Artificial Intelligence in Construction Industry

🚧 Future of AI in Construction Industry 🚧

Over $10 trillion is spent annually on construction-related activities by people and corporations worldwide, and that figure is expected to increase by 4.2% through 2023. Spending on and made possible by the quick-moving technical innovations that affect every aspect of the ecosystem make up a portion of this vast amount of spending. The Next Normal in Construction: How Disruption is Shaping the World’s Largest Ecosystem, published in 2020, by McKinsey noted an increasing interest in artificial intelligence-based solutions (AI).

🚧 What is Artificial Intelligence and Machine Learning in Construction?

When a machine duplicates human cognitive functions including problem-solving, pattern recognition, and learning, it is referred to as Artificial Intelligence (AI). Machine learning (ML) is just a subset of artificial intelligence. Machine learning incorporates statistical techniques into electronic devices like computer systems, to enable the capability of learning from data without having to be explicitly programmed. A machine is exposed to more data, so it improves its ability to interpret and provide insights.

For example, in construction technology, a machine learning algorithm may follow and analyze progress in a grading plan in order to discover scheduling hazards early. To establish a risk score and assess whether notifications are required, the program may ask questions regarding cut and fill volume measurements, weather trends, previous projects, machine uptime, and downtime, or any number of inputs.

🚧 AI and ML – Smart Construction Technology

AI and Machine Learning have a lot of potential in the Architectural, Engineering, Construction and Operation (AECO) industry. Making an entire list of all possible uses is not possible in a single article. For example, a few years ago, our mailboxes were filled with a lot of spam emails whereas in today’s scenario we probably receive relatively few. The reason behind it is that spam filters now rely on machine learning to detect trends and keep spam at bay, and they are really excellent at it.

While this is not a construction-specific application however the application solves the in-general issues and impacts everyone irrespective of their industry. The technology is allowing us to be more productive and focused on our work-related conversations rather than wasting time on deleting irreverent emails.

On any given day, a typical construction project may contain several change orders, hundreds of RFIs and thousands of open issues. Imagine having a smart assistant who can sift through this mound of project data and send you an alert about the top ten things that need your attention right now. Machine learning is that smart helper, assisting teams in identifying the most essential risk variables that require immediate attention from the perspective of construction safety and quality.

10 Application of  AI (Artificial Intelligence) in Smart Construction 

👉 1. Prevention of Project Over-budget by AI

Despite having the best project teams, most major projects go over budget. On projects, multiple AI powered software are used to anticipate cost overruns based on parameters such as project size, contract type, and project manager competence. Predictive models employ historical data such as projected start and finish dates to create realistic timetables for future projects. AI enables employees to gain remote access to real-world training materials, allowing them to quickly improve their skills and expertise. This cuts down the time it takes to onboard new professional to projects and results in faster project completion.

👉 2. AI Improvised building design through generative BIM design

Building Information Modeling (BIM) is a process of generating data-rich 3D model that helps designers, architects, engineers, modelers, drafters, and construction professionals to plan, design, build, and manage buildings, facilities, infrastructure, maintenance, and operation more efficiently. The 3D models must be taken into account with respect to the architecture, engineering, mechanical, electrical, and plumbing (MEP) plans in order to plan and design the building project. The coordination and collaboration amongst multi-disciplinary project teams and models are essential to detect clashes and resolve them during the preconstruction stage. This results in efficient construction completion.

To avoid rework, the construction industry employs machine learning in the form of AI-powered generative design to discover and minimize incompatibilities between the multi-trade models generated by the multiple project teams. There is software that utilizes machine learning algorithms to investigate all possible solutions and generate design options. When a user indicates requirements into the model, the generative BIM design software develops 3D models that are optimized for the constraints, learning from each iteration until the optimal model is found.

👉 3. AI for Improved Risk Management

Every construction project has some risk, which can take numerous forms, including quality, safety, timeliness, and cost. Because several subcontractors are working on different disciplines on job sites at the same time, hence the greater the project, the higher the risk. Today, general contractors employ AI and machine learning technologies to monitor and prioritise risk on the construction site, allowing the project team to spend their limited time and resources on the most critical risk variables. AI is used to assign priority to issues automatically. Construction managers can engage closely with high-risk teams to decrease risk by assigning a risk score to subcontractors.

👉 4. AI for Strategic Project Planning

In 2017, one construction intelligence start-up announced that their robotics and artificial intelligence would be the solution of fixing late and overbudget building projects. Robots acquire 3D scans of construction sites autonomously, which are then fed into a deep neural network that classifies how far along different sub-projects are. If things begin to go wrong, the management team can intervene to address minor concerns before they become large problems. Future algorithms will employ an AI approach known as “reinforcement learning.” Algorithms can be learned through trial and error using this technique. It can evaluate an infinite number of combinations and alternatives depending on previous work. Because it optimizes the optimal path and corrects itself over time, it helps with project planning.

