Achieving Smarter Buildings and More Efficient Facilities Management: The Implementation of Big Data

Achieving Smarter Buildings and More Efficient Facilities Management: The Implementation of Big Data

Mary-Catherine Greene (Glenveagh Properties Plc, Ireland), Daniel Clarke-Hagan (Institute of Technology Sligo, Sligo, Ireland) and Michael Curran (Queen's University, Belfast, UK)
DOI: 10.4018/IJDIBE.2020070101

Abstract

As buildings become more complex, smarter, interconnected, and self-reporting, can technologies be used to the advantage of the end-user and society? This study looks to determine if implementing big data can improve sustainability and increase efficiency in facilities management. Big data, the internet of things (IoT), their application in the construction industry, connection to sustainability, and impact on facilities management are researched. The research employs a mixed-methods approach with critical literature review, primary qualitative research by interviews, and quantitative data research by questionnaire with assessment through mind mapping and SPSS statistical analysis. Key findings identify an industry concept of big data, the IoT, BIM as a primary data contributor on AEC projects, with technology being most assistive to inception and design phases and improving decision making. Implications for industry arise from unrelated usage and misunderstanding of terminology. The study identifies space for further research into the topic.
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Introduction

Big data is becoming a buzzword across all industries these days, however, what it is, is not easily defined due to it having numerous associated meanings all built around a concept more than a definition. Big Data, is described as colossal amounts of detailed digital information or all information not normally circulating within a company as identified by (Russom, 2011) and (Finley, Blaeser, & Djavairian, 2015), while others propose big data is big data analytics; information filled with variety, volume, shared at high speed and used in various forms, thus declaring the Vs (volume, velocity, variety) the core of big data and big data analytics while arguing over the number of Vs in big data (Russom, 2011), (IBM, 2013), (Zhou, Fu, & Yang, 2016), (Herschel & Miori, 2017), (Kaur & Sood, 2017). These explanations of big data assist with understanding what it is and indicate that computer technology and business sectors are driving the interpretation of the subject. Partnering big data, Information Communication Technology, (ICT) has introduced the Internet of Things (IoT). Similarly the IoT has multiple explanations as to what it is, with it described as the interconnectedness of objects, the application of connecting devices through the internet or the use of sensor application to collect and share data (Hanus & Harris, 2013), (Ahsan & Bais, 2016), (Botta, de Donato, Persico, & Pescape, (2016)), (Cavalcante, et al., 2016). Like many new advancements, big data and IoT are developing concepts and although the concepts are realised and in use in industries, such as business, manufacturing, information technology and robotics, they are still in their infancy and are continually developing. In the construction industry the IoT is making headway and is driven by sub-sectors such as energy, mechanical and electrical and facilities management, primarily through the employment of Building Management Systems (BMS), (Lin, et al., 2015), (Deng, Zhang, Ren, & Liang, 2016), (Munshi & Mohamed, 2017) yet there is limited research into how the IoT and big data can be applied within the construction industry. Justification for the research stems from the preliminary empirical research identifying gaps in knowledge surrounding big data, its application to the construction industry, project phases, design, information sharing, project collaboration, the linking of technology platforms and how applications can improve sustainability. The study’s hypothesis proposes that big data can be used to gain knowledge in relation to the performance of existing projects, which can then be used as the basis for the design of new smart buildings, promoting sustainability from project outset, which in turn allows for more efficient facilities management during operation, ensuring sustainability across all project phases, thus proposing that big data can lead to smarter buildings and more efficient facilities management. The study looks to fill these knowledge gaps and to provide essential information for the industry through a mixed methods research approach combining literature review, interviews and questionnaire.

Research Methodology

Generating from an interpretivist paradigm, this study uses a sequential exploratory mixed methods research approach. This approach combines an in-depth critical literature review, examining themes including big data, smart buildings, the IoT, efficiency, Facilities Management, sustainability and technology both in general and in the context of construction. This empirical study of existing research assists in determining existing opinions and revealing gaps in the knowledge. Expanding on the literature review qualitative data is collected through three semi-structured interviews, conducted with experienced industry professionals to obtained additional knowledge and opinion in relation to big data, cloud computing, IoT, technology and sustainability in the context of the lifecycles of construction projects. Following the interviews Quantitative data collection by questionnaire with analysis through statistical analysis assists in determining industry opinion in relation to the research. The flowchart in Figure 1 explains the Research Methodology.

Figure 1.

Research methodology flowchart (Author, 2020)

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