Situation determination with reusable situation specifications

G. Thomson, S. Terzis, P. Nixon

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (Scopus)

Abstract

Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. In both cases, the situations are tailored to the specific environment, and are therefore not transferable to other environments. Furthermore, situations are recognised at a low-level of granularity, which limits the scope of situation-aware applications. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation specications that can be easily extended to create new speficic situations, and immediately deployed without the need of an environment expert. A proposed architecture of an accompanying situation determination middleware is provided, as well as an analysis of a prototype implementation.
LanguageEnglish
Title of host publicationFourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006
PublisherIEEE
Pages620-623
Number of pages3
ISBN (Print)0769525202
DOIs
Publication statusPublished - 2006

Fingerprint

Ubiquitous computing
Middleware
Learning systems
Specifications
Sensors

Keywords

  • situation determination
  • pervasive computing
  • mobile computing
  • mobile devices
  • middleware

Cite this

Thomson, G., Terzis, S., & Nixon, P. (2006). Situation determination with reusable situation specifications. In Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006 (pp. 620-623). IEEE. https://doi.org/10.1109/PERCOMW.2006.126
Thomson, G. ; Terzis, S. ; Nixon, P. / Situation determination with reusable situation specifications. Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006. IEEE, 2006. pp. 620-623
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Thomson, G, Terzis, S & Nixon, P 2006, Situation determination with reusable situation specifications. in Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006. IEEE, pp. 620-623. https://doi.org/10.1109/PERCOMW.2006.126

Situation determination with reusable situation specifications. / Thomson, G.; Terzis, S.; Nixon, P.

Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006. IEEE, 2006. p. 620-623.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

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AB - Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long training periods before the system can be used. In both cases, the situations are tailored to the specific environment, and are therefore not transferable to other environments. Furthermore, situations are recognised at a low-level of granularity, which limits the scope of situation-aware applications. This paper presents a novel approach to situation determination that attempts to overcome these issues by providing a reusable library of general situation specications that can be easily extended to create new speficic situations, and immediately deployed without the need of an environment expert. A proposed architecture of an accompanying situation determination middleware is provided, as well as an analysis of a prototype implementation.

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Thomson G, Terzis S, Nixon P. Situation determination with reusable situation specifications. In Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006. IEEE. 2006. p. 620-623 https://doi.org/10.1109/PERCOMW.2006.126