Human behavior prediction for smart homes using deep learning

Sungjoon Choi, Eunwoo Kim, Songhwai Oh

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

40 Citations (Scopus)

Abstract

There is a growing interest in smart homes and predicting behaviors of inhabitants is a key element for the success of smart home services. In this paper, we propose two algorithms, DBN-ANN and DBN-R, based on the deep learning framework for predicting various activities in a home. We also address drawbacks of contrastive divergence, a widely used learning method for restricted Boltzmann machines, and propose an efficient online learning algorithm based on bootstrapping. From experiments using home activity datasets, we show that our proposed prediction algorithms outperform existing methods, such as a nonlinear SVM and k-means, in terms of prediction accuracy of newly activated sensors. In particular, DBN-R shows an accuracy of 43.9% (51.8%) for predicting newly activated sensors based on MIT home dataset 1 (dataset 2), while previous work based on the n-gram algorithm has shown an accuracy of 39% (43%) on the same dataset.

Original languageEnglish
Title of host publication22nd IEEE International Symposium on Robot and Human Interactive Communication
Subtitle of host publication"Living Together, Enjoying Together, and Working Together with Robots!", IEEE RO-MAN 2013
Pages173-179
Number of pages7
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event22nd IEEE International Symposium on Robot and Human Interactive Communication: "Living Together, Enjoying Together, and Working Together with Robots!", IEEE RO-MAN 2013 - Gyeongju, Korea, Republic of
Duration: 2013 Aug 262013 Aug 29

Publication series

NameProceedings - IEEE International Workshop on Robot and Human Interactive Communication

Other

Other22nd IEEE International Symposium on Robot and Human Interactive Communication: "Living Together, Enjoying Together, and Working Together with Robots!", IEEE RO-MAN 2013
Country/TerritoryKorea, Republic of
CityGyeongju
Period13/8/2613/8/29

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Human-Computer Interaction

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