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PSINES: Activity and Availability Prediction for Adaptive Ambient Intelligence

Authors:

Grégoire Lefebvre,

Fano Ramparany,

James L. CrowleyAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 15, Issue 1

Article No.: 1, Pages 1 - 12

https://doi.org/10.1145/3424344

Published: 31 December 2020 Publication History

Abstract

Autonomy and adaptability are essential components of ambient intelligence. For example, in smart homes, proactive acting and occupants advising, adapted to current and future contexts of living, are essential to go beyond limitations of previous domotic services. To reach such autonomy and adaptability, ambient systems need to automatically grasp their users’ ambient context. In particular, users’ activities and availabilities for communication are valuable pieces of contextual information that can help such systems to adapt to user needs and behaviours. While significant research work exists on activity recognition in homes, less attention has been given to prediction of future activities, as well as to availability recognition and prediction in general. In this article, we investigate several Dynamic Bayesian Network (DBN) architectures for activity and availability prediction of occupants in homes, including our novel model, called Past SItuations to predict the NExt Situation (PSINES). This predictive architecture utilizes context information, sensor event aggregations, and latent user cognitive states to accurately predict future home situations based on previous situations. We experimentally evaluate PSINES, as well as intermediate DBN architectures, on multiple state-of-the-art datasets, with prediction accuracies of up to 89.52% for activity and 82.08% for availability on the Orange4Home dataset.

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Cited By

Song XWang DQuek CTan AWang Y(2023)Spatial-temporal episodic memory modeling for ADLs: encoding, retrieval, and predictionComplex & Intelligent Systems10.1007/s40747-023-01298-810:2(2733-2750)Online publication date: 14-Dec-2023
https://doi.org/10.1007/s40747-023-01298-8
Mohamed MEl-Kilany AEl-Tazi N(2022)Future Activities Prediction Framework in Smart Homes EnvironmentIEEE Access10.1109/ACCESS.2022.319761810(85154-85169)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3197618

Index Terms

PSINES: Activity and Availability Prediction for Adaptive Ambient Intelligence
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing theory, concepts and paradigms
      1. Ambient intelligence
2. Mathematics of computing
  1. Probability and statistics
    1. Probabilistic representations
      1. Bayesian networks

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Information & Contributors

Information

Published In

cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 15, Issue 1

March 2020

79 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/3446624

Editor:
Bashar Nuseibeh
The Open University, UK, 8 Lero, Ireland

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 December 2020

Accepted: 01 September 2020

Revised: 01 June 2020

Received: 01 September 2019

Published in TAAS Volume 15, Issue 1

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Cited By

Song XWang DQuek CTan AWang Y(2023)Spatial-temporal episodic memory modeling for ADLs: encoding, retrieval, and predictionComplex & Intelligent Systems10.1007/s40747-023-01298-810:2(2733-2750)Online publication date: 14-Dec-2023
https://doi.org/10.1007/s40747-023-01298-8
Mohamed MEl-Kilany AEl-Tazi N(2022)Future Activities Prediction Framework in Smart Homes EnvironmentIEEE Access10.1109/ACCESS.2022.319761810(85154-85169)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3197618

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