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 interior finishing. Each of these phases has specific requirements and uses different technical approaches to optimize processes and increase efficiency.
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Drones equipped with high-resolution cameras and LiDAR scanners capture detailed data from the construction site. This data is analyzed by AI algorithms to create topographical maps, monitor progress and identify potential problems at an early stage.
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Cameras attached to cranes continuously capture video footage of the construction site. AI algorithms analyse these videos to track progress, document and optimize work.
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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 issue warnings.
Some systems use AI-supported cameras to monitor compliance with protective clothing regulations, for example. In addition, danger zones can be defined in certain camera systems to monitor people entering. Violations are reported in the form of real-time warnings.
AI helps to record, analyze and optimize construction processes. These systems collect data from various sources (e.g. cameras or machine data) and use machine learning to record the current status, recognize patterns and identify the best courses of action.
Cranes equipped with intelligent systems can increase efficiency and safety on construction sites. These cranes are equipped with crane hooks, for example, which record the weight of the loads and can also identify the lifted object with an integrated camera. The data collected can be used to optimize crane utilization and minimize potential safety risks. Examples of such technologies are CAD24 and Versatile.
The recording of work processes with cameras enables detailed monitoring and analysis of repetitive trade sequences on the construction site.
In addition, key production figures such as component utilization, throughput times, working hours and expense values are recorded. If a repetitive sequence of trades is analyzed in detail, acceleration potentials can be identified. Monitoring the critical path is particularly important, as this allows bottlenecks and potential delays to be identified at an early stage.
Time-critical components are often identified and their utilization monitored in order to optimize the cycle time. Another important factor for shortening construction time is adapting the direction of work to the column movement of different trades. The shell construction time can be reduced by 10 to 20 % by adapting the cycle time to the real data.
Click for an example of recording workflows.
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.
Examples of manufacturers of such systems:
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.
