Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Weighting connections between different layers within a lattice structure is an important issue in the process of modeling activity recognition within smart environments. Weights not only play an important role in propagating the relational strengths between layers in the structure, they can be capable of aggregating uncertainty derived from sensors along with the sensor context into the overall process of activity recognition. In this paper we present two weight factor algorithms and experimental evaluation. According to the experimental results, the proposed weight factor methods have a better performance of reasoning the complex and simple activity than other methods.
LanguageEnglish
Title of host publicationKnowledge Science, Engineering and Management Lecture Notes in Computer Science
Pages365-376
Publication statusPublished - 2011

Fingerprint

Fusion reactions
Sensors
Uncertainty

Keywords

  • Dempster-Shafer theory of evidence
  • Activity Recognition
  • Sensor Fusion

Cite this

Liao, J., Bi, Y., & Nugent, C. D. (2011). Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. In Knowledge Science, Engineering and Management Lecture Notes in Computer Science (pp. 365-376)
Liao, Jing ; Bi, Yaxin ; Nugent, Chris D. / Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. Knowledge Science, Engineering and Management Lecture Notes in Computer Science. 2011. pp. 365-376
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Liao, J, Bi, Y & Nugent, CD 2011, Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. in Knowledge Science, Engineering and Management Lecture Notes in Computer Science. pp. 365-376.

Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. / Liao, Jing; Bi, Yaxin; Nugent, Chris D.

Knowledge Science, Engineering and Management Lecture Notes in Computer Science. 2011. p. 365-376.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion

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AU - Bi, Yaxin

AU - Nugent, Chris D.

PY - 2011

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N2 - Weighting connections between different layers within a lattice structure is an important issue in the process of modeling activity recognition within smart environments. Weights not only play an important role in propagating the relational strengths between layers in the structure, they can be capable of aggregating uncertainty derived from sensors along with the sensor context into the overall process of activity recognition. In this paper we present two weight factor algorithms and experimental evaluation. According to the experimental results, the proposed weight factor methods have a better performance of reasoning the complex and simple activity than other methods.

AB - Weighting connections between different layers within a lattice structure is an important issue in the process of modeling activity recognition within smart environments. Weights not only play an important role in propagating the relational strengths between layers in the structure, they can be capable of aggregating uncertainty derived from sensors along with the sensor context into the overall process of activity recognition. In this paper we present two weight factor algorithms and experimental evaluation. According to the experimental results, the proposed weight factor methods have a better performance of reasoning the complex and simple activity than other methods.

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KW - Activity Recognition

KW - Sensor Fusion

M3 - Chapter

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EP - 376

BT - Knowledge Science, Engineering and Management Lecture Notes in Computer Science

ER -

Liao J, Bi Y, Nugent CD. Weight Factor Algorithms for Activity Recognition in Lattice-Based Sensor Fusion. In Knowledge Science, Engineering and Management Lecture Notes in Computer Science. 2011. p. 365-376