Design and development of intelligent and easy home/office system - Zainal Abidin, Muhammad Shukri; Yusof, Rubiyah; Khor , Eik Fun; Zamzuri, Mohamad Fairol (Faculty of Electrical Engineering, 2006)
An Intelligent Home (I-Home) System is envisioned as the by-product of pervasive computing and the availability of smart computer technology which making human interaction with the system a better home life experience. By the year 2020, home activities in Malaysia will be heavily influenced by interactive information and smart control systems. I-Home can provide homeowner a smart environment that monitor and control household functions. It can provide a gateway to communicate with the outside world through web-based system incorporated into the home. Using a web based control system, homeowner can quickly look into home to see live video and control lighting. It anticipates forecasted weather, thief prevention and utility costs. Therefore the objectives of Intelligent Home System are comprises to two main objectives. The first objective is to develop master software based on Artificial Intelligent (AI) technique which is capable of integrating remote control and monitoring appliances and devices via the internet and the second objective is to design an intelligent sensor system using fuzzy logic and neural network to overcome false alarms occurrence as well as to provide home automation. The major phases of the research involves the development of intelligent sensoring system using AI techniques, development of home automation control, design and development of intelligent master list software, develop the control and communication protocols and development of integration module. The final phase is design and implementation of a prototype of the intelligent home system. The prototype develops in CAIRO premises shows the ability of computer and communication technology in building the automated home system that function autonomously by using artificial intelligent engine. Results proof that combination of fuzzy logic and neural network can improve the controller performance with less human dependence.