Digitalization and Automation, Low-Hanging Fruit for Construction Industry in the Era of AI

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By Rithika Thomas | 2Q 2024 | IN-7307

Real-world use cases and startup solutions are using Artificial Intelligence (AI) to streamline workflows, improve worker safety, and optimize resource utilization and cost in the construction industry.

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Beyond the AI Hype in the Built Environment

NEWS


The construction industry is harnessing the power of Artificial Intelligence (AI) to automate repetitive tasks, reducing dependency on manual labor and analyze large datasets to streamline decision-making. Environmental, Social, and Governance (ESG) reporting, compliance, and energy management are the fastest growing applications of AI with the potential to reduce the annual carbon footprint of the built world by 50%, according to Proptech reports. Additionally, in the last decade, Venture funding for AI-enabled construction industry startups in Europe and North America totaled US$18.6 billion, half of which was received from applications of AI in the last 2 years.

AI Transforming the Construction Industry Jobs from the Drawing Board to the Landfill

IMPACT


Computer-Aided Design (CAD) and Building Information Modelling (BIM) technologies have revolutionized the digitization process, enabling architects, engineers, and construction professionals to create detailed Three-Dimensional (3D) models to improve efficiency, accuracy, and cost effectiveness. AI is enhancing strategic planning and decision-making to optimize building layouts to maximize daylight, and improve material use, building operation, and ventilation, thus reducing waste and conserving resources. Generative AI algorithms are automating concept-level design iterations with sustainable parameters, optimizing building design for energy efficiency, performing regulatory checks, occupant comfort, structural stability, and cost effectiveness. For example, Dassault Systèmes’ 3D generative innovator using CATIA parametric modeling technology with automation has been supporting designers, architects and engineers, freeing up architects to focus on higher-level design decisions at the design stage. During building operations, AI is facilitating facility managers with predictive maintenance, energy management, and space utilization in facilities by collating information from Internet of Things (IoT) devices to detect equipment failure, predict maintenance, and optimize energy consumption to prioritize work.

Manual data entry, basic drafting, and customer services roles will be replaced with upskilling around operating machinery, data analysis, and managing AI-enabled systems. For example, construction companies are adopting drones, autonomous equipment, sensors, and digital tools to detect potential safety hazards and construction workers using robots for bricklaying, concrete pouring, and 3D printing building components, resulting in increased speed and precision during construction.

Convergence of AI and Built Environment—Startups Identify New Realm of Possibilities

RECOMMENDATIONS


AI has raised concerns about job displacement, data privacy, and ethical implications, so the new trend of AI-based startups are revolutionizing the industry in the following ways:

  • Forecast Viable Real Estate Investment: AI’s ability to process large datasets on historical data, market trends, economic indicators, climate, and social factors generates accurate forecasts for property prices, demand, and investments opportunities to make informed decisions and mitigate risks. Localize’s operating system supports the multi-family and residential real estate industry.
  • Sustainability: During the design stage, AI can optimize building design by optimizing building orientation, material selection, construction techniques, and compliance with specific green building regulations. In addition, AI can streamline the reporting process, optimize energy consumption, generation, tracking, and analyzing, and reduce building-level emissions though smart/IoT devices. Deepki leveraged AI for analyzing real estate portfolios and suggesting decarbonization strategies.
  • Streamline Operations & Predictive Maintenance: Machine Learning (ML) algorithms analyze building-level data to optimize occupant comfort, energy consumption, and equipment operation such as automatically adjusting Heating, Ventilation, and Air Conditioning (HVAC), demand response, and lighting for optimal occupancy patterns, and environmental conditions. AI helps monitor, detect, and trigger responses to equipment inefficiencies, minimize energy, water, and waste, and reduce carbon footprints. Sense tracks home energy demand.
  • Demolition Waste: Sorted,io uses computer vision technologies to improve waste sorting, a traditionally manual and inefficient process that can lead to waste being redirected annually.
  • Boost Safety, Quality, and Productivity: Construction safety is a critical concern in industry, and as buildings become more complex, real-time safety monitoring is using drones, sensors, and cameras to create a safer construction site and worker safety. Kwant supports workforce management, safety, and productivity, while OpenSpace performs reality capture on building sites to track site progress.

The biggest challenge in the construction industry is the lack of building-level data, which is critical to generative AI application, but digitization and automation are achievable short-terms goals for the industry as it evolves.

 

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