AI's integration with BIM is written by Manish Sharma, Chief Product Officer of Build and Constructs at Nemetschek Group.
Tackling rising costs and operational challenges associated with increasing demand, tensions in capacity, and increased regulatory and crisis management pressures has become a serious concern for healthcare and hospitals around the world.
Worse, many efforts to resolve these problems through strategic construction and renovation have been repeatedly thwarted by unusually high material costs, sustained labor shortages, and other pressures affecting the world's AEC/O landscape.
Whether dealing with new or existing facilities, these challenges underscore the urgent need for hospital operators and AEC/O partners to adopt intelligent, modernized construction and building management solutions.
Fortunately, the required conversions are complex and spanning all project phases, but coincides with the rapid advancements in artificial intelligence (AI).
AI's integration with Architectural Information Modeling (BIM) and other assistive technologies promises to accelerate modernization and lead a new generation of future-ready medical facilities for the benefit of patients and providers around the world.
Centralize data and optimize management throughout the building lifecycle
One of the major challenges in building, renovating and maintaining hospitals is managing the vast amount of critical data generated throughout the lifecycle. Without a truly unified data management solution, collaboration between stakeholders is difficult, often resulting in higher costs, avoidable errors and unreliable decisions.
This long-standing problem has plagued AEC/O experts for decades. Nemetschek Group has worked to address all project data through solutions such as Drofus, a cloud-based planning and data management platform that centralizes all project data and provides real-time visibility throughout the building's lifecycle. Even early versions of this technology have significantly improved efficiency and collaboration, particularly in the construction of new medical facilities.
A major example is the Glasblokkene Trinn 2, a 50,000-square-meter children's hospital in Bergen, Norway, designed and built using digital twins created from the Dolofass master database.
By leveraging digital twins from the early planning stages, stakeholders can access all relevant data when needed, improving collaboration and avoiding costly delays and errors common to fragmented documents.
The benefits realized in this project reflect what we call building lifecycle intelligence. This is an approach that bridges the data gap, preserves information value across design and construction, and enhances long-term operation.
With the continuous integration of AI and machine learning, these benefits will only grow. Deepen insights, improve prediction accuracy, and expand automation throughout the lifecycle.
Hospital safety and regulatory compliance revolution
Another important challenge facing modern healthcare facilities is the need to design and build unique safety and regulatory standards. More than most building environments, hospitals need to meet and maintain very strict building requirements to protect patients and care providers. Ensuring compliance with all regulations can be extremely expensive and time-consuming for your construction and maintenance team.
Whether to ensure reliability of fire walls, ventilation or alarm systems, traditional risk identification and mitigation processes are inefficient and relying excessively on manual inspections. However, this issue is currently being addressed by innovative, digital-first solutions like Imerso. It leverages a combination of BIM, reality capture and AI technology to automate construction monitoring and safety inspections.
For example, Imerso's AI-powered software is an invaluable tool for the construction and engineering team at Nordsjælland, NYT hospital outside Copenhagen, using technology to streamline the construction and compliance of fire walls throughout the facility.
By incorporating Imerso, they were able to automate multiple critical processes related to hospital firewalls, including quality monitoring during the planning stage, risk identification, system testing, and even aggressive safety verification.
As a result of these important modernization efforts, NYT stakeholders have dramatically reduced construction times, increased productivity and completed the project for 5.2 million euros with estimated cost reductions.
Additionally, the team reports that the ongoing use of Imerso has increased monitoring capacity by 15 times compared to previous methods, using only 7% of its resources.
Supporting the rapid evolution of healthcare
While these early use cases may be impressive, the true potential of these technologies lies in the ability of AI-powered systems to learn and improve through continuous development and adoption. Rather than being limited to niche applications, AI is expanding rapidly to support a broader trend in the healthcare industry's wider evolution.
For example, improving sustainability to combat climate change is the number one priority to ensure that hospitals and care facilities, who are responsible for around 5% of the world's carbon emissions each year, are responsible for the responsibility. This problem is particularly pronounced in the United States, where hospitals make up about 8.5% of annual emissions.
This has emerged several regulatory obligations and incentives to address the environmental impact of the industry, such as the UK's Sustainability and Transformation Program (STP) and the International Joint Commission's Healthcare Sustainability Certification.
This is an area where AI-based solutions already show strong potential. By integrating AI and machine learning into design and construction planning, teams can run virtual simulations to proactively assess environmental impacts and identify strategies to maximize sustainability. In operations, AI monitoring and predictive maintenance tools can help optimize energy use and reduce waste.
Another notable trend is the growing demand for decentralized care found in the construction of smaller community-based facilities and modular care units that expand capacity and increase infrastructure flexibility. In addition to enabling fast and efficient construction of new care centers, renovation and modular enhancement of existing facilities can benefit greatly from tools such as Imerso, Drofus and similar technologies, particularly for space optimization and regulatory compliance.
Finally, the global healthcare industry is currently on a accelerated, long-term path to digital transformation. It is also clear that AI has become essential to enable hospital infrastructure to meet complex demand and rapid innovation. As the global healthcare ecosystem evolves and the AEC/O sector deepens the integration of these tools, AI is expected to not only transform the way hospitals are designed, built and operated, but also dramatically improve the access and quality of care for patients around the world.
*Please note that this is a commercial profile.
