Adaptive Building Intelligence - Welcome to the ABI Website

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Motivation

Intelligent learning systems have become increasingly common due to improvements in user comfort and security provided by automated robots and self-adapting systems. The field of autonomous building control systems at the Institute of Neuroinformatics(INI) has gained our research interest.
Novel building architectures have been gradually equipped with an entire communication network. Now, this establishes a new world of possibilities since internal building devices can programmed and controlled remotely. Depending on occupants' needs, such a programmable system could improve user comfort and save more energy than a manually controlled system. Currently, ordinary lighting controls systems require frequent maintenance such as replacement or re-calibration of sensors and effectors and furthermore depend on stationary building structures. Self-adapting systems can prevent these burdensome and costly tasks. However, this seemingly easy task is complicated since structural changes must be detected and incorporated in real-time.

Here at the INI, we developed a novel adaptive building intelligence (ABI) system that is built on the Open Services Gateway initiative (OSGi). The system incorporates regular sensors (i.e. presence, temperature, illumination, humidity)) and effectors (i.e. lights, window blinds, wall-switches) that can be assessed through a dedicated fieldbus network (LonWorks). The ABI system introduces a generic Multi-Agent-System (MAS) design that integrates the most credible information currently available from several device agent controllers (DACs). The building structure itself is a non-stationary environment where not only individual desires are constantly changing but also the physical structure (e.g. mobile walls in multi-office environments, integration or dismounting of devices).
However, a major obstacle for autonomously learning dynamic space behaviors and configurations is that sensors perceive and react very differently from the human brain. For instance, we perceive fog with a different luminance intensity than measured by sensors. Furthermore, ambient light levels change dramatically even with small atmospheric changes such as a momentary scattering of particles over the sun. Hence, different skylight levels can be found even under the same sunlight condition. Consequently, intelligent buildings (IBs) need to be flexible enough to react to such environmental changes. An additional difficulty is that user instructions are next to their sparseness not always self-consistent and thus make learning behavior tedious [Diploma Thesis, Fall 05, Stephan K. Nufer and Mathias Buehlmann].

IB Goals

Our goal is the development of an IB that is adaptive to real users and also one that takes continuously fluctuating climatic factors into account. An intelligence building (IB) should:

Not disturb occupants: User wishes are upper priority. For instance: Blind motor noises, flashing or flickering lights, etc. should be minimized. User desires must be manually configurable and should not end up into opposing actions.
Be reliable: An IB application that would suddenly stop controlling an environment because of a network failure would ultimately result in discomfort.
Minimize energy consumption: Decrease the energy consumption, without affecting the user comfort (especially visual comfort). Broadly speaking we can say that the system must provide a reasonable payback period.
Incorporate all available sensor information: In order to enhance the predictions, an IB should consider all possible sensory information that can be received from an environment. Since the bigger the information flow the better adequately a building can be controlled (Multi-sensor environment).