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The purpose of this paper is to investigate the concepts of intelligent buildings (IBs), and the opportunities offered by the application of computer‐aided facilities management (CAFM) systems.

In this paper definitions of IBs are investigated, particularly definitions that are embracing open standards for effective operational change, using a questionnaire survey. The survey further investigated the extension of CAFM to IBs concepts and the opportunities that such integrated systems will provide to facilities management (FM) professionals.

The results showed variation in the understanding of the concept of IBs and the application of CAFM. The survey showed that 46 per cent of respondents use a CAFM system with a majority agreeing on the potential of CAFM in delivery of effective facilities.

The questionnaire survey results are limited to the views of the respondents within the context of FM in the UK.

Following on the many definitions of an IB does not necessarily lead to technologies of equipment that conform to an open standard. This open standard and documentation of systems produced by vendors is the key to integrating CAFM with other building management systems (BMS) and further harnessing the application of CAFM for IBs.

The paper gives experience‐based suggestions for both demand and supply sides of the service procurement to gain the feasible benefits and avoid the currently hindering obstacles, as the paper provides insight to the current and future tools for the mobile aspects of FM. The findings are relevant for service providers and operators as well.

This paper reports an investigation of the performance of a sample of office buildings in Hong Kong which were marketed as being intelligent. A summary review of literature charting the development of intelligent buildings and perspectives of what intelligence means when applied to office buildings provides a basis for the study. Adopting a fitness‐for‐purpose perspective, as the approach adopted most widely for evaluations, data on the buildings’ designs (incorporation of intelligence features), users’ requirements and occupants’ views of performance of their workplaces were collected via questionnaire surveys. Analysis followed the building ranking method adopted by Harrison. Results indicate that only a minority of the office buildings marketed as “intelligent” achieve the level of performance to match users’ and occupants’ requirements and so constitute business value intelligent buildings; the majority are underachieving.

Focuses on the first generation of intelligent buildings and tries to determine what benefits they have provided. Gives a brief perspective on developments in the USA, Japan and Europe and provides examples of intelligent buildings in Chicago, Tokyo and Paris. Identifies four classes of intelligent building.

The emergence of intelligent buildings is likely to impose significant demands on facilities managers into the twenty‐first century. Whether we choose the term intelligent or not, building intelligence permeates through every feature of the modern building. The capabilities of the facilities management team are tested not only in terms of their technological know‐how. Perhaps more importantly it is technological uncertainty and organizational change which are likely to demand more sophisticated approaches to building design, procurement, project management, team working and operations management. The work environment that the modern building facilitates is undergoing a transformation. There is evidence of a need for a new way of dealing with the uncertainties and ambiguities of the intelligent building. In turn, this demands a fundamentally new approach to educating the facilities manager of the future. Looks at two courses in intelligent buildings which serve quite different needs in the educational arena. Discusses the extent to which such courses will fulfil the needs of the marketplace in helping to deliver more productive working environments.

Within the building sector a lack of clarity in terminology does not help designers, clients or researchers. Non-domestic buildings have shown rapid increases in the use of advanced technology and control systems with varying drivers, many of which are labelled as intelligent. The term smart has been used interchangeably with intelligent without any clear distinction between the two. If the term Smart Buildings represented a separate, more advanced grouping, it would provide an opportunity to focus the future progress of non-domestic building development. The paper aims to discuss these issues.

Drawing upon academic and industrial literature and experience, this paper reviews the scope of Intelligent Buildings and the current available definitions of Smart Buildings to form a clear definition of both smart and Intelligent Buildings.

These definitions define the border between the intelligent and the (more advanced) Smart Building. The upper bound of the Smart Building is defined by (the future development of) the predictive building.

This work provides a clear focus which will allow the progression of the non-domestic building sector by providing guidance and aspiration, as well as providing a platform upon which a large amount of technical work can be based.

An intelligent building incorporates two key components: automated building control systems and information management control systems. Automated building control systems include energy management systems, automated security and fire systems, and network life‐support systems. Information management control systems include telecommunications, data networking, local area networks, and other short and long haul networks. When these systems are linked together with common wiring and central controls, the building becomes intelligent. The integration of these components in Infomart, a high‐tech facility located in Dallas, Texas, is described. The usage of these components by tenants, and their possible application to library buildings are discussed.

“Intelligent building” is a commonly used though little understood expression in the facilities arena. Explains that building, space and business management are the three main goals of an organization occupying a building. A cost/benefits model must examine efficiency and effectiveness productivity and the additional costs/disbenefits associated with intelligence. Identifies further three developing integration activities in the building development cycle – project, systems and services integration, and concludes that the “virtual building”, which maximizes both efficiency and effectiveness gains, is the ideal.

To date, assessment models for intelligent buildings have not been systematically investigated. Most of the existing studies have derived their findings from information technology (IT) perspectives and have not considered all factors including the architecture of the building and the necessities of IT as part of an integrated approach. This paper aims to bridge this gap.

Based on a review of recent literature, this paper identifies the principal factors of intelligent buildings, discusses various perspectives from the point of both architecture and IT, and provides a general model for assessment. This model has been applied in relation to a case study and the results have been analyzed by surveys.

The overall results from the case study were appropriate, thus reflecting the appropriateness of the proposed model. The conceptual model presents a roadmap for the assessment of intelligence in buildings. The research reported in this paper was carried out as a pilot study to determine an assessment system for intelligent buildings.

The elements of the proposed model provide a list of attributes for the intelligent buildings. This helps to ensure that the essential issues and factors are covered during the design and implementation phase in the construction industry. For academics, it provides a common language for them to discuss and study the factors crucial for the assessment of intelligence levels in buildings.

This study provides an integrated perspective of critical issues for intelligence assessment in the construction industry. It gives valuable information and guidelines that help the designers and constructors in one hand and the project managers on the other hand to construct the intelligent buildings in an effective way.

This paper aims to review the extant intelligent home specifications and put forward a new dimension for the specifications of intelligent home (IHS).

This study adopts a learning (bottom‐up) algorithm which emphasizes the importance of learning and adaptability to the dynamic environmental changes in the IHS.

The study finds that the intelligent home has been characterized by automation, integration of facilities and communication. However, it is contended here that an intelligent home specification in such a hard‐wired (top‐down) approach cannot be sustained in the light of the continuous changes of user requirements. Hence, adaptation to users' needs must be encompassed in a system of home intelligence.

This study provides a framework for all stakeholders to work for a common goal and a platform for benchmarking the performance of intelligent home in the long run.

This is the first to adopt the learning (bottom‐up) algorithm in defining home intelligence.

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, while 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.