AeroFlow - AI Inspection Digital Twin Platform

DDL created AeroTwin as part of an initial collaboration and solution exploration between Arcaina and Nelson Airport – the challenge was simple “How can AI help us with runway monitoring and inspections” – a process that was identified as a prime candidate for a modern re-think. The current process involves drivers in utilities driving the runway and observing damage, subsidence, objects or other risks to aircraft and the environment. Manual foot-based inspections also take place, with physical objects such as pens, being photographed next to areas of damage to comprise the ‘visual evidence’ of changes on the runway or infrastructure surfaces. DDL proposed a theoretical approach to augmenthuman elements that must be retained, with imagery processed via drones that would fly on repeated, automated missions and capture imagery around key/nominated areas requiring specific attention. AeroTwin has been built as the app to centrally; - Plan and manage drone fleets, flights and missions - Act as the processing hub for AI-image processing for crack detection, foreign objects and more which returns processed images into the app - Create monitoring zones and grids to compare images over time - View data and insights on developing damage or issues of concern by location – create and manage jobs to remediate issues - Use agents to query and inderstand patterns in damage, causes of damage, and potential remediation paths - View rich asset detail, such as 3D models, 360 environments, and visual asset layouts and interconnections between key nodes - Stream data into the app from IoT and edge devices to compare contextual information from important areas

- Costly and time-consuming runways inspections due to huge surface area - Disconnected workflow from inspection to remediation - Reporting is undertaken and generated manually - Massive infrastructure maintenance is planned years in advance, so access to timely data to make informed decisions is a competitive and commercial advantage

- Combining our expetise in Vision AI, applicaiton development, geospatial data and 3D/360/Digital Twins, DDL created AeroTwin as a one-of-a-kind hub that combines drone, AI, and infrastructure ops in one place - Selectable AI models process captured images to detect anomolies based on the area being monitored - Data is tracked in an app with additional analytis and agentic insights available on demand - Spatial awareness is provided through integrations with ArcGIS, IoT/Edge devices, 360 panoramas and a visual asset and node monitor

- AeroTwin was developed at no cost to Nelson Airport, and undertaken as a technical challenge to explore the benefits of AI for a large facility such as an airport. No specific outcome was sought, other than exploring possibilities, but it has proven the ability of AI to enhance traditional processes, introducing automation and consistency to critical processes, and providing a previously-unavailable combination of information to support efficient, operational asset management and inspections with 3D and real-time context on demand. - AeroTwin is now in full development as a standalone commercial product