Human Behavior Recognition in a Smart Home by Artificial Neural Networks

Authors

  • Narut Butploy
  • Pakin Maneechot
  • Nivadee Klungsida

Keywords:

Recognition, Intelligent Home Systems, Artificial Neural Networks, Smart Home

Abstract

This research aimed to find a model for predicting human behaviors using electronic monitoring system. The experiment study used WEKA, a well-established data mining model applied to real-world problem solving. The study focused on the network configuration of ANN. The results showed that a 2-layered neural network gives the best learning outcomes. However, the learning outcome was not good enough, but study still showed  that neural network techniques can be used to help recognize and predict behaviors, and can be used to predict information from other intelligent systems, such as smart home systems.

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Published

30 December 2020

How to Cite

Butploy, N. ., Maneechot, P. ., & Klungsida, N. (2020). Human Behavior Recognition in a Smart Home by Artificial Neural Networks. Journal of Renewable Energy and Smart Grid Technology, 15(2), 49–54. Retrieved from https://ph01.tci-thaijo.org/index.php/RAST/article/view/240689

Issue

Vol. 15 No. 2 (2020): July-December

Section

Articles

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