What Effect Will AI Have on Construction?

Construction and the built environment have historically been slow adopters of new technologies. However, that is starting to change.

An increasing number of construction firms are investing in new digital solutions, software, and data analytics that are making it easier to collaborate, share information and create virtual models.

What Will AI and Machine Learning Mean for Construction?

Whilst investors may still be reluctant to adopt them, a growing interest in green building practices and a shortage of skilled tradespeople has led firms to invest in AI and machine learning (ML) as a way to automate processes while remaining compliant with industry regulations.

Read on to learn more about how AI, machine learning, and other emerging technologies are transforming the construction industry.

What is AI?

Artificial intelligence is the use of software or hardware to design or build systems that can learn, reason, and act autonomously. AI systems are designed to perform tasks that normally require human intelligence, such as visual recognition, language translation, or complex mathematical modelling.

AI systems can be used to speed up and simplify many aspects of our daily lives, including manufacturing, logistics, and healthcare. Construction firms can use AI to automate and streamline a wide range of processes.

For example, AI can be used to create virtual models of projects that can be used as a collaborative planning tool and shared with all stakeholders, including clients and government officials.

Machine Learning in Construction

Machine learning is a subset of AI that uses algorithms to “teach” computers how to learn and make predictions based on data. In construction, machine learning can be used to predict maintenance issues on equipment, predict weather events and their impact on site operations, and monitor equipment usage, among other things.

Machine Learning
Machine Learning

Machine learning algorithms are designed to identify trends and patterns in large quantities of data. When applied to construction, these algorithms allow firms to track, manage, and analyse large amounts of data to uncover critical insights.

One way construction firms are using machine learning is to identify patterns in construction defects. Rather than manually reviewing each defect, firms can use algorithms to review images and tag defects automatically.

Firms can also use ML for predictive maintenance on equipment, track hours and usage of equipment, and optimising employee workflow.

Virtual Reality in Construction

Virtual reality (VR) is a computer-generated simulation that creates an immersive environment. This technology can be used to create immersive environments that allow project teams to collaborate remotely in real-time and improve the accuracy of cost estimation and scheduling.

VR can also be used to create a realistic vision of the final product. VR can be used to create virtual reality models, walkthroughs, and 3D models. These models can be used to help design and build projects more efficiently.

VR can also be used to create virtual tours of projects while they are still under construction. The ability to create a virtual tour while the project is still under construction can help stakeholders better understand the project, reduce delays, and mitigate risk.

Robotics in Construction

Robotics can be used in construction to automate and streamline a variety of tasks, including making clean and accurate cuts, moving materials, and mixing and pouring concrete. Robotics can be used for a wide range of tasks, including forming concrete, laying bricks, sweeping up debris, and inspecting buildings after natural disasters.

Construction robots can be programmed to do one specific task repeatedly or be equipped with sensors to allow them to adjust to changes in their environment. They can be used to lift heavy materials or work in dangerous conditions, and they can improve construction efficiency by working at night or in inclement weather.

Robotics are also increasingly being used to inspect and maintain tall structures, including bridges, wind turbines, and solar panels.

Automated Quality Control Using AI and ML

Construction firms are increasingly using AI and ML to identify construction defects and quality issues before they occur, which can save time and money.

For example, construction firms can use computer vision to scan and analyse images and 3D models of buildings and infrastructure to look for any irregularities. This automated quality control can be applied to existing projects as well as new projects.

Similarly, computer vision can be used to inspect the quality of materials used in the construction process. For example, computer vision can be used to analyse the colour and density of concrete being used to build a structure to make sure it meets the required specifications.

In addition to these quality control measures, computer vision can be used to automate the inspection process itself. For example, with the use of computer vision, engineers and inspectors can use video recordings instead of paper logs to document the inspection process.

Conclusion

Construction and architectural firms can use AI and machine learning to support their engineering, design, and construction operations. These technologies can be used to create virtual models, review blueprints, track hours and usage of equipment, manage projects and improve communications.

As we move forward, construction firms will need to ensure they have the internal resources and expertise to implement these emerging technologies successfully.

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