Thanks to artificial intelligence, the construction industry is moving into a new era of digitalization and optimization.
This is because AI technologies are increasingly being used in construction to record construction progress, optimize processes, increase efficiency and improve safety.
This blog takes a look at various applications of AI in construction and highlights specific examples that illustrate the benefits of these technologies.
Automated construction progress monitoring uses AI-supported systems to monitor construction progress in real time. Camera systems are used almost exclusively for this. These capture data from the construction site, which is analyzed by algorithms to track progress and detect deviations.
The use of AI technologies varies depending on the construction phase, be it earthworks, shell construction or finishing. The data obtained enables an objective assessment of the project status and improves transparency for clients and project participants.
Technology description
Stationary or mobile cameras are used, usually with a 360-degree function, which continuously supply images or video streams of the construction site. This image data is analyzed by computer vision. Based on construction drawings, schedules and target data, the AI recognizes whether certain construction elements such as walls, ceilings or installations have already been completed. This means that the actual status can be automatically compared with the planning status - on a daily basis.
AI can analyze different scenarios and create intelligent schedules based on real-time data and implemented information. These technologies help to predict delays and suggest countermeasures in good time.
Technology description
Scenario analysis begins with comprehensive data collection from various sources such as sensors, cameras, construction machinery and management software. This data is integrated into a simulation model that uses machine learning and predictive analytics to create different scenarios. The model tests different variations to assess the impact of changes in the construction process. The results are analyzed to determine the best strategies in terms of schedule, cost, quality and potential risks and bottlenecks.
Intelligent schedule creation uses various input parameters (e.g. effort values or column strength) to create dynamic and realistic schedules. By adjusting the input parameters, different scenarios can be displayed and checked. This enables a quick and time-optimized response to situations of varying complexity.
AI-based systems for resource management optimize the use of materials, machines and personnel. By analyzing data, demand can be predicted precisely and the use of resources can be planned efficiently.
Technology description
Real-time data from the construction site (e.g. from sensors) is collected and analyzed to monitor the current resource status. AI algorithms forecast future demand and identify potential bottlenecks. This predictive planning allows resources to be optimally allocated and waste to be avoided.
There are various platforms that help construction companies to manage subcontractors and materials effectively. AI analyses historical data and real-time information to predict demand and optimize the availability of resources. This leads to better planning and reduces material waste.
AI systems to improve occupational safety continuously monitor the construction site and detect potential hazards at an early stage. Sensors and cameras record safety-relevant data, which is analyzed by algorithms to identify risks and report warnings.
Some systems use AI-supported cameras to monitor compliance with the wearing of protective clothing, for example. In addition, some camera systems can define danger zones that are monitored for people entering them. Violations are reported in the form of real-time alarms.
Technology description
Visual recognition systems with deep learning models for object recognition and classification are primarily used. Cameras continuously record what is happening on the construction site and analyze, for example, whether people are wearing helmets or safety vests. In addition, virtual zones can be defined in the image, which automatically trigger an alarm if they are exceeded. Some systems combine image data with sensor data (e.g. from wearables or machines) to enable more comprehensive safety monitoring.
Cranes equipped with intelligent systems can significantly increase efficiency and safety on construction sites. These systems not only record the weight of the loads, but also use integrated cameras to detect which component is being moved. The collected data can be used to optimize crane utilization and identify potential safety risks at an early stage.
Examples of such technologies are CAD24 or Versatile, which are already in use on many large construction sites.
Technology description
The intelligent crane hooks combine weight sensors, cameras and AI-based analysis. The collected data is automatically processed to evaluate movement sequences, identify risks and improve the material flow. The systems learn with every use and can make increasingly better predictions.
Click for an example of recording workflows.
Another approach to optimizing construction work is the systematic tracking of construction processes using cameras. The processes of individual trades, especially repetitive activities, are recorded and analyzed. The aim is to identify bottlenecks at an early stage, improve throughput times and create more efficient processes overall.
In addition, key production figures such as cycle times, downtimes and component utilization can be recorded automatically.
Technology description
Stationary or mobile cameras are mainly used here, which continuously capture images or video footage of the construction site. Computer vision and machine learning are used to evaluate these images for specific work steps. The AI recognizes patterns, measures time intervals and creates analyses of process quality based on this.
Autonomous construction machines equipped with AI technology can carry out construction tasks independently. These machines use sensors, GPS and machine learning to maximize their work volume.
Technology description
Autonomous construction machines can carry out defined tasks independently. These machines are equipped with a variety of sensors such as lidar, radar and cameras that record their surroundings in real time. By integrating artificial intelligence (AI) and machine learning algorithms, they can recognize obstacles, plan a work strategy and navigate safely without the need for a human operator to be on site.
Manufacturers of such systems include Build Robotics and the Israeli start-up IntSite, which focuses on autonomous cranes.
The integration of artificial intelligence in construction offers enormous advantages in terms of efficiency, safety and quality.
From automated construction progress monitoring and intelligent scheduling, resource management and occupational safety to process optimization, autonomous construction machinery and 3D data generation - the applications are diverse and are already changing the way construction is carried out in practice. Companies that use these technologies can not only complete their projects more efficiently and cost-effectively, but also significantly improve the safety and quality of their construction projects.
The future of construction is digital and intelligent - and AI plays a central role in this.
