BIM, reality capture, augmented reality, real-time digital twins – these are just some of the innovations in architecture, engineering and construction that have revolutionized workflows. The rise of digital technology and tools in AEC are undeniable, but there are still plenty of challenges to be addressed. In this panel, leaders from AEC firms and technologists will discuss what challenges remain for digital workflows, how AI, advanced visualizations and other technologies will impact the AEC industry, and what potential breakthroughs might be on the horizon.
Session moderated by Niknaz Aftahi, aec+tech
Taking Construction from Eye Level to Sky Level: Driving Innovation at Skanska through Drone Technology
Skanska, one of world's leading construction companies, utilizes drone technology to solve complex challenges. The theme is centered around how drone technology can drive improvement and is looking to inspire the next wave of innovators in our industry.
The focus and case study will be centered around Portal North Bridge; Skanska's newest +$1.5-billion-dollar mega-project. Six launch locations and two drones were used to map over two miles of critical infrastructure. The site is nestled between the restricted airspaces of Teterboro Airport and Newark Airport. The mission also required extensive planning and approvals from New Jersey Transit and Amtrak. This planning included developing a 50+ page safety plan. The team also used flight mapping software to meticulously plan the route of the autonomous portion of the flight, ensuring adherence to all owner restrictions specified in the safety plan. The presentation will share lessons learned regarding team coordination and establishing client trust.
The audience will be introduced to the use cases of drone technology in construction. Real world deliverables examples from Portal North Bridge will include:
– Orthomosaics for logistics planning material staging, equipment and machinery tracking, and emergency response planning.
Kara Fragola, Skanska USA Civil
Modeler and AI as a Team for Fast Scan-to-BIM
Modeling a BIM model from a point cloud is time consuming and expensive. We present two use cases of an AI where in one modeling could be completely avoided, and one where modeling time could be reduced by 30% since modeler and AI work together as a team.
We trained an AI, an artificial neural network, to search for objects and features in 3D laser scans of facilities. The AI finds windows, pipes, valves, areas and much more information in a point cloud. As a result, the point cloud can be used as a database, where, e.g., specific objects can be counted and filtered like an Excel sheet, or the point cloud can be seen as a pre-modeled Revit model.
The first use case tackles destruction of a power plant. The AI took about 4 hours to gather building, structural and piping information in the huge scan. For destruction planning information about pipes, pipe fittings and pipe accessories can be gained containing, count, lengths, diameters, position and orientation.
The second use case tackles modeling of wooden columns and beams of a historic castle. In a workflow where modeler uses filtering and objects suggestions of the AI, the modeling process is accelerated and quality control is included in the semi-automatic modeling. We achieved a speed-up of at least 30% and could highly spare the nerves of the modelers.
Stefan Hormann, aurivus GmbH
Lidar On the Go: Transportation and Construction Applications of the Apple Lidar Sensor
Recently, Apple has include a lidar sensor on the IPhone Pro and Ipad systems as part of their expansion into many augmented reality applications. The portability of this sensor has made lidar accessible to a larger user base. The technology is rapidly evolving as new apps and use cases are created and has the potential to transform AEC workflows. This presentation will explore capabilities and limitations of the sensor in context of transportation and construction applications. Findings from a series of rigorous laboratory and field tests will be presented exploring performance in different geometric conditions, lighting conditions, and other acquisition strategies. In particular, potential use cases in transportation and construction will be explored such as quantity computation, as-built documentation, QA/QC, virtual annotation, visualization, augmented reality and more. Lastly, best practices for effective utilization of the sensor will be discussed.
Ezra Che, EZDataMD
Solving the Drafting Dilemma: How ENR's #1 Design Firm Is Revolutionizing As-Built Workflow with AI
In the AEC world, as-built site conditions have historically been documented through tedious manual surveying and drafting methods. The revised or red-lined hard copies usually end up in a dusty archive room – and are likely obsolete within a few months. Now, a quick scan with a UAV/UAS, mobile unit, or manned aircraft can provide the photogrammetric or lidar data needed to create a digitally accessible georeferenced site database that can be easily updated with future improvements.
When Jacobs was looking to create a state-of-the-art geospatial database of The Villages, a dynamic, 22,000-acre master-planned retirement community in central Florida, they knew remote sensing technology was the way to go. However, although they were efficiently collecting site data via manned aircraft, the team was still running into a major bottleneck: they were waiting weeks or months for a drafting team to manually identify and trace the dense, urban site features.
ENR's #1 design firm decided to turn to AI and machine learning to quickly transform their remote sensing data into a usable GIS database. Jacobs partnered with AirWorks to autonomously create linework for 3,000 acres of the development, including all roadways and 6,800 residences and driveways. By taking advantage of this emerging AI technology, Jacobs enjoyed prompt processing (less than two weeks), enhanced productivity, and fresh perspectives on site data.
Adam Kersnowski, AirWorks and Kris Anderson, Jacobs
