GUIDED AB

Brief description

The aim of GUIDED AB is to develop a new control system for building automation and home networking that adapts itself autonomously to the needs of users and residents. Aided by self-learning mechanisms, use patterns are to be automatically recorded and analysed. As a result, building and home networking components will be controlled efficiently and in line with residents' needs.

The challenge

In the smart home of tomorrow, electrical appliances are to behave autonomously and work not just independently but also efficiently. In addition to monitoring, the appliances will also be controlled in response to energy prices. To achieve this, they will be connected to corresponding energy-management and marketplace systems, so that the dishwasher, for instance, switches on when there is plenty of electrical energy available and the electricity price is at its lowest. Resource-efficient buildings with smart building system control can hence play an important role in Germany's Energiewende. These systems, which are technologically very complex, place high demands on the internal and external networking capability of the control components, their degree of flexibility and configuration options.

Aim

The GUIDED AB project aims to explore innovative concepts for flexible building automation and home networking for smart residential buildings and to implement prototypes based on application scenarios. This means that new approaches must be developed for targeted recording and self-learning analysis of use patterns in order to achieve intuitive and foresighted control based on this data. Existing single solutions are to be integrated into a holistic system and operate in an independent and foresighted manner. The focus here is on simple operation and configuration of complex building control using, among other things, a virtual 3D model of houses or apartments (3D dual reality). Sensors and actuators are also to be included in order to create a hardware basis for the services in GUIDED AB. The aim is to develop mobile apps which consumers can use to individually organise their home appliances and to have them controlled via learning systems.

Technologies

Concepts for self-learning services will be developed in this project in order to capture and analyse use patterns. The project pursues a generic, open and expandable approach. This means that suppliers can add other components and services to the platform, expanding them successively. Together with the project partners' housing construction experts, application scenarios will be developed for energy efficiency, comfort, quality of life and security/safety in private homes. This will include both existing building systems, for instance, refurbishment projects, as well as new systems for new buildings.

Use case

Two test labs will be set up for component, integration and system testing. Following testing in the test labs, the applications will be put through their paces in a realistic test environment and then installed in a selected residential building.

Partners:Hager Electro GmbH & Co KG (project leader), Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, FH Dortmund - Institut für Kommunikationstechnik (IKT), INTERACTIVE Software Solutions GmbH, IS Predict GmbH, QBUS eNET GmbH & Co. KG, Scheer Management GmbH