Capturing more of the world does not automatically produce better decisions. This block looks at how AI is turning reality capture from a collection exercise into an intelligence workflow. The first session covers GeoAI applied to lidar and imagery for automated feature extraction, change detection, and risk identification, with a candid look at where the line sits between AI driven and deterministic methods inside established human owned processes. The second looks ahead to Physical AI, autonomous drone systems as a persistent capture layer, and edge computing that lets sites interpret and respond to changing conditions in near real time.
10:30 AM – 11:00 AM
From Sensor to Decision: How GeoAI is Transforming the Value of Reality Capture
Presented by Aaron Morris, Woolpert, and Rebecca Swabey, Equator Studios
Reality capture technologies have dramatically improved our ability to observe the world, but collecting more data does not automatically create better decisions. As organizations face increasing data volumes, workforce constraints, and growing demands for timely insight, the challenge resides in turning information into action.
This presentation explores how GeoAI is transforming reality capture from a data collection exercise into an intelligence-generation workflow. By combining advanced sensing technologies, including lidar and imagery, with AI-driven analysis, organizations can automate feature extraction, detect change, identify risks, and deliver decision-ready insights at unprecedented scale.
At the same time, turning that information into action is not automatic. This presentation digs into a real tension organizations face once the data exists: how useful that output is once it reaches an established, human owned process. Usefulness isn’t just a function of the data or the model, it also depends on where the line sits between AI driven and deterministic methods, and how well an organization can move between the two.
11:00 AM – 11:30 AM
From Point Clouds to Predictive Intelligence: The Future of Reality Capture
Presented by Paul Doherty, The Digit Group, Inc.
Reality capture has become essential to how we document and understand the built environment. For years, practitioners have relied on laser scanning, photogrammetry, lidar, and drone-based workflows to create highly accurate digital representations of physical assets and construction environments. Yet many current workflows remain episodic: capture occurs at a specific point in time, data is processed, and decisions are made after the fact.
The industry is now entering a new phase where reality capture is evolving from static documentation to continuous intelligence through the emergence of Physical AI.
This session examines how intelligence is becoming embedded directly into reality capture workflows through the convergence of autonomous systems, AI-enabled sensing, edge computing, digital twins, and advanced processing platforms. Rather than simply collecting data, next-generation capture ecosystems can interpret, analyze, and respond to changing conditions in near real time.
A primary focus will be the rise of the Internet of Drones (IoD) as a persistent capture layer within the built environment. Autonomous drone systems, connected sensors, and intelligent edge devices are enabling continuous site awareness by automating data acquisition, increasing capture frequency, and delivering contextual information directly into project platforms and digital twins.
Attendees will learn how emerging Physical AI architectures can transform large geospatial datasets into actionable operational intelligence through simulation environments, AI model training, and scalable processing workflows. The session will present practical applications and implementation examples demonstrating how these technologies are already being applied across construction, infrastructure, facilities, and asset management environments.
Participants will gain an understanding of how reality capture professionals can evolve their role beyond data acquisition and become providers of operational intelligence that supports better decision-making, reduced project risk, improved safety, and measurable performance outcomes.
