Development of a conceptual model for the selection of intelligent building systems

With the availability of a myriad of intelligent building components or products in the market, the decision to choose between them becomes significant and crucial in the configuration of building alternative. This results in placing the decision makers in the selection [`]dilemma'. This paper presents the development of a conceptual model for the selection of intelligent building systems which aims at assisting the decision makers to select the most appropriate combination of intelligent building components. The paper commences by reviewing the literature on intelligent building research. A survey is conducted to examine the criticality of selection attributes. Findings of this survey enrich the field of intelligent building research in at least two ways. Firstly, it widens the understanding of the factors, as well as their degree of importance, in affecting the selection of intelligent building systems and components. Second, the identified selection attributes form a conceptual framework which can be used to guide the selection of intelligent building components.

[1]  Wai Lok Chan,et al.  Intelligent Building Systems , 1999, The International Series on Asian Studies in Computer and Information Science.

[2]  Shengwei Wang,et al.  Integrating Building Management System and facilities management on the Internet , 2002 .

[3]  A. Kujuro,et al.  Systems evolution in intelligent buildings , 1993, IEEE Communications Magazine.

[4]  Marja-Liisa Siikonen Customer service in an elevator system during up-peak , 1997 .

[5]  Peter E.D. Love,et al.  Industry-centric benchmarking of information technology benefits, costs and risks for small-to-medium sized enterprises in construction , 2004 .

[6]  Edward Finch Is IP everywhere the way ahead for building automation , 2001 .

[7]  H. Arkin,et al.  Evaluating intelligent buildings according to level of service systems integration , 1997 .

[8]  Rabee M. Reffat,et al.  Environmental Comfort Criteria: Weighting and Integration , 2001 .

[9]  James Jaccard,et al.  Statistics for the Behavioral Sciences , 1983 .

[10]  Ren C. Luo,et al.  Fire detection and isolation for intelligent building system using adaptive sensory fusion method , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[11]  Richard Fellows,et al.  Intelligent building systems in Hong Kong offices , 2000 .

[12]  Jane Gradwohl Nash,et al.  Doing Data Analysis with SPSS: Version 14.0 (with CD-ROM) (Doing Data Analysis with SPSS) , 2005 .

[13]  Rabee M. Reffat,et al.  Expert System for Environmental Quality Evaluation , 2001 .

[14]  Rachel Becker,et al.  Research and development needs for better implementation of the performance concept in building , 1999 .

[15]  B.M. Flax Intelligent buildings , 1991, IEEE Communications Magazine.

[16]  David Dugdale,et al.  Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach , 2001 .

[17]  Makarand Hastak Advanced automation or conventional construction process , 1998 .

[18]  A. D. Henriksen,et al.  A practical R&D project-selection scoring tool , 1999 .

[19]  Franco K.T. Cheung,et al.  Multi-criteria evaluation model for the selection of architectural consultants , 2002 .

[20]  Wolfgang F. E. Preiser,et al.  Intelligent office building performance evaluation , 2002 .

[21]  Gregg R. Yost,et al.  Configuring elevator systems , 1996, Int. J. Hum. Comput. Stud..

[22]  Kim Bjarne Wittchen,et al.  Assessment of energy and natural resources conservation in office buildings using TOBUS , 2002 .

[23]  Henry Feriadi,et al.  The use of performance-based simulation tools for building design and evaluation — a Singapore perspective , 2000 .

[24]  Robert H. Carver,et al.  Doing Data Analysis with SPSS Version 18.0 , 2008 .

[25]  A.J.F. Rutten,et al.  Sky luminance research imperative for adequate control of temporary supplementary artificial lighting installations , 1994 .

[26]  Francisco Herrera,et al.  A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems , 2005, Eng. Appl. Artif. Intell..

[27]  Eric Loe Proving the benefits ‐ justifying the costs of intelligent systems , 1996 .

[28]  M. Atif,et al.  Energy performance of daylight-linked automatic lighting control systems in large atrium spaces: report on two field-monitored case studies , 2003 .

[29]  Heng Li,et al.  Construction Partnering Process and Associated Critical Success Factors: Quantitative Investigation , 2002 .

[30]  Jun Yang,et al.  Decision Support to the Application of Intelligent Building Technologies , 2001 .

[31]  Earl Reinhold Carlson,et al.  Understanding building automation systems : direct digital control, energy management, life safety, security/access control, lighting, building management programs , 1991 .

[32]  Ajith Abraham,et al.  Feature deduction and ensemble design of intrusion detection systems , 2005, Comput. Secur..

[33]  M. Aygün Comparative Performance Appraisal by Multiple Criteria for Design Alternatives , 2000 .

[34]  Rick Best,et al.  Design and Construction: Building in Value , 2002 .

[35]  Wan Ki Chow,et al.  Evacuation with smoke control for atria in green and sustainable buildings , 2005 .

[36]  Edward Finch Remote building control using the Internet , 1998 .

[37]  D. M. Gann High-technology buildings and the information economy , 1990 .

[38]  Olfa Kanoun,et al.  System Technologies: Sensor Systems in Intelligent Buildings , 2008 .

[39]  Shengwei Wang,et al.  Model-based optimal control of VAV air-conditioning system using genetic algorithm , 2000 .

[40]  C. K. Y. Lin,et al.  Hospital lift system simulator: A performance evaluator-predictor , 2003, Eur. J. Oper. Res..

[41]  Xia Rui-li On Intelligent Building , 2008 .

[42]  Shunji Tanaka,et al.  Dynamic optimization of the operation of single-car elevator systems with destination hall call registration: Part I. Formulation and simulations , 2005, Eur. J. Oper. Res..

[43]  Danny H.W. Li,et al.  Evaluation of lighting performance in office buildings with daylighting controls , 2001 .

[44]  Paul C. Ivey,et al.  An R&D options selection model for investment decisions , 2005 .

[45]  Steven T. Bushby,et al.  BACnetTM: a standard communication infrastructure for intelligent buildings , 1997 .

[46]  Shengwei Wang,et al.  Intelligent building research: a review , 2005 .

[47]  Yiqun Pan,et al.  Measurement and simulation of indoor air quality and energy consumption in two Shanghai office buildings with variable air volume systems , 2003 .

[48]  M. Azegami,et al.  A systematic approach to intelligent building design , 1993, IEEE Communications Magazine.

[49]  A.T.P. So,et al.  Building automation in the 21st century , 1997 .

[50]  George Ofori,et al.  Building waste assessment score: design-based tool , 2004 .

[51]  J Franklin,et al.  Optimisation of a three-colour luminescent solar concentrator daylighting system , 2004 .