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In the construction industry, as in other sectors, big data refers to the huge quantities of information that have been stored in the past and that continue to be acquired today. Big data can come from people,

computers, machines, sensors, and any other data-generating device or agent. That, naturally enough, is what makes it big. Construction and building big data already exists in all the plans and records of anything that was ever built.

It is also constantly increasing with additional input from sources as diverse as on-site workers, cranes, earth movers, material supply chains, and even buildings themselves.

Traditional information systems are good at recording basic information about project schedules, CAD designs, costs, invoices, and employee details. However, they are limited in their ability to work with unstructured data like free text, printed information or analog sensor readings. Often, they can only handle orderly digital rows and columns of numbers.

The idea of harnessing big data is to gain more insights and make better decisions in construction management by not only accessing significantly more data, but by properly analyzing it to draw practical building project conclusions. In fact, big data, like truckloads of bricks or bags of cement, isn't useful on its own.

It's what you do with it using big data analytics programs that counts.

GETTING DOWN TO BUSINESS WITH BIG DATA To see how big data is already being used by the construction industry, consider the design- build-operate lifecycle that increasingly defines construction projects today.

Design. Big data, including building design and modeling itself, environmental data, stakeholder input and social media discussions, can be used to determine not only what to build, but also where to build it. Brown University in Rhode Island, US, used big data analysis to decide where to build its new engineering facility

for optimal student and university benefit. Historical big data can be analyzed to pick out patterns and probabilities of construction risks

to steer new projects towards success and away from pitfalls.

Build. Big data from weather, traffic, and community and business activity can be analyzed to determine optimal phasing of construction activities. Sensor input from machines used

on sites to show active and idle time can be processed to draw conclusions about the best mix of buying and leasing such equipment, and how to use fuel most efficiently to lower costs and ecological impact. Geolocation of equipment also allows logistics to be improved, spare parts to be made available when needed, and downtime to be avoided.

Operate. Big data from sensors built into buildings, bridges and any other construction makes it possible to monitor each one at many levels of performance. Energy conservation

in malls, office blocks and other buildings can be tracked to ensure it conforms to design goals. Traffic stress information and levels of flexing in bridges can be recorded to detect any out of bounds events. This data can also be fed back into building information modeling (BIM) systems to schedule maintenance activities as required.

HOW "THE INTERNET OF THINGS" IS AFFECTING THE CONSTRUCTION INDUSTRY Remote operation: If you can hook up a machine to the web either with a physical or a wireless connection, you can give it instructions remotely. It can operate alone in areas that would be hazardous to humans because of pollution. Similarly, wearable computing like Google Glass can help workers on site access instruction manuals in hands-free mode, or benefit from remote support that sees what they see.

Supply replenishment: When units of supply are labeled with RFID tags, a system on site can count them. When the count drops below

Big data including building design and modeling can be used to determine what to build and where to build it

a given level, the system can trigger a request from a central system to order more. Idle time goes down and projects have better chances of being completed on time. Costs are also contained because the construction company does not need to buy in significantly more supplies than it is likely to use at any one time. Instead, just-in-time provision becomes possible automatically.

Construction tools and equipment tracking: Similarly, you'll know where that pneumatic drill ended up or how many excavators are currently located at a given construction site. This will help reduce the time lost looking for mislaid items as well as the cost of purchasing replacements. GPS data is already being used to monitor vehicle fleet locations.

It also allows excavating or landscaping equipment to be precisely positioned on a terrain to then automatically carry out instructions using a virtual map of the digging, cutting or other terrain modifications to be made.

Equipment servicing and repair:

Sensors in machines allow them to transmit information about their status and any need for service or repairs. Fixing machines before they break makes more sense than waiting for failure, which by Murphy's Law is all too likely to happen just at the wrong time.

Remote usage monitoring: For equipment used by workers, whether power drills or articulated earth- movers, the IoT means construction hours can be logged automatically. Limits can be monitored, so as to prevent worker fatigue and possible accidents. Wearable computing in the form of wristbands can also monitor driver health and alertness. Action can be taken if the limits are in danger of being exceeded.

Power and fuel savings: Via the IoT, sites can send back information on the amount of electrical power they use, so that after-hours lighting can be adjusted for energy- savings. Machines can send back information on idling time (which uses fuel) so that on and off periods can be adjusted without penalizing projects through the time needed to restart machines.

Augmented Reality (AR): Google Glass offers AR, but you have to be wearing the Google Glass goggles to make use of it. The next step will likely be to integrate AR directly into equipment visors and vehicle windshields. Operational instructions or navigational and driving information will then come over the IoT in real time, and be overlaid onto the real-world view of the job to be done or the journey to be traveled.

Building Information Modeling (BIM): Computer models that have been used to direct real-life construction can in turn be updated by sensors placed in the buildings that have now been constructed. The sensors can send back information on the way that materials are affected by changing climates and the passage of time. They can supply information on possible changes in energy efficiency in roofing, how structures behave when there are earth tremors, or how a bridge bends under the weight of passing traffic.

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Publication:OER Dossier
Date:Dec 31, 2017

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