AI in Construction

- Overview

Over the past 40 years, machine learning (ML), especially deep learning (DL), has made significant technological advances, triggering major changes in various industries. It has also become a powerful tool for automating construction processes that lag behind other industries in terms of performance and productivity. 

Machine learning technology plays an important role, especially when processing large amounts of data, and can bring significant added value to save time and maximize computing resources. For example, they can be used for text mining in project-related documents to help reduce demands on human resources while improving safety.

Since 2017, due to its excellent performance in the field of computer vision, deep learning has been widely adopted in many construction fields such as safety.

- Applications of AI in Construction

AI can automate many processes involved in construction projects, making construction work safer and more efficient. Common use cases include scheduling, resource allocation planning, quality control, and predictive maintenance of heavy machinery. 

Some ways AI is used in construction include:

• Automating tasks: AI-powered robots can perform tasks like painting, bricklaying, and welding, which can reduce labor costs and improve project completion times.
• Analyzing images: AI algorithms can analyze images of construction sites to detect quality issues in materials. Parsing building codes: AI can quickly identify relevant building codes, which can help ensure construction jobs are up to code.
• Streamlining communication: AI automation can help streamline communication between contractors and clients.
• Managing project timelines: AI automation can help manage project timelines and budgeting.
• Automating the estimating process: AI can automate the estimating process, which is a manual process that can take days of work.

[More to come ...]