Big Data: Facing the Frontier of Artificial Intelligence and Machine Learning

By David Pratt, Manager of BIM/VDC, Robins & Morton

A recent article in Protocol, a newsletter covering technology, discussed a product called Replica that creates “an expansive computer-generated model of how people move through a community, based on a combination of cell phone data and census information.”

A spinoff from Google’s parent company Alphabet, Sidewalk Labs’ Replica is aimed at urban planners, including transit authorities.

“Unlike surveys that are based on years-old data by the time they are put to use,” the article reports, “Replica’s models can be updated quarterly.”

However, the sudden access to so much information is presenting challenges for urban planners looking to utilize the data.

“Replica’s technology is so new, urban planners don’t know what to do with it,” Protocol reporter Matt Drange wrote.

Although Urban planning is not construction, and Replica isn’t likely to join the project management applications found on a jobsite, innovation is universal. It happens when we think beyond the current state. Few of us would have thought that an X-Box® controller would have a useful place in a construction office. But Buildfore®, Robins & Morton’s software company, did. Their CtrlWiz® application uses the simple interface of a game controller to make it easy to navigate Navisworks®. This is true of many of the innovations on the construction site – drones, 3D scanning, and robots tying rebar. Many of these innovations evolved from technologies first developed outside of the industry, and we can expect the same to happen with data.

Replica illustrates an interesting shift in how we apply data and technology. Typically, the gathering and processing of information is task-driven – for example, cost analysis, estimate development or project tracking.

What if we took that same approach and applied it to information, but instead of thinking about how technology could be adapted, we imagine how data could be used?

We have access to exponentially more data than we use, thanks to something not much bigger than a deck of cards – the smart phone. It’s easy to snap a photo of a quality issue and share that very precise information with the appropriate trade contractor. However, that doesn’t even begin to tap the recording, sensing and processing power we carry around in our pockets. Considering the potential can make us feel much like the urban planner wondering what to do with Replica.

Almost a decade ago, ConstructConnect predicted, “As construction projects become more complex, big data may soon become the most important tool at a construction company’s disposal.”

Big data refers to amounts of information so massive that traditional software can’t analyze them. It’s the opposite of the narrowly focused data – such as project status – that we’re accustomed to using. If big data sounds mind boggling, that’s because it is. Big data is characterized by the need to use artificial intelligence (AI) and machine learning to unlock its value. The spreadsheet-based tools we typically use aren’t powerful enough to analyze such large and disparate data sets.

Typically, that kind of computing power has been out of reach for most companies. However, AI and machine learning are just like any other technology: as computing power increases and prices decrease, accessibility increases.
One of the differences of big data – compared to the narrower data sets we’re accustomed to using – is that it is big.

Think, for example, about safety. A single incident on one jobsite may appear to be isolated. A big data approach could look beyond that single incident, consuming a huge number of workplace incidents and using artificial intelligence and machine learning to potentially identify a common factor that might have been hard to see looking at just one or a few cases. That approach could expand to include quality issues, equipment failures or delays. We’ve already seen how jobsite camera videos are analyzed by AI and over time and produce analyses of site traffic, deliveries, routines, and safety awareness. But that’s just a small example.

The challenge using big data is being able to decipher the huge amounts of information to produce tangible benefits. That’s where companies specializing in big data analytics will need to step in, just as they have done in so many other industries and businesses. With that will come additional challenges. How do we protect personal privacy, ensure confidentiality of competitive company information and secure data? But information is power, and big data technology can harness that power.

Four decades ago, scientist E.O. Wilson wrote, “We are drowning in information, while starving for wisdom.” With the amount of information already flowing back and forth on major construction projects, the thought of adding hundreds, thousands or more data points can feel like drowning. But we can see opportunity in the rest of his quote: “the world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely.”