De Paola, A, Ferraro, P, Lo Re, G, Morana, M and Ortolani, M (2020) A fog-based hybrid intelligent system for energy saving in smart buildings. Journal of Ambient Intelligence and Humanized Computing, 11 (7). pp. 2793-2807. ISSN 1868-5145

[thumbnail of 0165.pdf]
Preview
Text
0165.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

Download (1MB) | Preview

Abstract

In recent years, the widespread diffusion of pervasive sensing devices and the increasing need for reducing energy consumption have encouraged research in the energy-aware management of smart environments. Following this direction, this paper proposes a hybrid intelligent system which exploits a fog-based architecture to achieve energy efficiency in smart buildings. Our proposal combines reactive intelligence, for quick adaptation to the ever-changing environment, and deliberative intelligence, for performing complex learning and optimization. Such hybrid nature allows our system to be adaptive, by reacting in real time to relevant events occurring in the environment and, at the same time, to constantly improve its performance by learning users’ needs. The effectiveness of our approach is validated in the application scenario of a smart home by extensive experiments on real sensor traces. Experimental results show that our system achieves substantial energy savings in the management of a smart environment, whilst satisfying users’ needs and preferences.

Item Type: Article
Additional Information: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Springer at http://doi.org/10.1007/s12652-019-01375-2 - please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: Ambient intelligence, Fuzzy systems, Fog computing, Energy efficiency
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Natural Sciences > School of Computing and Mathematics
Depositing User: Symplectic
Date Deposited: 06 Aug 2019 08:33
Last Modified: 26 Jul 2020 01:30
URI: https://eprints.keele.ac.uk/id/eprint/6624

Actions (login required)

View Item
View Item