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AI and Machine Learning Technology for Construction Construction Will Benefit From Integrating AI and Machine Learning Technologies Into Workflows

The rise of artificial intelligence (AI) and machine learning technology is rapidly redefining the entire concept of how work will be performed in the near future, including in the construction industry.

These AI and machine learning technologies are allowing construction companies to operate more efficiently and safely, increase automation and reduce equipment downtime. However, key decision makers and companies must carefully consider both the short and long-term benefits of deploying AI and machine learning technology at their construction sites.

Construction firms that are looking to streamline and advance their operations are increasingly turning to AI-powered solutions and programs. As a near-term investment, these companies will see a variety of immediate benefits, like automated monitoring for heavy machinery and real-time location tracking for site equipment and materials.

For example, AI is powering a new generation of programs that allow construction companies to continuously monitor their heavy equipment on-site in real time. Should any component break down or malfunction, the program proactively alerts the operator to the issue and the faulty equipment is immediately taken offline for servicing. As a supporting result, on-site and worker safety is also increased by using more reliable, safer equipment.

Additionally, AI software embedded into a location tracking program means that the program can proactively alert a project manager when materials arrive on-site and state where exactly that delivery was left at the site. This reduces the amount of effort and time needed to track down and distribute the latest shipment of materials, making for more interconnected jobsite operations.

The construction industry stands to realize many long-term benefits as it integrates additional AI and machine learning technologies into its operations. As The New York Times has previously written, the effects of quickly adapting to the latest technologies can cause unease for individuals and companies alike. However, concerns about the future or potential capabilities of AI do not mean that the construction industry should be discouraged from doing so.

The design and planning phase for any construction project is one of the most important steps in the construction process and requires months – or even years – of meticulous attention to detail and preparation by an entire team of architects, engineers and construction professionals. AI and machine learning technology stand to help improve and quality-check this entire process, resulting in a construction process and plans that are accurate, verified and well designed.

Moreover, advancements in AI and machine learning will also help assist project managers and architectural consultants in demand forecasting and scheduling during the years-long design and planning phase before ground is actually broken. Additional research and trials are also being conducted to further leverage AI in order to increase project and site safety, such as designing a more intuitive user-machine interface for using heavy-duty equipment and increasing automation capabilities for site surveying.

As the construction industry continues to move toward increased automation to increase safety and on-site productivity, it will undoubtedly turn toward AI and machine learning applications to help get the job done. These tools offer both short and long term benefits for companies, workers and projects alike, including real-time data and asset monitoring, AI-assisted design and planning and predictive maintenance for construction equipment and fleets.

Already, construction firms are utilizing these practical applications across their projects and operations. By taking steps to modernize for a constantly evolving world, the construction industry will ultimately benefit in the long term from closely integrating AI and machine learning technologies into their planning, design and production workflows.

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