AI in AECO: For Today and Beyond

AI and machine learning have vast potential in construction. Requests for data, change orders, and open punch items are part of the day-to-day activities in the industry. Machine learning is a good assistant that can analyze this mountain of information. It then alerts project managers to the critical things that require their attention. In several applications, AI is already used during this process... It has benefits, ranging from mundane spam email filtering to advanced safety observation.

Today

• AI and cost overruns

Even the most qualified project teams fail to meet project budgets on mega projects; it's a fact. That's why nowadays ANNs (artificial neural networks) are used on projects to predict cost overruns based on factors such as project size, contract type, and project managers' competence level. Artificial intelligence allows staff to access real-life and personalized training materials remotely, enhancing their skills and knowledge quickly.

PS: This also reduces the time to onboard new resources onto projects.

• AI and generative design

As part of the 3D modeling process, the architecture, engineering, mechanical, electrical, and MEP plans must be federated together as well as the sequence of activities of the respective teams in a software that uses machine learning algorithms to explore all the variations of a solution and generate design alternatives. Generated design software produces 3D models optimized for constraints set by the user. Every iteration brings it closer to the ideal model.

• AI and Risk mitigation

Every construction project has some risk that comes in many forms such as quality, safety, time, and cost. The larger the project, higher is the risk, as multiple sub-contractors work on different trades in parallel on job sites. Today, general contractors use AI and machine learning solutions?to monitor and prioritize risk on the job site.

• AI for Project planning

To solve late and over-budget construction projects, 3D scans of construction sites are assessed with endless combinations and alternatives based on similar projects, and then feed that data into a deep neural network that classifies how far along different sub-projects are. Algorithms in this scenario use reinforcement learning.

• AI for construction safety

Construction workers are killed on the job five times more often than others. In 2022, 1,069 construction professionals died while working, a rate of 9.6 fatalities per 100,000 full-time workers, according to a report released by the Bureau of Labor Statistics (US) Monday.

An algorithm that analyzes photos from job sites, and scans them for safety hazards such as workers not wearing protective equipment can potentially notify supervisors and at the same time compute risk ratings so safety briefings can be held when an elevated threat is detected.

• AI in 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 before by estimating the required components based on plans or defects, then issuing production orders automatically.

• AI in Post-Construction

Once buildings have been constructed, whether they are used for commercial or residential purposes, AI systems can be utilized for asset and facility management. Artificial intelligence can inspect, monitor, and predict maintenance especially when there a live integration with IoT devices. A good example for a cutting edge solution is Bentley Systems 's Bridge Monitoring. (to find more about it https://www.bentley.com/solutions/bridge-monitoring/)

• AI and Big Data

At a time when a massive amount of data is 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, Lidar, security sensors, building information modeling (BIM), and others has become a pool of information. This presents an opportunity for construction industry professionals and customers to analyze and benefit from insights that are ai-generated.

Artificial intelligence is the science of making machines do things that would require intelligence if done by humans” – John McCarthy

• AI and Productivity

AI is used to manage tasks and project controls. For example, workers can input sick days, vacancies, and sudden departures into a data system and it will adapt the project accordingly. Some companies offer self-driving construction machinery to perform repetitive tasks autonomously and more efficiently than their human counterparts, such as pouring concrete, bricklaying, excavation, welding, and demolition.

• AI and Labor Shortages

Construction companies use AI and machine learning to better plan for labor and machinery distribution across activities. An algorithm 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.

Into the Future

Robotics, the Internet of Things, and AI can reduce building costs by up to 20%!

Engineers use virtual reality goggles and send mini robots into buildings under construction to trace the work as it progresses.

AI is used to arrange the routing of plumbing and electrical systems in modern buildings and to develop safety systems for worksites.

AI is also used to trace the period interactions of employees, objects, and machinery on the location and alert supervisors of potential issues of safety, construction errors, and productivity problems.

AI will alter business models within the construction industry, reduce expensive errors, reduce worksite injuries, and deliver efficient building operations. Leaders at construction corporations should prioritize investments based on areas where AI will have the foremost impact on their company’s distinctive wants.

Early movers can set the direction of the business and profit in the short and long run. If construction productivity is enhanced by as much as 50%, it is estimated to bring an additional $1.6 trillion into the industry’s value each year and further boost the global GDP.

• Design Optimization

One of the primary things to discuss when talking about AI and construction is the design process as well as the factors that influence it. The design phase now could be rather archaic, and slow to adopt new technology, therefore slowing the process of creating a building. Using AI, contractors, and owners will use a supervised learning system from collected environmental information, material data, building information, etc. to identify the best way to create a building or maybe a community.

An AI-powered tool might advocate to a builder what specific design languages, materials, and cost area units are required to create the house based on available data, almost instantly.

• Quality Control

Both the contractor and the future occupants benefit from quality control, which can be tedious but crucial. In this case, neural networks, the basis for artificial intelligence, may prove helpful. The use of neural networks could enable comparison of existing models against various construction inconsistencies based on drone-collected images. This method allows owners and contractors to predict potential problems before they occur, resulting in time and cost savings.

• Business Model

AI is used to better understand customers’ wants, making custom brand experiences. the globe of smart construction won't be any different. Understanding client wants is going to be the new age of "personalized" construction.

• Project Lifecycle

Though still a far-off, smart construction could also be fully passing a future AI system, an idea that is both exciting and scary for many in the industry. The proper AI system may probably work with clients on their designs, produce the final design and send a robot out to complete it, all whereas being passed by just a few individuals.

• Smart 3D Printing

As a result of AI, 3D printing homes have become commonplace. Using smart robotics, contractors can build homes in hours instead of weeks or maybe years. Learning from simulations, builders would possibly use fully autonomous robots to construct full-scale communities and even cities in the near future.

• Modular Construction

Modular homes are a unique and relatively new addition to the construction industry. In short, these houses are often built offsite saving time and resources, and eventually to be delivered to the area of their selecting. AI may eventually make this method even more efficient with auto supply chain coordination.

• Project Management

AI manages all tasks while not breaking a sweat and provides future construction programs with calculated risks, constructability, and also the structural stability of various technical solutions for mega commercial projects, single homes, and projects out of this world.

Finally

Data is the name of the game and can be for several of the topics on this list. AI permits players in this industry to investigate huge amounts of knowledge in real time drastically cutting inefficiencies and waste all the way down to a fraction of what it had been years ago.