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ThinkHome: Improved energy efficiency based on artificial intelligence in future homes
ThinkHome is a networked controlled home of the future with the ultimate goal to optimise energy efficiency and user comfort at the same time. On this way, smart interaction between all building services is of utmost importance. Goals of this project include the definition of a comprehensive knowledge base that holds all relevant building data, the evaluation of control strategies based on artificial intelligence and machine learning, as well as agent based software engineering.
Titel und Synopse
ThinkHome ist ein vernetztes, autonom gesteuertes Haus der Zukunft, das der Optimierung der Energieeffizienz und der Verbesserung des Nutzerkomforts dient. Das intelligente Zusammenspiel aller Haustechnikkomponenten ist hierbei von höchster Bedeutung. Zu den Projektinhalten zählen eine umfassende Wissenspräsentation aller in einem Gebäude vorkommenden Daten, der Einsatz von Methoden der künstlichen Intelligenz, maschinelles Lernen sowie agentenbasiertes Software Engineering.
Project description / tasks
Status
ongoing
Summary
Starting point / motivation
The application of automation technology to residential environments holds a lot of benefits. Still, much of the potential available in a typical present-day home automation system lies fallow since the control strategies linking sensors and actuators are not as flexible as they should be. Tuning such a system precisely to the requirements of its users and the characteristics of both building structure and building services equipment is a task reserved to those with specialist knowledge. Moreover, it is almost never done in full due to the large effort required. For the same reason, once the system is installed, necessary readjustments are foregone almost as a rule. The task gets even harder as more design disciplines are involved. Therefore, intelligent homes that utilize modern computer technology to autonomously govern and constantly adapt the building environment to optimize both user comfort and energy-consumption simultaneously are in dire need.
Contents and goals
ThinkHome is an incarnation of such an intelligent home of the future that utilizes artificial intelligence (AI) to improve control of home automation functions provided by dedicated automation systems. It is able to detect and utilize patterns to provide a better, more energy-efficient, yet comfort oriented, control of building functions. Primary targets are functions that require comparably high amounts of energy, such as those found in heating/ventilation and air-conditioning, and lighting/shading. For an optimization, the system must be capable of detecting user interactions and desires, to identify patterns in these data and to be able to learn and adapt to its environment. ThinkHome must therefore be able to perceive its environment, especially the home in which it is employed. It has to learn environmental parameters such as thermal inertia and combine this knowledge together with various parameters and data found in and around today's buildings (presence, occupancy, temperature, daylight …) to find an optimal strategy for controlling the environment.
Ultimate goal of the ambitious project is to prove that ThinkHome can fulfill all the demands mentioned above. This includes the definition of a knowledge base that holds all relevant data. This knowledge base is fundamental to enable our vision of optimized, AI based control strategies that allow maximizing energy efficiency. To maximize the usefulness of AI, different approaches have to be investigated and evaluated regarding their performance and output when both energy efficiency and user comfort are taken into account. An agent based framework is home for agents that act on behalf of users (avatars) and has the artificial control strategies embedded. Moreover, it provides access to the knowledge base and interfaces to the underlying building control systems. The project outcome will be verified by a prototype implementation that will be installed into an existing building automation model. Additionally, a simulation shall highlight both the applicability and benefits that ThinkHome holds in real world projects. From its beginning, all results of the ThinkHome project will be made available to the public through open workshops and via a dedicated project homepage.
ThinkHome is open for all!
Project partners
Project management
Univ.Prof. Dr. Wolfgang Kastner
Vienna University of Technology, Institute
of Computer-Aided Automation Automation Systems Group
Contact address
Technische Universität Wien, Rechnergestützte Automation
Univ. Prof. Dr. Wolfgang Kastner
E183/1, Treitlstr. 1-3
A-1040 Vienna
Tel.: +43 (1) 58801-18320
Fax:+43 (1) 58801-18391
E-Mail: k@auto.tuwien.ac.at
