IB Index: Developing a Standard Evaluation System for Intelligent Buildings

Abstract

Intelligent building is a rapidly growing market in the Architecture, Engineering, Construction, and Operation (AECO) industry that aims to deploy emerging technologies and leverage data-driven decision making during the whole building lifecycle. However, there is a lack of holistic understanding of intelligent buildings and more importantly, there is a gap in standard methods and criteria for evaluating intelligent buildings. Ambiguity in knowing what makes a building intelligent and how to unpack the complex concept of building intelligence limits building stakeholders’ abilities to decide what technologies to implement in their buildings and to measure the effectiveness of their initiatives and strategies. This research responded to the current gaps by identifying the main components of building intelligence and used that finding as a basis for developing a tool (called the IB Index) for intelligent building evaluation. To do this, I conducted mixed-methods research consisting of actor-network theory and grounded theory to form the research theoretical foundation as well as systematic literature review and case studies for data collection and analysis. This research contributes to the body of knowledge by documenting the process and the essential elements of a standard whole-building evaluation system (including the building intelligence evaluation criteria, ontology, building performance criteria, and the weighting system). As the main outcome of the research, the IB Index provides the framework and evaluation capabilities (presented in three supplementary PDF documents) to understand the array of technological capabilities and intelligent building workflows and best practices and also to identify their impacts on building performance. Overall, the IB Index enables project stakeholders to evaluate, prove, and improve their building intelligence throughout its lifecycle.