Implementation of neural networks in the construction industry

The use of artificial intelligence in the construction industry is rapidly expanding, and by 2030 the AI market in this area will reach $2.5 billion. Such figures were given by researchers from Market Research Future. At the same time, neural networks are expected to become the main growth driver for this market, since it is they that allow the digital “mind” to learn and make more and more effective decisions each time.

In this article, we will talk about exactly how the technology of neural networks is used in modern construction.

Artificial neural networks (ANN) is one of the methods of artificial intelligence that imitates the work of the human brain at the software level. It uses digital analogues of biological neurons in a layered structure and creates an adaptive system, thanks to which computers have the opportunity to learn from their mistakes and constantly improve themselves.

The importance of neural networks lies in the fact that they are able to quickly process huge amounts of data and make intelligent decisions with minimal human intervention.

There are several main types of neural networks:

• Neural networks of direct distribution. Perform data processing in one direction, from the input node to the output, and use the feedback process to improve decisions.

• ANN with backpropagation algorithm. This is a more complex type of neural networks in which data processing does not proceed linearly, but along many different paths. In this case, only one path will be correct, which can match the input node with the correct output node. To improve the accuracy of the results, such ANNs use corrective feedback loops, taking into account the “weight” of the nodes.
• Convolutional neural networks. In such ANNs, the hidden layers are able to perform various mathematical functions, such as summation or filtering, which allows them to extract the necessary data from the general stream, classify them according to relevant features, and make informed decisions.

The choice of the optimal type of neural network directly depends on the tasks that ANN will solve in a particular business.

If earlier neural networks were used mainly at the stages of preparation for construction – during the planning and design of architectural structures, today their use has expanded significantly. Here are some of the more common options.

Generative design

Generative design with the help of machine learning algorithms is able to imitate the engineering approach to the design of architectural structures. Using such a tool, it is enough for a specialist to enter the necessary parameters into the system – requirements for space, materials, number of rooms and their purpose, cost restrictions, etc., and in response, the program will issue thousands of unique implementation options within the specified criteria.

At the same time, the engineer does not need to make drawings and carry out calculations on his own – just choose the most suitable option and, if necessary, modify it a little. As a result, we get dozens of hours of saved time and reduced costs for the work of qualified specialists.

Calculation of the budget and preliminary estimate

Neural networks are used to predict potential cost overruns and help generate the most accurate budget for a project. To do this, they determine the specification of materials and equipment that are included in the project, analyze data on their cost and availability in the desired region, take into account the planned dates for the start and end of construction, and many other parameters.

The use of neural networks in calculations will be useful not only at the development design stage, but also in the future, if necessary making changes to the construction plan.

Material Cost Forecasting

Neural network solutions can be used to accurately predict building material consumption based on historical data. This can minimize waste, optimize procurement, and reduce project costs.

Security monitoring

Artificial intelligence based on neural networks is able to monitor the territory of the facility in real time and identify potential threats to the life and health of specialists. In this way, the company can minimize the risk of accidents at the construction site.

For example, a Japanese company has created software that, using special sensors, collects data on the movement of specialists and determines when they are at risk of falling from scaffolding.

Improving Energy Efficiency

Neural network-based services allow engineers to monitor and analyze the energy efficiency of buildings in real time, and also offer optimal solutions for improving performance.

Neural networks are rapidly being introduced into many areas of business, and the construction industry is no exception. The use of ANN helps construction companies optimize internal processes, increase their efficiency and speed up the construction of architectural structures. Ultimately, this has a positive effect not only on competitiveness, but also on the profitability of the entire business.

Our team selects unique technical solutions for each company and helps clients improve their operations through the implementation of innovative solutions based on neural networks. We have experience in implementing a wide variety of cases in this area, using which we can bring your most daring ideas to life.