A Weight Factor Algorithm for Activity Recognition Utilizing a Lattice-Based Reasoning Structure

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper introduces a new weight factor method for lattice-based evidential fusion for the purposes of activity recognition within smart environments. In calculating the weight factor between the lattice layers, the uncertainty information derived from sensors along with the sensor context has been taken into consideration. According to the experimental results, the proposed weight factor method has the ability to effectively incorporate the uncertainty into the inference process, and subsequently infer complex activities such as a preparing lunch activity with an accuracy of 65.20%.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages2
Publication statusPublished - 2011
EventTools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on -
Duration: 1 Jan 2011 → …

Conference

ConferenceTools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Period1/01/11 → …

Fingerprint

Sensors
Fusion reactions
Uncertainty

Keywords

  • Evidence Theory
  • Activity Recognition
  • Lattice-Based Reasoning Structure

Cite this

@inproceedings{ace9967a85184582bd08ec134f527d40,
title = "A Weight Factor Algorithm for Activity Recognition Utilizing a Lattice-Based Reasoning Structure",
abstract = "This paper introduces a new weight factor method for lattice-based evidential fusion for the purposes of activity recognition within smart environments. In calculating the weight factor between the lattice layers, the uncertainty information derived from sensors along with the sensor context has been taken into consideration. According to the experimental results, the proposed weight factor method has the ability to effectively incorporate the uncertainty into the inference process, and subsequently infer complex activities such as a preparing lunch activity with an accuracy of 65.20{\%}.",
keywords = "Evidence Theory, Activity Recognition, Lattice-Based Reasoning Structure",
author = "Jing Liao and Yaxin Bi and Nugent, {Chris D.}",
year = "2011",
language = "English",
booktitle = "Unknown Host Publication",

}

Liao, J, Bi, Y & Nugent, CD 2011, A Weight Factor Algorithm for Activity Recognition Utilizing a Lattice-Based Reasoning Structure. in Unknown Host Publication. Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on, 1/01/11.

A Weight Factor Algorithm for Activity Recognition Utilizing a Lattice-Based Reasoning Structure. / Liao, Jing; Bi, Yaxin; Nugent, Chris D.

Unknown Host Publication. 2011.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A Weight Factor Algorithm for Activity Recognition Utilizing a Lattice-Based Reasoning Structure

AU - Liao, Jing

AU - Bi, Yaxin

AU - Nugent, Chris D.

PY - 2011

Y1 - 2011

N2 - This paper introduces a new weight factor method for lattice-based evidential fusion for the purposes of activity recognition within smart environments. In calculating the weight factor between the lattice layers, the uncertainty information derived from sensors along with the sensor context has been taken into consideration. According to the experimental results, the proposed weight factor method has the ability to effectively incorporate the uncertainty into the inference process, and subsequently infer complex activities such as a preparing lunch activity with an accuracy of 65.20%.

AB - This paper introduces a new weight factor method for lattice-based evidential fusion for the purposes of activity recognition within smart environments. In calculating the weight factor between the lattice layers, the uncertainty information derived from sensors along with the sensor context has been taken into consideration. According to the experimental results, the proposed weight factor method has the ability to effectively incorporate the uncertainty into the inference process, and subsequently infer complex activities such as a preparing lunch activity with an accuracy of 65.20%.

KW - Evidence Theory

KW - Activity Recognition

KW - Lattice-Based Reasoning Structure

M3 - Conference contribution

BT - Unknown Host Publication

ER -