AI In Construction
Adopting the latest technology can be daunting for teams. But machine learning and artificial intelligence are helping make job sites more efficient and saving money in the process. AI solutions that have made an impact in other industries are beginning to emerge in the construction industry. Artificial intelligence is an aggregative term for describing when a machine mimics human cognitive functions, like problem-solving, pattern recognition, and learning. Machine learning is a subset of AI. Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to “learn” from data, without being explicitly programmed. A machine becomes better at understanding and providing insights as it is exposed to more data. The potential applications of machine learning and AI in construction are vast. Requests for information, open issues, and change orders are standard in the industry.
Most megaprojects 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.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. Not only Building Information Modeling is a 3D model-based process that gives architecture, engineering and construction professionals insights to efficiently plan, design, construct and manage buildings and infrastructure it also works in order to plan and design the construction of a building, the 3D models need to take into consideration the architecture, engineering, mechanical, electrical, and plumbing (MEP) plans and the sequence of activities of the respective teams.
The challenge is to ensure that the different models from the sub-teams do not clash with each other. The industry is trying to use machine learning in the form of generative design to identify and mitigate clashes between the different models generated by the different teams in the planning and design phase to prevent rework. There is software that uses machine learning algorithms to explore all the variations of a solution and generates design alternatives.
Also, as we study the AI has a crucial role in risk management and project planning. As discussed every construction project has some risk that comes in many forms such as Quality, Safety, Time, and Cost Risk. The larger the project, the more risk, as there are multiple sub-contractors working on different trades in parallel on job sites. There are AI and machine learning solutions today that general contractors use to monitor and prioritize risk on the job site, so the project team can focus their limited time and resources on the biggest risk factors. AI is used to automatically assign priority to issues. An AI Startup launched in 2018 with the promise that its robots and artificial intelligence hold the key to solving late and over budget construction projects. The company uses robots to autonomously capture 3D scans of construction sites and then feeds that data into a deep neural network that classifies how far along different sub-projects are.
If things seem off track, the management team can step in to deal with small problems before they become major issues. It aids in project planning since it optimizes the best path and corrects itself over time. Due to which 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. This frees up human workers for the construction work itself and reduces the overall time required to complete the project. 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.
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. Building managers can use AI long after the construction of a building is complete. AI can be used to monitor developing problems and even offers solutions to prevent problems.
Leaders at construction companies should prioritize investment based on areas where AI can have the most impact on their company’s unique needs. Early movers will set the direction of the industry and benefit in the short and long term.