Lendlease Innovation Leader on Improving Outcomes With Machine Learning and AI

August 5, 2019 | 4 minute read
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In Part I of this month's "Trailblazers" series, Jasna Sims, group head of innovation culture at Lendlease, shared her company's approach to improving project delivery through innovation. In Part II, Sims reviews how developing technologies such as sensors, lidar, machine learning, and artificial intelligence (AI) are helping the construction and engineering industry improve.

Dr. Burcin Kaplanoglu, executive director and innovation officer at Oracle Construction and Engineering, leads the discussion.

BK: What emerging technologies do you see representing the best opportunities today?

JS: Some proven technologies have been around for a while. Even the most basic technologies help the way we deliver products and services. It’s about understanding what problems need to be solved and looking around for the right technologies.

Sensors are incredibly useful, although probably not the sexiest of technologies. While this technology isn’t sending people to Mars, there's so much that can be done with simple sensors.

We're using sensors on our heavy vehicles and equipment to drive productivity, improve costs, and save lives in the following ways:

•    Manage the number of hours that our drivers have worked to ensure they take a rest break. We know that tired drivers make mistakes, and mistakes on construction sites can impact health and safety.
•    Prevent trucks from colliding.
•    Truck sensors tell us whether a truck has a fault or a mechanical failure that’s unexpected or about to happen. Sensors give us early warning to fix that.
•    Productively manage truck fleets.
•    We also put sensors on archaeological items to ensure we don’t inadvertently disturb artifacts during construction.

A small thing like a sensor can make such a difference. Sensors can also help improve the products and services that we deliver. For example, in our commercial buildings, sensors improve our customers' ability to get the right outcomes from the space they’ve built.

We’re using sensors in our communities to inform things like: whether the sprinklers should go on based off recent rainfall, whether disposal bins need to be emptied, etc. We're using sensors around security as well.

Lidar scanning

Lidar scanning on our construction sites is also exciting, because we can measure construction progress on site. We can ensure that we've built what we think we've built, and that it matches with our BIM models.

While we’re in early stages of innovating around lidar scanning, we’re in the advanced stages of using sensors.

BK: Artificial intelligence and machine learning have been a hot topic - especially over the last 12 months in every industry, including construction and real estate. What value do you see in these technologies?

JS: With artificial intelligence, we’re looking at how to incorporate lessons learned and knowledge from past designs, including the performance of materials, and provide this information to our designers in the early stages.

We embed AI into building information modeling (BIM) models so that people can visualize early warnings and guidance on how to avoid pain points that we've experienced in the past while they’re designing with details and materials.

Some design details have proven not to withstand the test of time. We managed this by sending out design alerts for people to stay aware of. There’s a fantastic opportunity to build AI into the model, manage the data differently, and make it easier to digest for the designers.

Safety global minimum requirements

We’re also heavily focused on safety. We have something called our “safety global minimum requirements”. These are our own safety requirements that often go above and beyond the safety standards of some of the places that we operate.

We’re experimenting with putting those requirements into BIM models. Designers would have early visibility into how their designs impact people’s ability to safely build and maintain their designs down the line.

The early design stage: AI and machine learning

That’s a good place to start with artificial intelligence and machine learning.  he early design stage confirms that we design the right things to begin with and that we avoid clashes during construction while looking at buildability, safety, and other important issues.

These technologies have applications throughout the entire development and construction process, but design is a good place to start. The ability to add the greatest value to any project is during that concept stage. Re-work costs you so much and you can never get the same outcomes.

BK: You mentioned constructability, safety onsite, productivity and avoiding errors. Assuming we have the data, machine learning can extract that data and help make us smarter.

The next time we design or build something, we’ll know that there are certain patterns we can avoid. It’s a big opportunity to move ahead with the way we design and build cities, communities, and buildings. Everything comes together.

JS: Definitely. Machine learning and artificial intelligence gives us such an opportunity to improve.

Our people can focus on designing the best buildings and the best outcomes for our customers instead of reviewing pages of “lessons learned” to make sure they're not designing something that has failed before.

Read our eBook: "Innovation in Construction: Perspectives from AEC Innovation Leaders"

Related "Trailblazers" posts:

Explore innovation in action at the Oracle Construction and Engineering Innovation Lab, a simulated worksite with integrated technologies.


Corie Cheeseman

Corie Cheeseman is a senior content marketing manager for Oracle Construction and Engineering.

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