In real life, that apprentice might have to go up 30 stories,
walk out on a beam, receive a piece of steel and weld it, and
that is very a different situation, says Lengieza. You don’t
want to expose an apprentice to that risk and danger without
VR is also being used for construction machine operating
training, he adds. This eliminates the need to transport stu-dents
to locations and equipment and reduces the chances of
damaging very expensive machines.
2. Augmented reality (AR): This is taking data and
information out into the field. It involves using a spatial/vir-tual
reality headset that lets the wearer see and interact with
digital content at a job site by overlaying holograms or 3D
models over the real world.
For example, says Lengieza, a person can visualize what
the design of the building is supposed to be, right alongside
the current progress of the building to detect any problems
3. Robotic technology: This is currently being used to
automate processes and increase productivity for such jobs
as welding, demolition, drywall hanging, brick laying and
masonry assistance (lifting concrete blocks) but it is not com-monplace,
he says. He envisions robotic technology in rover
and data collection applications evolving more rapidly in the
companies are welcoming
and embracing innovation.
As old methodologies and
science converge, new
efficiency, productivity and
profits, says Lengieza.
4. Automation technology: The mining industry is
using this technology to have haul trucks respond to calls to
the shovel, move into position and haul to dump points, says
Lengieza. Development is happening with backhoes, bulldoz-ers,
excavators and other construction vehicles so that they can
operate themselves and make construction safer and faster.
5. Machine learning: This is being used to more effi-ciently
– and with greater accuracy – analyze and categorize
project data, which in turn helps boost productivity, increase
safety and reduce costs, says Lengieza.
A method of data analysis, machine learning is a process
wherein computers, by creating algorithms, learn from previ-ous
data without being explicitly programmed.
6. Artificial intelligence (AI): This involves layering
industry knowledge into machine learning so AI can think
like a construction superintendent and, by way of exam-ple,
make suggestions, says Lengieza. However, that is a
ways off because there must be enough aggregated data to
train AI models and then time has to be invested to evolve
those models. n
Attend the education session “A Construction Tech Odyssey –
From Today to 2025” on Thursday, March 12, 2020 from 9:30
a.m. to 10:30 a.m. at CONEXPO-CON/AGG in Las Vegas. Visit
conexpoconagg.com to register.
ALBERTA HEAVY Quarter 1 2020 47