What are the benefits of AI in the construction industry?

In today's high-tech era, every industry needs to go with technology if it does not want to be phased out. In recent years, AI has gradually been used more in the CE industry, improving the efficiency and safety of the work site.

 

 

What are artificial intelligence and machine learning?

 

Artificial Intelligence (AI) is a collective term used to describe when a machine imitates human cognitive functions (such as 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 enable computer systems to "learn" from data without explicit programming. When the machine is exposed to more data, the machine will better understand and provide insight.

 

 

Several major benefits of AI to the construction equipment industry

 

1. Prevent cost overruns

Despite hiring the best project team, most large projects are over budget. Artificial neural networks are used in projects to predict cost overruns based on factors such as project size, contract type, machines used (such as bucket diggers and mud bucket excavators) and manager’s ability level. Predictive models use historical data such as planned start and end dates to imagine the actual schedule of future projects. AI helps employees remotely access real training materials, helping them quickly improve their skills and knowledge. This reduces the time it takes to load new resources onto the project. As a result, project delivery has been accelerated.

 

2. Design better through generative design

Building information modeling is a 3D model-based process that provides architecture, engineering, and construction professionals with insight to effectively plan, design, construct, construction machine spare parts, and manage buildings and infrastructure. The industry is trying to use machine learning in the form of generative design to identify and alleviate the conflicts between different models generated by different teams during the planning and design stages to prevent rework. There is software that uses machine learning algorithms to explore all variants of the solution and generate design alternatives.

3. Risk mitigation

Every construction project has some risks, including quality, safety, time and cost risks and other forms. The larger the project, the greater the risk, because there are multiple subcontractors working on different industries in parallel on the job site, including bucket chain excavators, Komatsu wheel loaders, Kobelco blade runners and so on. Today there are artificial intelligence and machine learning solutions that are used by general contractors to monitor and prioritize risks 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 priorities to issues. Subcontractors are rated based on risk scores, so construction managers can work closely with high-risk teams to reduce risks.

 

4. Construction safety

The number of deaths of construction workers at work is five times that of other workers. According to the OSHA report, the main cause of death in the private sector in the construction industry (excluding road collisions) is falling, followed by object impact and electrocution. The Boston-based general contractor has annual sales of $3 billion and is developing an algorithm that can analyze photos of the work site, scan them for safety hazards, such as workers or bucket shovel excavator drivers without protective equipment, and associate the images with accident records. The company said it can calculate the project's risk rating, so it can conduct a security briefing when it detects an elevated threat.

 

5.AI will solve the problem of labor shortage

Some companies are beginning to provide self-driving bucket bushing excavators to perform repetitive tasks, such as concrete pouring, bricklaying, welding, and demolition, which is done more efficiently than their human counterparts. Labor shortages and the desire to increase the industry's productivity have forced construction companies to invest in artificial intelligence and data science. Construction companies are beginning to use artificial intelligence and machine learning to better plan the distribution of labor and bucket wheel excavators at work. The robot constantly evaluates the work progress and the location of workers and grading bucket mini excavators, enabling the project manager to immediately inform which workplaces have enough workers and equipment to complete the project on time, and which may be behind where additional labor can be deployed.