Digitalisation in the construction industry is in full swing: data and open data interfaces are becoming increasingly important
Digital transformation has gained significant momentum in recent years. The fact that digitalisation in the construction industry is pointing upwards is not only due to the Covid-19 pandemic and a general increase in interest in digitalisation topics, but above all to the convincing added values that can be achieved along the entire value chain with the help of digital tools.
These include, for example, better overall planning of projects and the associated resources, increased cost and schedule reliability through simulations with the digital twin, improved communication and collaboration between the numerous trades involved – especially in large projects, faster coordination through paperless processes and stringent quality assurance across all project phases. There are benefits in terms of sustainability, too – the construction sector is, after all, responsible for almost 40% of global carbon emissions – enormous potential is available through increased efficiency in construction and operation, better planning of materials, improved recycling and the reduced production of waste.
Artificial Intelligence is trending in the construction industry
While digitalisation has already made inroads in the construction industry, another technology is now well on its way to becoming an integral part of the construction process: artificial intelligence (AI). With the expansion of Building Information Modelling (BIM) to the entire construction lifecycle and the associated transition to data-driven design and construction, ever greater volumes of data are being generated in all phases of a project. The question of how these can be not only processed but also used intelligently is already finding great resonance in business as well as in research. Many start-ups, as well as established research institutions such as the Technical University of Munich or the Institute for Applied Construction Informatics at the Munich University of Applied Sciences, are intensively working on tangible application possibilities for artificial intelligence in the construction industry.
The importance of the topic of AI in the meantime can be seen in the example of the Munich-based Nemetschek Group, one of the digitalisation drivers in the industry since its founding in the 1960s. The company invests in up-and-coming companies that complement their existing portfolio of solutions for the complete value chain from planning to construction to operation.
One example is US-based Reconstruct. In the past few years, the company has achieved continuous growth of around 300% with AI solutions, becoming the US market leader for remote quality control and progress tracking. At the other end of the construction value chain in operations and management is Spanish company DEXMA: with its energy experts, the start-up develops intelligent energy data management solutions to minimise the environmental footprint of organisations and buildings. By using AI-based data, owners and operators receive precise forecasts about the behaviour of their buildings and can thus reduce energy costs.
Achieving more with data – throughout the building lifecycle
All stakeholders in the building value chain are spending more and more time as information managers and organising, structuring and interpreting that information. Artificial intelligence and machine learning are proving to be powerful tools in this context to further maximise the value and potential of data and make timely decisions faster – with positive impacts across the entire AEC/O lifecycle.
AI and machine learning are fuelled by data. Using historical data, machine learning enables future outcomes to be predicted based on past developments, patterns to be identified and new insights to be generated in a whole new way. In the planning and design phase of buildings, architects and engineers are already benefiting from innovative software tools that help identify rule-based collisions between models, create accurate construction simulations and schedules, and increase the efficiency of the design phase. In the future, the use of AI in planning and design will help automate traditionally manual tasks and provide technologies that enable cost-optimised, faster and higher quality work. The need to successfully complete projects with fewer resources has given further impetus to the demand for insights from AI and machine learning.
During construction, project managers and site workers need to make the best use of available resources. The construction industry has always struggled with time and cost overruns, especially as projects become larger and more complex. When combined with monitoring data from construction sites, such as photos, videos and field sensors, patterns that lead to problems can be identified. Project managers can take corrective action faster – even before problems become critical and affect the progress of the construction project.
Improved efficiency for a more sustainable construction process
On most projects, coordinating the large number of workers, materials and machines presents significant logistical and scheduling challenges. Here, AI can have a profound impact on construction site coordination, too. Scheduling deliveries to the jobsite and procuring materials are areas that are significantly improved through more efficient routing, loading and inventory management using AI solutions. Downtime is minimised as resources can be better planned for material tracking and equipment utilisation.
While efficiency is the main driver for AI in the construction industry, there is now an increased focus on end-user requirements and the desire for more sustainable buildings. Once a project is complete, AI provides additional benefits throughout the facility’s operation. Sophisticated building management systems that integrate information from internet-connected sensors and other data collection devices are quickly becoming commonplace.
No other new technology has the potential to transform the entire building lifecycle on such a scale as artificial intelligence. As data plays an increasingly important role in the design, construction and operations process thanks to BIM, using AI to further increase efficiency and meet user needs is the next logical step in the evolution of the AEC/O industry.
For the construction industry to realise the full potential of AI-based technologies in the future, one thing will be required above anything else: a smooth flow of data – no matter where project participants are regionally located, regardless of which software solution they prefer and across all phases of construction. With the openBIM philosophy, a promising approach already exists; now, it is a matter of also implementing the cultural change. The close and cooperative collaboration of all project participants will only become more important in the future.
Corporate Communication & CSR