Artificial Intelligence Techniques for Advanced Smart Home Implementation
نویسنده
چکیده
Smart-home concept has been around for many years and played a very important part in the design and implementation of future houses. Early research focus on the control of home appliances but current trends are moving into a creation of self-thinking home. In the recent years many research projects were performed utilizing artificial intelligence tools and techniques. This article highlights research projects employing multi-agent system, action prediction, artificial neural network, fuzzy logic and reinforcement learning. It is found that the combination of tools and techniques are crucial for successful implementation. This article provides platform for future relative studies between different algorithms, architectures and serves as a reference point for developing more cutting edge smart home technologies.
منابع مشابه
Smart Home Intelligence - The eHome that Learns
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 add...
متن کاملIncorporating Temporal Reasoning into Activity Recognition for Smart Home Residents
Smart environments rely on artificial intelligence techniques to make sense of the sensor data that is collected in the environment and to use the information for data analysis, prediction, and event automation. In this paper we discuss an important smart environment technology – resident activity recognition. This technology is beneficial for health monitoring of a smart environment resident b...
متن کاملInterleaved Activity Recognition for Smart Home residents
Smart environments rely on artificial intelligence techniques to make sense of the sensor data and to use the information for recognition and tracking activities. However, many of the techniques that have been developed are designed for simplified situations. In this paper we discuss a more complex situation, namely recognizing activities when they are interweaved in complex and realistic scena...
متن کاملModeling Smart Homes for Prediction Algorithms
This paper reviews the goals of the Domoweb project and the solutions adopted to achieve them. As a result we enjoy a great support to develop smart home techniques and solutions. As a consequence of the acquired experiences a Smart home model is proposed as a division of four main categories. In relation with the smart home model, we show the essential features a smart environment prediction a...
متن کاملHardware Simulation of Pattern Matching and Reinforcement Learning to Predict the User next Action of Smart Home Device Usage
Future Smart-Home device usage prediction is a very important module in artificial intelligence. The technique involves analyzing the user performed actions history and apply mathematical methods to predict the most feasible next user action. Unfortunately most of the techniques tend to ignore the adaptation to the user preferred actions and the relation between the actions and the state of the...
متن کامل