hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Smart Home Simulation using Avatar Control and Probabilistic Sampling
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0001-8804-5884
Ulster University, Jordanstown, United Kingdom. (CHIC)
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Ulster University, Jordanstown, United Kingdom. (CHIC)
2015 (English)In: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), Piscataway, NJ: IEEE Press, 2015, 336-341 p.Conference paper, Published paper (Refereed)
Abstract [en]

Development, testing and validation of algorithms for smart home applications are often complex, expensive and tedious processes. Research on simulation of resident activity patterns in Smart Homes is an active research area and facilitates development of algorithms of smart home applications. However, the simulation of passive infrared (PIR) sensors is often used in a static fashion by generating equidistant events while an intended occupant is within sensor proximity. This paper suggests the combination of avatar-based control and probabilistic sampling in order to increase realism of the simulated data. The number of PIR events during a time interval is assumed to be Poisson distributed and this assumption is used in the simulation of Smart Home data. Results suggest that the proposed approach increase realism of simulated data, however results also indicate that improvements could be achieved using the geometric distribution as a model for the number of PIR events during a time interval. © IEEE 2015

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2015. 336-341 p.
Keyword [en]
Avatars, Intelligent sensors, Smart homes, Data models, Software, Conferences
National Category
Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-27741DOI: 10.1109/PERCOMW.2015.7134059ISI: 000380510900076Scopus ID: 2-s2.0-84946097507ISBN: 978-1-4799-8425-1 (print)OAI: oai:DiVA.org:hh-27741DiVA: diva2:814238
Conference
SmartE: Closing the Loop – The 2nd IEEE PerCom Workshop on Smart Environments, St. Louis, Missouri, USA, March 23-27, 2015
Projects
SA3L, CAISR
Funder
Knowledge Foundation
Note

This work was supported by the Knowledge Foundation of Sweden, Grant Number 2010/0271. Additionally, Invest Northern Ireland is acknowledged for supporting this project under the Competence Centre Program Grant RD0513853 - Connected Health Innovation Centre.

Available from: 2015-05-26 Created: 2015-02-09 Last updated: 2017-05-30Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Lundström, JensJärpe, EricNugent, Christopher
By organisation
CAISR - Center for Applied Intelligent Systems Research
Signal ProcessingOther Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 361 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf