The construction industry is a major sector of the world economy. Artificial intelligence (AI) has a lot of potential in the construction industry. AI solutions that have made an impact in other industries are beginning to emerge in the construction industry. It's beginning to change the way buildings are designed, constructed and utilised after construction. The technology combination of IoT and AI will change construction for the long term with new business opportunities.
Following are 10 methods incorporated with AI, to help us improve construction, and further develop the processes involved:
1. Boosting project monitoring and risk management
E&C stakeholders can use neural networks, using drone-generated images and laser generated data capturing project progress, to teach an AI how to create 3-D “twin models” to match BIM-generated models. These applications would dramatically reduce decision-making cycles in a construction project from a monthly basis to a daily basis—through full automation of the project scheduling and budgeting update on the combination of BIM, AI, drone, and laser capabilities.
2. AI Will Address Labor Shortages
Labor shortage and a desire to boost the industry’s low productivity are compelling construction firms to invest in AI and data science. Construction companies are starting to use AI and machine learning to better plan for distribution of labor and machinery across jobs. A robot constantly evaluating job progress and the location of workers and equipment enables project managers to tell instantly which job sites have enough workers and equipment to complete the project on schedule, and which might be falling behind where additional labor could be deployed. Experts expect construction robots to become more intelligent and autonomous with AI techniques.
3. Project Planning
AI database systems are now helping to inform engineers on how specific projects should be constructed. For example, if engineers were working on a proposed new bridge, AI systems would be able to advise and present a case for how the bridge should be constructed. This is based on past projects over the last 50 years, as well as verifying pre-existing blueprints for the design and implementation stages of the project. By having this information to hand, engineers can make crucial decisions based on evidence that they may not have previously had at their disposal.
4. AI Will Make Jobsites More Productive
AI is being used to manage the project and control tasks. For example, workers can input sick days, vacancies and sudden departures into a data system and it will adapt the project accordingly. The AI will understand that the task must be moved to another employee and will do so on its own accord. There are companies that are starting to offer self-driving construction machinery to perform repetitive tasks more efficiently than their human counterparts, such as pouring concrete, bricklaying, welding, and demolition. Excavation and prep work is being performed by autonomous or semi-autonomous bulldozers, which can prepare a job site with the help of a human programmer to exact specifications.
5. Prevent cost overruns
Most mega projects go over budget despite employing the best project teams. Artificial Neural Networks are used on projects to predict cost overruns based on factors such as project size, contract type and the competence level of project managers. Historical data such as planned start and end dates are used by predictive models to envision realistic timelines for future projects. AI helps staff remotely access real-life training material which helps them enhance their skills and knowledge quickly. This reduces the time taken to onboard new resources onto projects. As a result, project delivery is expedited.
6. AI for Construction Safety
Construction workers are killed on the job five times more often than other laborers. According to OSHA, the leading causes of private sector deaths (excluding highway collisions) in the construction industry were falls, followed by struck by an object, electrocution, and caught-in/between. A Boston-based General Contractor with annual sales of $3 Billion is developing an algorithm that analyzes photos from its job sites, scans them for safety hazards such as workers not wearing protective equipment and correlates the images with its accident records. The company says it can potentially compute risk ratings for projects so safety briefings can be held when an elevated threat is detected.
7. AI and Big Data in Construction
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 job site becomes a potential data source for AI. Data generated from images captured from mobile devices, drone videos, security sensors, building information modeling (BIM), and others have become a pool of information. 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.
8. Off-site Construction
Construction companies are increasingly relying on off-site factories staffed by autonomous robots that piece together components of a building, which are then pieced together by human workers on-site. Structures like walls can be completed assembly-line style by autonomous machinery more efficiently than their human counterparts, leaving human workers to finish the detail work like Plumbing, HVAC and Electrical systems when the structure is fitted together.
10. Post-Construction
Once buildings have been constructed, whether they are used for commercial purposes or it is a development of new houses, AI systems can be used inside the structure. In the US alone, $1.5 billion was invested in 2016 by companies looking to capitalise on this growing market.AI can be used to monitor developing problems and even offers solutions to prevent problems.