A deep learning and gamification approach to improving human-building interaction and energy efficiency in smart infrastructure
Applied Energy(2019)
Abstract
•Discrete Choice Models model occupant actions through machine learning algorithms.•Deep Learning shows outstanding potential for sequential decision making.•Artificial Intelligence can generate high dimensional dynamic occupancy usage data.•Gamification in human-centric cyber-physical systems promotes energy efficiency.•Participation in social game communicates usage data and facilitates forecasting.
MoreTranslated text
Key words
Artificial intelligence for humans-in-the-loop cyber-physical systems,Human-building interaction,Deep learning,Discrete choice models,Game theory
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined