Earticle

초록

영어

A smart home (sometimes referred to as a smart house or eHome) is one that has highly advanced automatic systems. A smart home appears "intelligent" because its computer systems can monitor many aspects of daily life. Our research, presented in this paper, is based on a universal implementation model for the smart home. The “Home Intelligence” (HI) module of the smart home, offers important added-value to the intelligent behavior of the smart-home environment. The HI creates an integrated environment in which the Artificial Intelligence (AI) mechanism can infer and suitably react according to changing conditions and events. By identifying abnormal or unexpected events and, when necessary alerting the home’s occupants, the AI module can provide an immediate automatic response if desired. Because of the complexity of the systems, their diverse areas of control and supervision, the variety of information technologies and learning mechanisms, and the reasoning capabilities used in updating the information system, developers, suppliers and users must cooperate. Cooperation will be expressed by agreeing to anonymously transfer information from the client to the developer through the suppliers. The transferred information will include characteristics of abnormal events, which have actually occurred in reality (true life scenarios), and the responses of the smart home. This information is then analyzed and used for AI learning and to improve the system’s reasoning mechanisms. Collecting information from a large number of clients will allow for faster learning and updating of the home intelligence system. A simulation system was developed in order to illustrate the HI module. The simulation illustrates the learning and the reasoning processes as well as demonstrates the smart home’s responses to abnormal events.

목차

Abstract
 1. Introduction
  1.1. What is a Smart Home?
  1.2. Universal Implementation Model for the Smart Home
  1.3. OPM -Object-Process Methodology
 2. Home Intelligence (HI) - The Artificial Intelligence (AI) Engine
  2.1. Abnormal events – Identification, Response, Control and Updating of theLearning System
  2.2. Developers, Suppliers And Clients Of Artificial Intelligence Systems In SmartHomes
  2.3. Learning and Updating Abnormal Events data
 3. A Simulation System for Illustrating the HI Module
  3.1. Running the simulation and creating a database
  3.2. Training Process - Data Mining model
  3.3. Identifying Abnormal Events in Daily Activity
 4. Examples of Scenarios and Response Procedures
  4.1. Fire Scenario
  4.2. Monitoring an elderly person’s vital signs
 5. Conclusions
 References

키워드

저자

• David Bregman [ School of Business, The College of Management Academic Studies ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605