Big Data in Construction

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5 months ago
Image © Remaking Cities Institute, School of Architecture, Carnegie Mellon University - 3D-Data Visualization for Urban Design and Planning

As touched upon in previous articles the construction industry is slow on the uptake and implementation of technologies and digital platforms offering the potential to enhance productivity, efficiency, innovation and growth when compared to other industries. A McKinsey report on The Next Normal in Construction outlines how, despite the fact construction accounts for 13% of global GDP, over the last 20yrs productivity growth has averaged a meek 1% growth per annum. Lets review how big data in construction can help buck the trend. 

A significant digital shift is coming, accelerated by the growth and implementation of BIM standards in recent years globally, the realisation of efficiencies in design associated with various digital drafting/analysis tools and the competitive advantage that leveraging these tools offer. Digitalization will also likely form a key part of industrialization of construction, or in other words the transition to a more automated and manufacturing-led process. This is related to the increased productivity, safety, efficiency and reduced environmental impact.

Big Data and IoT

What does Big Data in Construction encapsulate? “Big” refers to the huge volume or quantity of data currently available and the likely exponential growth of this data with time. Almost every activity that is in any way computerized generates data, often at huge volumes which can be analysed and used to develop trends, uncover issues and identify opportunities for growth/development within a particular industry. The key characteristics of big data can be summarized as volume, variety (photo, video, text, audio, structured versus unstructured), velocity (the speed of generation) and variability or consistency. Value and veracity, related to trustworthiness, rounds out what have been termed the “the six V’s of big data”.

The internet of things (IoT) is a term used to describe the network of all devices used to access and interact online, ranging from personal electronics, various sensors and monitors, drones and satellites etc., that are connected to the internet through which it can send and receive data.

Big data and the Internet of things are already helping the industry in a number of ways including reduced downtime of labor and equipment, improved productivity and increased safety and security. Big data is also being used in design and construction. Brown university used big data to assess the optimal location for its engineering faculty. In addition big data and IoT form a very important part of building analytics and Building Management Systems (BMS) which are essential elements of what are termed smart buildings – buildings which save/conserve energy during off-peak hours, have automated AC and lighting, and use data from this interconnected network to enhance building efficiency and reduce environmental impact.

The interface to manage and harness data

The fact that terabytes, petabytes, or even more data can be and have already been stored, does not mean data collection and utilization is without challenges. Depending on veracity, variety and variability of this data (as mentioned above) extracting useful information can be an extensive and complicated process. This raises the question, what technology do we use to leverage all the benefits that big data brings. Below is an illustration from a report published by World Economic Forum in 2016 showing this integration of technology and the construction life-cycle underway. This figure shows conceptually from left to right the timeline of a project, from top to bottom the user-end and the device-end of technologies. Both axes require technology integration and information security measures.

Digital Technologies Applied in the E&C Value Chain (World economic forum & The Boston Consulting Group, Shaping the Future of Construction, Industry Agenda Report, 2016)

What are some of the ways Big Data can make a Big Impact in Construction:

 
  • Data driven decisions to avoid project cost overrun: According to a report published in IJIMT 2017, research by Flyvbjerg discovered that in 258 transportation projects (in 20 countries, built between 1927 and 1998) there is an average of 28% cost overrun in almost 9 out of 10 projects. Autodesk’s former SVP for products also pointed out that “Material waste accounts for approximately 25% of a project’s cost, and rework adds an estimated 10%”, which is inexcusable since “today’s digital tools are readily available to stop this haemorrhaging of money, materials and time”.
  • Data driven space requirements and energy performance goals: Architectural design has been driven by the need of clients and prescriptive building codes. The understanding of customer preferences and space requirements based on future demand and simulation will become critical inputs for design in the future. Big data will facilitate the transition from prescriptive codes to performance-based codes. In the case of energy conservation the simulation results will depend on weather data and design load of HVAC.
  • Enhanced collaboration and construction oversight: We have mentioned in our BIM article the various parties – designer, contractor, owner and facility manager participating throughout the life-cycle of a building. Given the new survey technologies, drones and 3D scanning, there is a huge potential in the real-time information sharing during the progression of project phases on cloud platforms to inform better decisions based on multi-party agreement. Here are a few examples of these new technologies.
General structure of the software implementation of a BIM-based production system 
(Image © HOCHTIEF ViCon, from BIM - Technology foundations and industry practice, Springer, 2015)
General structure of the software implementation of a BIM-based production system (Image © HOCHTIEF ViCon, from BIM - Technology foundations and industry practice, Springer, 2015)

  • Inform best practices and avoid risks: A report from McKinsey indicated how businesses can benefit from embracing continued development in their data analytics model, through the accumulated portfolio, analyzing market trends and forecasting. Business can also reduce overall cost in the long run by applying data-driven decisions to achieve balanced procurement and leasing strategies. Below is an exhibit from this report showing 3 major categories of data input in a business’s analytics model – defined as micro data (specific projects), macro data (portfolio from accumulated projects and precedence), and external data (external services, weather, economic indicators, etc.)

The vast array of project-related data that owners can access and need to effectively own (McKinsey&Company, How advanced analytics can benefit infrastructure capital planning, 2018)

Maximum efficiency – Digital Twin

Progressively as BIM standards and practices evolves, BIM technology becomes more prevalent and has less platform interfacing issues, building design, construction and operations are projected to rely on a permanent digital twin – i.e. a digital building model which can synchronize activities of a building project as a mirror to reality and thereby help guide decisions related to building operations, design and construction. What makes this digital replication necessary? This article offers a glance at the benefits a digital twin can offer. Key players in this include energy modeling, prefabrication and automated manufacturing process, real-time data acquired from sensors installed in a building for simulation to inform future decisions.

Building design and construction is gradually becoming more digitized, and despite the fact that the end product of construction is a real-world structure, the planning, design, construction, performance, operations and maintenance rely heavily on digital models and analytics. The IoT and big data will play a huge part in helping guide us all as designers in the right direction in all of these areas.

This is an area of much depth and great potential, all of which we cannot cover in this article but we hope you enjoyed our introduction into the world of big data in construction. Thanks for reading!

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