AI in Civil Engineering

Deep learning technologies have been effectively employed in a variety of industries for many years, including civil engineering. Indeed, with the emergence of complex constructions such as skyscrapers, machine learning techniques grabbed centre stage in the sector a long time ago. We are seeing the application and growth of AI in the construction industry more than ever before, with intelligent algorithms, big data, and deep learning machines transforming productivity performance.

AI has been used by practising civil engineers, contractors, and service providers to tackle a wide range of challenges. Artificial Intelligence in civil engineering, for example, has advanced to the point where efficiencies are fed directly into construction processes. AI is also used in the early stages of many projects to improve design, risk management, and productivity. It is critical to understand that construction organizations who have already begun to apply AI processes are 50% more profitable. More importantly, Artificial Intelligence (AI) as a whole offers a wide range of applications in civil engineering. Engineers can make better decisions and deliver their services more effectively in an age where robots can think rather than just do.

1) For better designs of buildings:

With iconic structures of all shapes and sizes dotting the skylines of major cities throughout the world, we can all agree that the boundaries and standards of design and engineering have been pushed to their limits. All of this is possible because to the industry’s biggest game-changer: Artificial Intelligence in 3D Building Information Modelling (BIM).

2) To overcome costs/schedule overrun:

Most mega construction projects go over budget and are prone to mistakes because they are frequently created in a short timeframe and with limited information about the scope of the entire project.

Although cost overruns are unavoidable, using AI in construction allows an engineer to have a clear picture of cost estimates and outcomes from past projects, allowing for improved planning and budgeting. Civil engineers can foresee cost overruns and envision realistic timetables for existing projects using learning algorithms that use features of completed projects.

Furthermore, AI allows engineers to access remote sites and assists them in implementing real-time training resources in order to increase abilities and team leadership.

3) On-site smart construction to expedite project completion:

Some companies are offering self-driving construction machinery to perform repetitive tasks more efficiently than humans, such as pouring concrete, bricklaying, welding, and demolition. Excavation and preparation work is done by autonomous or semi-autonomous bulldozers, which may prepare a task site to exact specifications with the help of a human programmer. This frees up human labour for the actual construction job and cuts the project’s overall completion time in half. Project managers can also monitor work on the job site in real time. They monitor worker productivity and process compliance using facial recognition, onsite cameras, and other similar technology.