Construction Scan 01
A LiDAR point-cloud sample for reviewing field geometry and spatial detail from a browser.
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Spatial Computing Case Study
WebGIS 3D Construction Site Scanning Platform
An iOS LiDAR, photogrammetry, GIS, and cloud platform for capturing construction sites and producing measurable 3D and geospatial outputs.
Construction and Civil EngineeringiOS, Cloud Backend and Web Dashboard
Project Overview
From operational challenge to working product
WebGIS turns a LiDAR-equipped iPhone into an integrated construction-site capture tool. Field engineers can collect point clouds, geotagged photographs, and GPS coordinates in one scanning session.
Captured assets are uploaded to a Python and Django backend, processed through photogrammetry pipelines, and delivered through a web dashboard as point clouds, USDZ and GLB models, GeoTIFF overlays, and measurement tools.
Business Challenge
The problems the product needed to solve
Replace slow, expensive, and fragmented site-documentation workflows with a mobile-first process.
Capture LiDAR point clouds and geotagged images simultaneously without frame drops, misalignment, or data loss.
Upload large scan packages reliably from construction sites with unstable connectivity.
Produce 3D, point-cloud, measurement, and GIS outputs through one connected platform.
Interactive 3D Scan Demo
Explore WebGIS point-cloud scans in the browser
Rotate, zoom, and inspect three sample PLY scans captured for the WebGIS workflow. The demo shows how field data can move from mobile LiDAR capture into a browser-based review experience.
Construction Scan 02
A second site-capture sample that demonstrates interactive navigation across dense scan data.
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Construction Scan 03
A larger point-cloud sample for inspecting how mobile capture supports site documentation.
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Our Solution
A connected system designed for the workflow
The iOS application uses ARKit and Core Location for LiDAR depth, spatial tracking, and GPS metadata, while RealityKit and Metal maintain a responsive real-time point-cloud preview.
A Django REST Framework backend manages uploads and asynchronous AliceVision processing. The admin dashboard lets project teams review scans, measure distance, area, and volume, inspect 3D models, and export GIS-ready files.
Key Features
Capabilities delivered through the platform
LiDAR point-cloud capture
ARKit captures dense spatial data while the device camera records overlapping site imagery.
Geotagged imagery
Core Location attaches coordinates, altitude, and heading to photographs captured during the scan.
Dual photogrammetry pipeline
AliceVision and Apple photogrammetry workflows produce detailed models in USDZ and GLB formats.
GeoTIFF generation
The backend creates georeferenced raster outputs for use in QGIS, ArcGIS, and related GIS tools.
Point-cloud measurements
Dashboard tools support distance, area, trench-depth, and excavation-volume analysis.
Offline capture and smart sync
Scan data remains on the device and uploads with retry behavior when connectivity becomes available.
Technologies Used
Product and engineering stack
- Swift
- UIKit
- ARKit
- RealityKit
- Metal
- Core Location
- Python
- Django REST Framework
- AliceVision
- USDZ
- GLB
- GeoTIFF
Results & Impact
What the work made possible
One connected field-to-dashboard workflow
Point clouds, images, GPS data, 3D models, GIS files, and measurements are managed through one platform.
Stable simultaneous capture
LiDAR and image capture were engineered to run together without degrading either data stream.
Up to 100 meters per scan
A single mobile session can cover construction features such as trenches and foundations across substantial site distances.
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