Construction, a highly information-intensive industry, has been slow to adopt the technology. Up until about six or seven years ago, the technology was reserved only for the back office. It was used for HR and accounting, contract writing, and tracking change orders.
Kris Lengieza explains that this changed due to several reasons. Procore is a leading provider of Construction Management Software. They include:
- Mobile devices and new technology are ubiquitous in our daily lives.
- A growing shortage of workers
- The industry needs to be more efficient.
- The sector is attracting younger people with fresh ideas.
- Growth of technology and innovation firms
Construction companies today embrace and welcome innovation. New technologies are improving efficiency, productivity, and profits as old methods and science merge, says he.
Lengieza, for example, cites the use of 360° cameras, also known as photospheres, to document and capture construction progress and to check safety issues, amongst other uses.
The 15-year veteran in the construction industry says that webcams can be used to enhance visibility on a job site. Webcams are used to record time-lapses, track weather data, and detect deviations in schedules.
Lengieza said drones were being used to survey and track progress on construction sites. Drone Technology can capture more accurate, real-time data in a much shorter time frame than traditional methods.
He says that a big challenge for construction is to collect structured data in order to perform analytics. Big data, cloud computing, and other technologies, such as labor tracking software, project management, cloud computing, etc., can all be used today to understand how projects progress, determine which projects need immediate attention, identify more effective ways of doing things, and make better decisions.
Key Technologies for the Construction Industry
Lengieza says that the construction industry is embracing new technologies.
1. He says that VR simulations can replicate situations in the real world that are difficult, costly, or dangerous. Typical training for an apprentice ironworker to learn how to weld involves him standing on the floor.
Lengieza says that in real life, the apprentice may have to climb 30 stories and walk on a beam. He might also be required to receive a piece and then weld it. It is not a good idea to expose an untrained apprentice to such danger and risk.
He adds that VR can also be used to train construction machines. It eliminates the need for students to travel to equipment and locations, and it reduces the risk of damaging expensive machines.
2. It is a way to bring data and information into the field. This involves wearing a virtual/spatial reality headset to interact with digital content on a job site. Holograms and 3D models are superimposed over the real environment.
Lengieza explains that a person could visualize the intended design of a building alongside its current progress to detect any issues or problems.
3. He says that robotic technology is being used in the construction industry to automate processes, increase productivity, and perform jobs such as bricklaying, drywall installation, welding, and demolition. However, it is still not commonplace. He sees the rapid development of robotic technology for rover applications and data collection in the construction sector.
4. Lengieza observes that the mining industry uses automation technology so that haul trucks can respond to shovel calls, move into place, and haul to dump locations. Construction vehicles such as bulldozers and excavators are being developed to be self-operating. This will make construction safer and quicker.
5. Lengieza says that machine learning is used to analyze data more accurately and efficiently, which helps increase productivity and safety and lower costs.
Machine learning is an analytical method that involves computers creating algorithms to learn from past data without having been explicitly programmed.
6. He says that artificial intelligence (AI ):) involves layering knowledge of the industry into machine learning, so AI can, for example, think like a superintendent in construction and make suggestions. This is still a long way off because it takes a lot of data to train AI and time to develop the models.