor networks by city authorities as well as mobile sources, such as citizens’ smartphones,¬ taxis and buses equipped with sensors. This kind of data varies not only along the temporal but also the spatial axis. For handling such frequently updated, time-stamped and structured data from a large number of heterogeneous sources, this paper presents a data-centric framework that offers a structured substrate for abstracting heterogeneous sensing sources. More importantly, it enables the collection, storage and discovery of observation and measurement data from both static and mobile sensing sources.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
Zhou, YUNSPECIFIEDUNSPECIFIED
De, SUNSPECIFIEDUNSPECIFIED
Wang, WUNSPECIFIEDUNSPECIFIED
Moessner, KUNSPECIFIEDUNSPECIFIED
Date : 19 December 2014
Identification Number : 10.1109/CSE.2014.190
Contributors :
ContributionNameEmailORCID
PublisherIEEE, UNSPECIFIEDUNSPECIFIED
Uncontrolled Keywords : Internet of Things, sensor data, time-series data, smart city, observation and measurement data discovery
Additional Information : © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 02 Dec 2014 18:42
Last Modified : 20 Feb 2015 14:33
URI: http://epubs.surrey.ac.uk/id/eprint/806674

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800