A Distributed Intelligent Building Agent Language (DIBAL)

We describe a new approach to Intelligent Building systems, that utilises an intelligent agent approach to autonomously governing the building environment. We discuss the role of learning in building control systems, and contrast this approach with existing IB solutions. We explain the importance of acquiring information from sensors, rather than relying on pre-programmed models, to determine user needs. We describe how our architecture, consisting of distributed embedded agents, utilises sensory information to learn to perform tasks related to user comfort, energy conservation, safety and monitoring functions. We show how these agents, employing a behaviour-based approach derived from robotics research, are able to continuously learn and adapt to individuals within a building, whilst always providing a fast, safe response to any situation. Finally, we show how such a system could be used to provide support for older people, or people with disabilities, allowing them greater independence and quality of life.

FIPA is an IEEE Computer Society standards organization that promotes agent-based technology and the interoperability of its standards with other technologies. In the design phase of Intelligent Buildings, it is essential to manage many services and facilities, to do this, multi-agent systems are a good tool to manage them. In this paper, we will gereneral description of the features and elements of multiagent systems described by Foundation for Intelligent Physical Agents (FIPA). Secondly, we will focus on the architectures of these multi-agent systems. And finally, we will propose a multi-agent system design to see the application in the design of a detached house where the lighting, air conditioning and security systems will be integrated.

In order to support personalized people comfort and building energy efficiency as well as safety, emergency, and context-aware information exchange scenarios, next-generation buildings will be smart. In this paper we propose an agent-oriented decentralized and embedded architecture based on wireless sensor and actuator networks (WSANs) for enabling efficient and effective management of buildings. The main objective of the proposed architecture is to fully support distributed and coordinated sensing and actuation operations. The building management architecture is implemented at the WSAN side through MAPS (Mobile Agent Platform for Sun SPOTs), an agent-based framework for programming WSN applications based on the Sun SPOT sensor platform, and at the base station side through an OSGi-based application. The proposed agent-oriented architecture is demonstrated in a simple yet effective operating scenario related to monitoring workstation usage in computer laboratories/offices. The high modularity of the proposed architecture allows for easy adaptation of higher-level application-specific agents that can therefore exploit the architecture to implement intelligent building management policies.

2008 IEEE International Conference on Service Operations and Logistics, and Informatics, 2008

Intelligent buildings can bring a great deal of benefits to the commercial sector as well as the occupants living in the building. It has been identified in the prior research that energy efficiency is pivotal to energy saving while occupant's well-being is a major contributor to overall work productivity. Among the various technologies and methods for addressing these two issues, agent technology has gained increasing attentions in developi?g such an intelligent work environment in recent years, due to Its capability to tackle complex tasks. In this paper, we present a multi-agent system that acts as an act-on to the existing Building Management System (BMS) and requires input from wireless sensor network and policy management, with the aims to dynamically configure building facilities to meet the requirements of both building energy efficiency and personalised work environment.

We describe a new application domain for intelligent autonomous systems – intelligent buildings. We show how a building can be regarded as a machine and how behaviour-based principles first proposed by Brooks for mobile-robot control can be applied to enable autonomous intelligent-building agents to adapt their control to suit the occupants. In other words we will argue that "an intelligent building is a robot that we live inside". We present a novel approach to the implementation of Intelligent Buildings based on a multi embedded-agent architecture comprising a low-level behaviour based reactive layer together with a high- level deliberative layer based on evidential learning (a case-like learning mechanism). We also present a hierarchical agent architecture in which mobile agents (residing on body wearable devices) and fixed agents (residing in buildings) can be integrated, opening new commercial and personal possibilities. We discuss how this architecture is being implemented, using a combination of IP and Lonworks networking technology together with a Java programming environment. We consider future directions of this work, in particular how it might play a key role in intelligent interactive environments enabled by emerging technologies such as mobile phones and embedded-internet devices.