With 7% of the world’s workforce being employed in the construction industry, it would be assumed that this major sector was at the forefront of developing new technologies for use in construction-related activities. However, compared to other industries, like manufacturing and agriculture, construction is progressing at a snail’s pace.
While adopting the latest technology can be intimidating, it is essential if the construction industry wants to improve on productivity, safety and cost-saving. Artificial Intelligence solutions have already made an impact in other industries and are beginning to emerge in the construction industry.
What Is Artificial Intelligence & Machine Learning?
Artificial Intelligence, or AI, is the ability of a computer programme to mimic human cognitive functions, such as problem-solving, learning and pattern recognition. Machine Learning is the application of AI that allows systems to automatically learn and improve from past experiences without having to be explicitly programmed.
1. Project Planning
Project planning and management is an obvious area that AI and machine learning can improve on. In fact, AI might hold the key to solving the problem of behind schedule and over budget construction projects. The AI software can use 3D scans of construction sites to keep track of the various sub-projects and then notify the management team if things get off track.
In the future, an AI technique known as reinforcement learning will allow algorithms to learn based on trial and error. The AI will then be able to aid in project planning by optimising the best path while making corrections as the project continues.
2. Cost Saving
Many construction projects go over budget despite the best efforts of the management team. AI networks are beginning to be used to predict any potential cost overruns on projects based on a range of factors, such as project size.
The predictive models make use of collected data from previous projects, such as start and end dates, to create a realistic timeline for any future projects. In addition, AI can help project management and staff remotely access any training materials required to increase productivity and help reduce costs.
3. Risk Mitigation
Every construction project has some form of risk, ranging from health and safety risks to cost risks. Usually, the larger the project, the more risk and a higher chance something can go wrong. Thankfully, there are a range of AI and machine learning solutions available that can be used to monitor and prioritise risks on construction sites.
This allows project managers to focus their resources on the biggest risk factors and reduce the risks involved. AI is used to automatically assign priority to issues, allowing managers to mitigate risk on construction sites.
4. Improved Design
The construction industry is beginning to use machine learning for 3D modelling for building designs. The process allows construction professionals to efficiently design, plan and then construct buildings and infrastructure without the need for rework.
The 3D models take the architecture, electrical, plumbing and engineering plans into consideration and ensure that the different models from each of the different plans don’t clash with each other. There is even software that uses machine learning to explore all of the different variations and generate alternative designs to prevent any conflicts.
5. Improved Construction Safety
Despite the best efforts of the construction industry, construction sites are simply hazardous environments. Construction workers are killed on the job five times more often than other labourers. New technology, such as AI and machine learning, is helping to improve health and safety on construction sites.
Machine learning can be used to analyze photos from construction sites, scan them for safety hazards, such as a lack of safety equipment, and then correlate those images with recorded accident records. The hope is this technology can potentially compute risk ratings for construction projects, allowing management to target any areas of increased risk.
6. Increased Productivity
AI also stands to improve productivity at construction sites by removing the need for workers to perform repetitive tasks. Self-driving vehicles and construction machinery can perform tasks such as pouring concrete, welding, bricklaying and demolition more efficiently than their human counterparts.
Not only does this allow human workers to focus on more important or more complicated tasks, but it also reduces the time required to complete a construction project. In addition, it also improves the accuracy of some work, such as excavations work. Autonomous machinery can prepare a job site to exact specifications after being programmed.
7. Remove Labour Shortages
Removing labour shortages and boosting the construction industry’s low productivity is one of the most compelling motivators for investing in AI and machine learning. Construction companies are beginning to use AI to plan for an improved distraction of labour and equipment across various construction sites.
The hope is the AI will constantly evaluate the progress on sites and ensure that each construction site has enough workers and equipment to complete the project on schedule. In addition, if there are any setbacks or problems, the AI can recognise and suggest where additional workers could be deployed to improve the situation.
8. Data Analyses
Construction presents a huge opportunity for data analyses. At a time when a massive amount of data is being created every day, AI Systems are exposed to an endless amount of data to learn from and improve every day. Every construction site becomes a potential data source for AI.
This presents an opportunity for construction industry professionals and customers to analyze and benefit from the insights generated from the data with the help of AI and machine learning systems.
9. Off-site Construction
Construction companies are increasingly making use of off-site factories that use autonomous machinery to assemble building components, which are then transported to construction sites and then assembled. Some structures, such as walls can be completed by autonomous machinery in an assembly-line style much more efficiently than if they were built by human workers.
10. Post-construction Care
AI is useful in construction even after the project has been complete. For example, building managers can make use of Building Information Modelling to gather and store information about the structure of the building. AI can then be used to monitor any developing problems just as it did during construction. AI can even offer solutions to prevent potential problems.
The Future Of AI In Construction
Despite concerns that AI will result in massive job losses, it is unlikely that AI will actually replace the human workforce in construction. Rather, it will have an impact on business models in the construction industry. AI can remove expensive errors or setbacks, reduce the number of onsite injuries and make projects run more efficiently. Leaders in the construction industry should prioritise investing in new technologies, like AI and machine learning, to have a positive impact on the needs of their industry.