Using AI to build sustainably and save money

Building a sophisticated and complex building is often a challenge. It has been likened to navigating a maze where there is an obstacle, dead end or picket fence at every corner. Budget constraints, conflicting design documents, tight schedules and managing a workforce are just a few of the many challenges that project teams face. Now add the increasing pressure to minimize the environmental impact of buildings.

The role of the architect during building visualization and planning cannot be overemphasized. Beyond simply drawing beautiful images and creating intricate building visualizations before design work begins, architects manage stakeholder expectations and grapple with design revisions while trying to weave cost-effective sustainability elements into the documents based on client demand. All of this occurs under the threat of tight deadlines and accelerated project schedules. Unfortunately, architects’ sustainability efforts often falter during the construction process due to unpredictable owner financing, material and labor costs that require budget cuts, or value engineering efforts that affect the original design intent.

General contractors typically face their own set of challenges when it comes to sustainable construction. Many in the construction industry admit to being cautious about adopting new technologies and processes, so conventional building practices often clash with the more rigorous sustainability standards dictated by clients and policy. Even facility managers are struggling to keep up with modern building management systems, which are driven by powerful computers and data, making day-to-day building management more complex and precise than ever before.

In the rapidly changing world of construction, the use of data and new technologies promises to revolutionize the way buildings are designed and constructed. Specifically, AI shows incredible potential and could be a game changer, helping to streamline the design, planning and construction processes, ultimately delivering cost savings for developers and property owners.

DESIGN

Sustainable design continues to evolve to address the carbon footprint of buildings. Embedded carbon refers to the emissions associated with the construction of buildings and can account for 85% of a building’s carbon footprint in its first year. Carbon footprint is largely determined by the choice of building materials, particularly steel and concrete. While most contractors are already making a fair effort to reduce embodied carbon during construction by using feasibility reviews to reduce material usage, challenges still arise from incomplete or inaccurate data sets, particularly in areas such as mechanical, electrical, and plumbing systems. AI offers promise in reconciling material data between databases and BIM models and recommending alternative lower-carbon materials for buildings. Operational carbon refers to emissions generated during everyday use of buildings and poses its own unique set of challenges due to advanced, emerging technologies being implemented for energy efficiency and decarbonization, which require new energy modeling techniques. AI can also help in this regard by mapping optimized paths through parametric analyses.

AI will play a key role in identifying the optimal balance between embodied and operational carbon and driving environmental sustainability and cost savings. The industry is now seeing a number of construction technology startups offering AI-based solutions that can be applied earlier in the project lifecycle to significantly reduce the upfront and operational costs of buildings, ultimately benefiting developers and owners.

CONSTRUCTION

AI has the potential to drive sustainability in the construction process as well. AI algorithms are already optimizing workspaces for minimal environmental impact and streamlining material delivery routes to maximize efficiency. Even waste management is being improved with the power of AI. The construction industry consumes a staggering 93% of all raw materials used annually. To address this challenge, waste processing plants are using AI-powered robots with object recognition to sort mixed waste onto conveyor belts, dramatically increasing material recycling rates and creating a safer work environment for human resources while minimizing environmental impact. AI will also play a role in building dismantling by creating reuse markets and closed-loop systems where recovered materials can seamlessly find new homes in future projects. Steps are already being taken toward applying AI to recycling in real-time and practical ways. For example, startups are using AI and robotics to recycle used lumber by automatically and efficiently removing nails and fasteners from discarded structural lumber and preparing the recycled lumber for use on future construction sites. Other companies are using predictive analytics to help size waste containers and optimize waste collection schedules, resulting in less mess and cleaner job sites.

AFTER CONSTRUCTION

With stringent new regulations and growing sustainability demands across the country, facility managers are facing increased pressure to optimize building performance and efficiency. AI-based monitoring-based commissioning processes, supported by automated fault detection and diagnostic tools, are focused on energy monitoring, analysis, and fault detection. Granular measurements are being used to help facility managers understand energy usage patterns. Automated analytics, now moving from rule-based systems to machine learning-based systems based on historical data, promises to proactively optimize building system performance and provide real-time insights beyond traditional reactive alarm-based approaches. These advanced systems are able to interpret system behavior in relation to detailed operational sequences. Future iterations will aim to identify problems, as well as automatically change and optimize equipment operations, rather than relying solely on human facility managers. Historically provided by third parties, these systems are increasingly being integrated by vendors into building management systems.

By leveraging AI’s predictive capabilities and sustainable practices, architects and general contractors can realize tangible environmental and financial benefits while shaping a greener, more efficient built environment for generations to come. AI is already proving to be a game-changer for the construction industry and its sustainable design and construction processes. The built world should anticipate that AI will play a key role in increasing sustainability and streamlining and delivering cost-effective solutions throughout the design and construction process.