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Shutterstock/Panchenko Vladimir
Artificial intelligence (AI) has extended into many industries, with one major industry being the construction industry. Experts report seeing both a massive rise in the usage of AI in construction, as well as great promise for its future.
Talk of AI in construction might spur thought of its use with robotics systems. While robotics could make use of artificial intelligence, most of the robotics systems in construction currently do not. However, that is expected to change as robotics researchers develop ways to deal with the highly variable and uncertain nature of a construction site. Robotics without AI is becoming increasingly common on job-sites for applications like bricklaying, welding, and demolition.
In the immediate future, the construction industry is set to reap the benefits of automation by using it in functions common to all industries, such as in human resources and demand forecasting. AI is also being used to transition into a paperless, more streamlined way of doing business. PlanGrid is an AI-infused program that allows stakeholders to gain access to and exchange blueprints on various devices, resulting in smoother interactions among people.
AI is also developing as a means to carry out construction-specific tasks, especially in applications like surveying and the analysis of structures. Komatsu recently started its SMARTCONSTRUCTION solutions service that includes automated 3D map generation, blueprint extraction, and construction plan modeling, as well as drones surveying construction locations. These operations that can normally take weeks can be achieved in one day thanks to AI.
Building Information Modeling
AI is currently being used to reimagine how construction operations are done through BIM (building information modeling). With BIM, stakeholders can access the complete background of a building; from its conception to its management, to its demolition. AI, virtual assistant, and NFC (near-field communication) technology will soon be able to provide real-time information through a conversational interface. This will be particularly helpful in an emergency situation. First responders headed to an emergency could get information on the building in real-time, enabling them to rapidly make appropriate decisions.
Also on the horizon, lessons learned through past mistakes will not be repeated, as both tribal and industry knowledge become AI knowledge. Such knowledge is held in daily reports, schedules and weather forecasts. For example, engineers can use AI to better leverage knowledge on designs from the past 50 years. AI can use data to suggest optimal designs, help in reviewing designs and provide engineers a large group of knowledge that would otherwise have in front of them.
Many top tech brands with AI muscle are making noteworthy inroads into the construction industry. Oracle recently acquired Textura to create the Oracle Engineering and Construction Global Business Unity, which provides extensive cloud-based project control and an execution platform that deals with all stages of construction projects. Also, SAP has started providing construction businesses with solutions that cover anything from bidding to HR.
These businesses and have identified trends in the construction industry and are using AI as a strong tool to take advantage of these trends. For instance, AI can be used to address the skilled labor shortage the industry is currently facing by eliminating simple, redundant jobs, leaving the more complex tasks to humans.
Small Companies will Face a Major Investment Barrier
Almost anything on a construction site can be a data collection tool, and more data means more accurate solutions. The problem with this is that small-to-mid-sized companies may not have sufficient data scale to compete, except if the industry sets up a shared database. While it will probably happen for government projects and large equipment suppliers, private sector advantages will likely go to the biggest architecture, engineering, and construction companies, especially those that go all-in on AI.
In fact, many large early adopters are already working vigilantly on data collection and rolling out wearable devices for their workers.
Further Reading
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