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Smart sensing and sensor data collection on the move for modelling intelligent environments
Caulfield School of Information Technology, Monash University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1990-5734
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0002-4133-3317
2008 (English)In: Next Generation Teletraffic and Wired/Wireless Advanced Networking: 8th International Conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART 2008, St. Petersburg, Russia, September 3-5, 2008. Proceedings / [ed] Sergey Balandin; Dimitri Moltchanov; Yevgeni Koucheryavy, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2008, p. 306-317Conference paper, Published paper (Refereed)
Abstract [en]

With advent of pervasive computing and considerable acceptance of sensor networks, smart sensing techniques and data collection have been topics of interest. This paper presents a smart sensing and data collection technique from sensor networks using context aware high powered mobile objects within the environment. The paper proposes CAM-R a context aware robot that can move within smart environments sensing new sensor sources and collecting sensory originated data efficiently. Based on these sensed data sources, we propose an extension to context spaces model that builds a virtual model of the intelligent environment. This intelligent environment model built using extended context spaces can be used by number of context aware applications to efficiently query and retrieve data from the sensor network using CAM-R based data collection approach. We also present a prototype implementation of CAM-R built using off-the-shelf hardware and a context based cost function used to compute data collection decisions. We validate our system by implementing the virtual modelling of the intelligent environment based on simulated input obtained from CAM-R and sensors. We also evaluate CAM-Rby simulating and comparing the energy spent by the sensor nodes during data collection process using our proposed approach and traditional fixed sink based approach.

Place, publisher, year, edition, pages
Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2008. p. 306-317
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5174
National Category
Media and Communication Technology Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Mobile and Pervasive Computing; Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-39206DOI: 10.1007/978-3-540-85500-2_31Scopus ID: 2-s2.0-51849116433Local ID: dda48860-3099-11dd-9729-000ea68e967bISBN: 978-3-540-85499-9 (print)OAI: oai:DiVA.org:ltu-39206DiVA, id: diva2:1012715
Conference
Russian Conference on Smart Spaces : 03/09/2008 - 05/09/2008
Note
Validerad; 2008; 20080602 (jerker)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2018-07-10Bibliographically approved

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Zaslavsky, ArkadyDelsing, Jerker

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