How to Inspect a High Rise Building with Drones? A Case Story
- Hammer Missions
- Jul 31
- 5 min read
Updated: Aug 29
Inspecting high-rise buildings has traditionally been a challenging and time-consuming task, often requiring complex access solutions and extensive manual assessments. However, recent advancements in drone technology combined with AI are transforming how these inspections are conducted, making the process safer, faster, and more accurate.
In this article, we explore a real-world case study from Hammer Missions that demonstrates how drones and AI were effectively used to assess a 10+ storey building, providing valuable insights into the workflow, data capture, analysis, and reporting process.
The Challenge of High-Rise Building Drone Inspections
When faced with a multi-story building, especially one exceeding 10 stories, gaining safe and comprehensive access to all parts of the structure is a significant hurdle. Traditional inspection methods can be costly, risky, and prone to human error. This is where drones come into play, allowing inspectors to capture detailed imagery of the entire building envelope — including roofs and facades — without the need for scaffolding or rope access.
By bringing the building virtually to the desktop, drones enable detailed assessments from anywhere — improving inspection speed, safety, and data quality.
Data Capture Using Drone Flight Planning
Capturing a high-rise building with drones requires precise flight planning to ensure full coverage. In this case study, the drone followed predefined waypoints around the building, capturing thousands of images from multiple angles. Each yellow dot on the flight path marked an exact photo location, documenting the entire facade and roof.
A key factor is the camera angle during capture—top-down shots focus on the roof, while angled shots capture facade details. Vertical overlap between roof and facade images is essential to avoid gaps and ensure a seamless, accurate 3D model.
Flight automation tools like Hammer Missions help operators design efficient paths with optimal overlap. While other software can be used, the priority is ensuring enough overlap for complete, high-quality reconstruction.
Creating and Analysing the 3D Model
Once the drone data is captured, it is uploaded to a processing platform where it is transformed into both 2D maps and detailed 3D models. This process takes just a few hours, delivering a high-resolution digital twin of the building that can be explored in detail on a desktop.
But a visually impressive model alone isn’t enough. Clients and stakeholders want actionable insights: What is the current condition of the building? What defects exist? And what steps are needed to remedy them?
Identifying Big Picture Issues: Water Stains
One of the first observations from the 3D model was water staining on the roof and various parts of the facade, visible as discolouration suggesting possible water ingress or drainage issues. Inspectors can zoom into the model and review original drone images to assess the extent and severity.
Marking these defects is simple. Using the inspection platform, inspectors tag stained areas and link each to its precise location on the model. This spatial context helps distinguish between similar-looking areas and keeps observations organised.
Detecting Smaller but Critical Defects: Spalling
Water penetration often leads to more serious structural issues like spalling — the chipping or flaking of concrete or facade materials caused by corrosion and freeze-thaw cycles. Identifying spalls early is crucial since they tend to worsen over time if left unaddressed.
In the project, spalling was detected on multiple facade sections. While some defects were visible directly on the 3D model, others required inspecting the high-resolution drone images. Inspectors can click on any part of the model to bring up the closest detailed image, allowing for precise identification and assessment of spalls.
Similar to water stains, spalls were tagged and severity ratings assigned to prioritize repairs. This structured approach helps stakeholders understand which areas need immediate attention and which can be monitored over time.
Leveraging AI for Comprehensive Defect Detection
To ensure no defects were missed, AI models were employed to automatically detect and tag water stains and spalls across thousands of images. This AI-assisted approach not only speeds up the inspection process but also enhances accuracy by catching subtle defects that might be overlooked during manual review.
By combining human expertise with AI technology, the inspection team was able to generate a more complete and reliable defect inventory, improving confidence in the assessment results.
Quantifying Defects and Preparing Reports
A vital part of any inspection is quantifying the defects to inform repair planning and budgeting. The Hammer Missions platform allowed the team to count the number of observations for each defect type — water stains, spalling, standing water — and measure their affected areas in square meters or square feet.
All this data was exportable to CSV files or spreadsheets, making it easy for contractors and engineers to use it during repair estimations and project management.
After thorough analysis, a comprehensive report was generated directly from the platform. The report includes:
A summary introduction written by the lead engineer or contractor
Location details of the building inspection
Visual maps and 3D views highlighting all defects
Quantification tables sorted by severity, with high-priority issues listed first
Detailed images of each defect with annotations and comments on recommended actions
This report is exportable as a PDF and can be easily shared with clients, stakeholders, or contractors. Interactive links within the report allow users to jump directly to specific defects in the 3D model, facilitating clear communication and efficient planning.
Enhanced Visualisation with Facade Mode
The platform’s facade mode enables inspectors to isolate and rotate the building’s facade for closer examination of defects like spalling. Zooming in increases image clarity, helping to better understand the condition even without physically being on-site. When available, closer drone photographs supplement the view with higher detail.
Conclusion: Revolutionising Building Assessments with Drones and AI
This case study by Hammer Missions showcases how integrating drones, AI, and advanced software platforms can revolutionise the way we inspect and assess high-rise buildings. From detailed data capture with precise flight planning to AI-assisted defect detection and comprehensive reporting, the entire workflow enhances efficiency, accuracy, and safety.
Clients receive clear, actionable insights into the building’s condition, backed by quantifiable data and interactive 3D models. Contractors benefit from precise defect locations and severity ratings, enabling targeted repairs and better resource allocation. Knowing the exact 3D location of each defect adds a new layer of planning convenience—for example, spalling on the adjacent parking garage can be visualised in relation to nearby trees and structures, helping plan repair access more efficiently.
Hammer Missions’ collaboration with AMF Construction highlights how these cutting-edge tools are already being applied in real projects, setting new industry standards for facade and structural inspections.
About Us
Hammer Missions is a software AI firm helping companies in the built environment leverage drones and AI for assessing existing conditions. Having seen 5000+ projects, we're pleased to be working with leading firms in AEC to streamline and scale the process of facade inspections. If you're looking to learn more about how AI can automate and accelerate your building assessment projects, please get in touch with us below. We look forward to hearing from you.
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