The article written by Matthew Bester explores Leica Geosystems’ use of smart digital reality in construction through autonomous reality capture systems and AI integration.

With over 12 years of global experience in the Reality Capture industry, Matthew Bester specialises in SLAM-based reality capture. His expertise extends to the innovative deployment of autonomous robotic systems, contributing to advancements in secure reality capture processes and facilitating swift decision-making. 

Unlocking the power of smart digital reality in construction 

In the fast-evolving landscape of construction, where data reigns supreme, companies are reshaping the industry through the integration of smart digital reality. Their approach leverages data generated in the physical world by cutting-edge autonomous reality capture systems, including handheld devices, drones, and robotic deployments.

This strategy not only harnesses the power of 3D technology but also integrates artificial intelligence (AI) into the data processing and analysis, accelerating decision-making processes and delivering tangible benefits in terms of cost savings, time efficiency, and increased safety. 

The intersection of smart digital reality and autonomous systems 

Leica Geosystems’ utilisation of autonomous reality capture systems marks a pivotal shift in how we perceive and utilise data in construction workflows. These advanced systems, whether handheld, airborne, or robotically deployed, use highly specialised robotic algorithms to capture the intricacies of the physical world in meticulous detail. The integration of AI into the subsequent data processing and analysis phases propels this approach beyond mere data collection, transforming it into a dynamic decision-making tool. 

Accelerating decision-making with AI integration 

By infusing AI into the heart of data processing and analysis there is assurance that the wealth of information captured by autonomous systems, is not just stored, but actively contributes to informed decision-making. This integration allows for the rapid extraction of insights and conclusions from complex datasets. This could be classification of point cloud data to extract features or assets autonomously, or the assistance in texturing of meshes. The implications are profound – decisions that traditionally took days or weeks can now be made swiftly, saving valuable time and resources while simultaneously enhancing safety protocols. 

Considerations for adopting autonomous solutions: The autonomous readiness model 

For companies contemplating the adoption of autonomous solutions in their construction workflow, the Autonomous Readiness Model provides a comprehensive framework. This model encompasses five key pillars: People, Process, Technology, Sustainability, and Finance. 

  1. People: Central to the success of any technological transformation are the people who wield these innovations. There must be emphasis on the importance of developing digital skills among employees, ensuring they can effectively navigate and leverage the capabilities of autonomous systems and 3D data. 
  2. Process: The integration of autonomous solutions necessitates a re-evaluation of existing processes. From the digitization of workflows to work process enhancement through AI, companies need to align their processes with the capabilities of these advanced technologies and the data-flow and information flow that comes along with generating mass amounts of data. 
  3. Technology: Understanding and embracing the technology landscape is critical. This includes considerations of the data lifecycle, digital maturity, and the adoption of new ways of working. Hexagon’s smart digital reality exemplifies the pinnacle of such technological integration and decision making at the nexus of digital and physical realities.  
  4. Sustainability: As the world places increased emphasis on sustainable practices, the Autonomous Readiness Model prompts companies to align their adoption of autonomous solutions with environmental, social, and governance (ESG) considerations in both economic sustainability and environmental sustainability.  
  5. Finance: The financial aspect is, understandably, a crucial factor. The model advises on the acquisition costs, maintenance considerations, and the overall infrastructure costs associated with integrating autonomous solutions into the construction workflow. 

Towards autonomous readiness and the future of construction 

Some facts; 

70% of digital transformation efforts fail – Gartner.

84% of construction firms are using autonomous technology in operations, only 16.5% use fully autonomous robot – Hexagon.

60% of leaders in construction believe autonomy will have a significant impact on: market competitiveness; profitability; sustainability and owner satisfaction – Hexagon.

98% of global executives agree AI foundation models will play an important role in their organizations’ strategies in the next 3 to 5 years – Accenture.

As the construction industry progresses towards a future defined by autonomy, the Autonomous Readiness Model brings structured consideration – a metric that gauges an organisation’s preparedness for this digital transformation journey. 

The use of AI in this context becomes not just a technological addendum but a critical ally. AI facilitates quick data analysis and processing, unravelling intricate patterns and insights from vast datasets that would be insurmountable for traditional approaches. 

The benefits for the construction industry are far-reaching. From improved project efficiency to enhanced safety measures, the adoption of autonomous solutions represents a paradigm shift. It’s not merely a technological upgrade; it’s a strategic move towards a future where construction is not just about building structures but about building them smarter, faster, and safer. 

The marriage of smart digital reality and autonomous systems is not just a technological evolution; it’s a revolution that promises to reshape the landscape of construction as we know it.