Human activity prediction in smart home environments with LSTM neural networks

N. Tax

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

16 Citations (Scopus)


In this paper, we investigate the performance of several sequence prediction techniques on the prediction of future events of human behavior in a smart home, as well as the timestamps of those next events. Prediction techniques in smart home environments have several use cases, such as the real-time identification of abnormal behavior, identifying coachable moments for e-coaching, and a plethora of applications in the area of home automation. We give an overview of several sequence prediction techniques, including techniques that originate from the areas of data mining, process mining, and data compression, and we evaluate the predictive accuracy of those techniques on a collection of publicly available real-life datasets from the smart home environments domain. This contrast our work with existing work on prediction in smart homes, which often evaluate their techniques on a single smart home instead of a larger collection of logs. We found that LSTM neural networks outperform the other prediction methods on the task of predicting the next activity as well as on the task of predicting the timestamp of the next event. However, surprisingly, we found that it is very dependent on the dataset which technique works best for the task of predicting a window of multiple next activities.
Original languageEnglish
Title of host publicationProceedings of the 14th International Conference on Intelligent Environments (IE)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)978-1-5386-6844-3
ISBN (Print)978-1-5386-6845-0
Publication statusPublished - 27 Dec 2018
Event14th International Conference on Intelligent Environments, IE 2018 - Rome, Italy
Duration: 25 Jun 201828 Jun 2018


Conference14th International Conference on Intelligent Environments, IE 2018
Abbreviated titleIE'18
Internet address


  • Activity prediction
  • Neural networks
  • Process mining
  • Sequence prediction
  • Smart home environments

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