👉 5. AI for More Productive Job-site

Some construction companies are offering self-driving AI-powered construction machinery to execute repetitive operations more efficiently than human counterparts, such as welding, bricklaying, demolition, and pouring concrete. Excavation and preparation work is done by semi-autonomous or autonomous bulldozers with the help of a human programmer to prepare a specified job site. This frees up human labor for the actual construction job and cuts the overall completion time of a project 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, Unmanned Aerial vehicles (UAV), Drones, onsite cameras, and other similar technology.

👉 6. AI for Better Safety

As per a report by Occupational Safety and Health Administration (OSHA) “FALLS ARE THE LEADING CAUSE OF DEATH IN CONSTRUCTION. In 2018, there were 320 fatal falls to a lower level out of 1,008 construction fatalities (BLS data).” An algorithm developed by a Boston-based construction technology company analyzes photos from its job sites, identifies safety dangers such as construction staffs not wearing protective equipment, and compares the images to its accident data. According to the company, it may theoretically compute risk ratings for projects in order to hold safety briefings when an elevated threat is discovered.

👉 7. AI Identifies Labor Shortages

Construction companies are investing in AI and data science due to labor constraints and a drive to improve the industry’s low productivity. Construction firms are beginning to adopt artificial intelligence (AI) and machine learning for construction management resulting better arrangement of manpower distribution and equipment across jobs.

With the help of Artificial Intelligence and robots, project managers can instantly know which job sites have enough people and equipment to complete the project on time, and which are falling behind and might use additional personnel. Robot continually analyses job progress and the placement of workers and equipment. Spot the Dog, an AI-powered robot, can independently inspect a project every night to assess work progress, allowing contractor to complete more work in remote places where trained labour is scarce.

Use BIM Automation to Automate Modeling and Design Activities

Resources :- Trimble Connected Construction Industry

👉 8. AI-Powered Off-site Construction

Off-site facilities staffed by automated systems are increasingly utilized by construction businesses to piece together building components, which are subsequently patched together on-site by human workers. For example, Walls can be built more effectively on an assembly line by autonomous machinery than by humans, leaving human workers to handle the specific work such as HVAC, Mechanical, electrical, Plumbing (MEP) and systems once the building structure is put together.

👉 9. AI Integrated with Big-data in Construction

AI systems are vulnerable to an infinite quantity of data to learn from and develop data on every day at a time when vast amounts of data are being created every day. Every building construction site becomes a possible data source for artificial intelligence. Data collected from building information modeling (BIM), drone captured data, mobile device photos, onsite security sensors, and other sources has accumulated into a pool of data. With the use of AI and machine learning systems, construction industry professionals and clients will be able to identify and get an overview from the data.

👉 10. AI for Maintenance and Operation

Long after the work is finished, building managers can use AI. Advanced analytics and AI-powered algorithms generate useful insights into the operation and performance of a road, bridge, building, and nearly anything in the built environment by gathering information about a structure using drones, 3D Laser Scanners, sensors, and other wireless technologies. This implies Artificial Intelligence can be used to track the progression of issues, identify when preventative maintenance is required, and even identify human nature for maximum security and safety.

🚧 How AI works in simple terms?

Future of AI in Construction Industry

Artificial intelligence uses the cognitive power of computers to simulate human intelligence. Artificial intelligence can be gained in two ways:

👉 Machine learning – Machine learning (ML) is the study of computer algorithms that can learn and develop on their own with experience and data. Computers are capable of recognizing patterns and learning from examples. For instance, Machine learning keeps spam out of email inboxes. Examples of emails categorized as spam and non-spam have been fed into the algorithms.

👉 Deep learning – Deep learning simulates the neurons in the brain, taking machine learning to the next level. As computers and algorithms process more data over a longer period of time, they learn and adapt their algorithms in the same way that humans do. Deep learning in construction is utilized to recognize project type, material requirements, scheduling, predict scenarios, and respond accordingly.

🚧 The Future of AI in Construction 🚧

Despite projections of significant job losses, AI will not be able to completely replace the human workforce. Instead, it will change the business models of Architecture, Engineering, Construction and Operation (AECO) industry mitigating jobsite injuries, reducing costly errors, and increasing the efficiency of construction operations.

Construction professional should focus their investments on areas where AI may have the greatest influence on their business and project specific demands. Early adopters will shape the industry’s future and benefit in both the short and long term. Tejjy Inc. being one of early adopter of advanced technology like AI-powered Virtual Reality &  Augmented Reality (AR & VR), Drone and 3D Laser Scanning technology, providing ISO-certified quality assured construction project management and Tejjy BIM services to the Architecture Engineering and Construction (AEC) industry in the USA. With the presence in multiple locations in the USA including Maryland, Washington DC and Alaska our expert BIM professionals, Engineers, Architects and Drafters served over 2400+ happy clients.