Abstract
Purpose - This paper aims to review the extant intelligent home specifications and put forward a new dimension for the specifications of intelligent home (IHS).
Design/methodology/approach - This study adopts a learning (bottom-up) algorithm which emphasizes the importance of learning and adaptability to the dynamic environmental changes in the IHS.
Findings - The study finds that the intelligent home has been characterized by automation, integration of facilities and communication. However, it is contended here that an intelligent home specification in such a hard-wired (top-down) approach cannot be sustained in the light of the continuous changes of user requirements. Hence, adaptation to users' needs must be encompassed in a system of home intelligence.
Research limitations/implications - This study provides a framework for all stakeholders to work for a common goal and a platform for benchmarking the performance of intelligent home in the long run.
Originality/value - This is the first to adopt the learning (bottom-up) algorithm in defining home intelligence.
| Original language | English |
|---|---|
| Pages (from-to) | 365-375 |
| Number of pages | 11 |
| Journal | Facilities |
| Volume | 24 |
| Issue number | 9-10 |
| DOIs | |
| Publication status | Published - 15 Jul 2006 |
| Externally published | Yes |
Keywords
- Automation
- Buildings
- Learning