Industrial Mobile AR Application Development

Industrial Mobile AR Application Development

At an oil refinery, a technician replaces a valve. Every hour of downtime costs the enterprise millions of rubles. Documentation is a 400-page PDF, schematics in AutoCAD on a server, instructions in a folder. Searching for the right information takes up to 4 hours. An AR app on a tablet shows an arrow to the correct valve, displays bolt torque, and step-by-step instructions overlaid on the real equipment. Replacement time drops by 60%.

Such solutions run on Vuforia, Scope AR, Augmentir. We build similar systems, adapting them to corporate ERP and the specifics of a given production facility. Contact us for a preliminary assessment—we'll evaluate your project.

How to Recognize Industrial Equipment Without Markers?

Standard image tracking on a flat picture doesn't work in a workshop: equipment is three-dimensional, metal surfaces glare, lighting is unstable, and smoke may be present. Let's compare three approaches:

Marker-based — we use ARImageTrackingConfiguration (ARKit) or AugmentedImageDatabase (ARCore). Reliable, independent of the object's appearance. Downside: markers must be physically placed and may get dirty.

Markerless object recognition — ARKit provides ARObjectScanningConfiguration for scanning 3D objects into .arobject format. Works for compact equipment with texture. For large objects, we train a model via Create ML or use Vuforia Model Targets SDK.

Spatial anchors — position the scene once and save the anchor to the cloud. On restart or device change, the position is restored. Suitable for large objects: turbines, tanks, machine tools.

Why is AR Useless Without ERP Integration?

Industrial AR without connection to production systems is an expensive toy. The real value is in contextual data:

• Scanning equipment pulls up the current maintenance order, repair history, and required spare parts.
• Overlays of real sensor readings (temperature, pressure, vibration) on physical equipment via OPC-UA or MQTT.
• Digital equipment passport: users see an AR layer with ERP data directly over the machine.

Integrations via REST or GraphQL, authentication via corporate SSO (SAML 2.0, Azure AD). Offline mode is critical: a production shop may not have stable Wi-Fi; all instructions are cached locally using Core Data or Room.

What Technologies Do We Use?

What's Included in a Pilot Project?

1. Equipment and process audit — select 10–20 units for the first AR instructions.
2. Choose recognition method — based on audit results: markers, object tracking, or spatial anchors.
3. Develop a prototype — for one equipment type, linked to real data.
4. Integrate with ERP/SCADA — pull current orders and sensor readings.
5. Create an authoring tool — so technicians can create new instructions without programmers.
6. Pilot deployment — test in one workshop for 2 weeks.

Result: a working prototype, API documentation, and training for two employees. Timeline: 8–12 weeks. Cost is calculated individually — call or email us, we'll evaluate your project within a day.

Steps for Implementing an AR Solution on the Production Floor

1. Pre-project survey (3–5 days) — engineer visit to site, photography, condition analysis.
2. Stack selection: AWS + ARCore/ARKit + ERP adapter.
3. MVP development (4–6 weeks) — basic AR instruction for one assembly.
4. Testing on real equipment with technician participation.
5. Refinement and scaling to remaining units.
6. Commissioning and staff training.
7. Support (12-month warranty on architectural solutions).

Why Choose Us

• Over 10 years of experience in developing AR for industry.
• Delivered 40+ projects for machine-building, oil & gas, and energy enterprises.
• Proprietary authoring tool platform — cuts time to create new instructions by half.
• Warranty on all architectural solutions — 12 months.
• Work with any ERP (SAP, 1C, Oracle) and SCADA.

Order a pilot project — get a working prototype in 8–12 weeks. Contact us by phone or through the form on our website. Get a consultation for your project — we'll assess complexity and propose the optimal solution.

ARKit from Apple — official documentation.

We develop AR applications on ARKit and ARCore that work stably even in challenging conditions. Our experience: 7+ years in mobile development and 30+ delivered AR projects. Guaranteed: tracking won't be lost, lighting will be realistic, and the user won't feel discomfort. Certified Apple and Google developers.

Why does tracking get lost and how to fix it?

ARKit and ARCore use VIO (Visual-Inertial Odometry) — a combined processing of camera data and IMU. Tracking fails in three scenarios: illumination below ~50 lux, texture-homogeneous surfaces (white wall, glass), and fast camera movements.

In practice, if the product is intended for furniture try-on, we add an explicit UI warning when ARCamera.TrackingState.limited(.insufficientFeatures). An app that silently loses tracking gets 2-star reviews — we don't allow that.

Plane detection is configured via ARWorldTrackingConfiguration.planeDetection = [.horizontal, .vertical]. Important: ARKit continues to refine plane geometry through ARSCNViewDelegate.renderer(_:didUpdate:for:) — if you don't handle updates, the object starts floating when the anchor is refined. Our team solves this at the architecture stage, not during testing.

AR Foundation: cross-platform with nuances

Unity AR Foundation is an abstraction layer over ARKit and ARCore. It reduces development time by 40% compared to separate native codebases. But some features (e.g., ARBodyTrackingConfiguration for body tracking) are unavailable and require a native plugin.

For React Native and Flutter, direct AR Foundation is missing. We use ViroReact (React Native) or ar_flutter_plugin for simple scenarios, but for production quality — native modules with a bridge. Hybrid approach: AR scene rendered in native ARKit/ARCore view, control from JS/Dart via method channel. Included in our standard delivery.

Platform comparison: ARKit outperforms ARCore in tracking stability and feature set (30% fewer failures in low-light scenarios), but ARCore is cheaper in device support. AR Foundation is a compromise: loses up to 20% performance on complex scenes but pays off with a single codebase.

Try-on: product fitting via AR

Fitting glasses, jewelry, cosmetics — a separate class of tasks. Here, face tracking is needed, not plane detection.

ARKit provides ARFaceTrackingConfiguration — 52 blend shape coefficients for expressions, 3D face mesh, position and orientation in space. Works only on devices with TrueDepth camera (iPhone with Face ID).

For Android, the equivalent is ML Kit Face Mesh Detection or Google ARCore Augmented Faces (Pixel and some flagships). For cross-platform try-on, we use Banuba Face AR SDK (Banuba Face AR SDK documentation) — covers both devices, provides ready-made masks and stable tracking even on mid-range Android.

Try-on quality critically depends on 3D product models. Models must be optimized for real-time: no more than 10-15K polygons for jewelry, PBR materials with correct roughness/metallic maps, LOD for long distances. Within our engagement, we provide ready-made optimization guides.

How to achieve realistic lighting in AR?

ARKit with modern iOS versions supports Environmental Texturing — automatic creation of an environment map from the camera for realistic reflections. Enabled via ARWorldTrackingConfiguration.environmentTexturing = .automatic. Without it, metallic and glass materials look plastic.

ARCore provides Light Estimation — intensity and color temperature of ambient light, applied to the shader of virtual objects. In practice, it's the difference between an object that blends into the scene and an obviously overlaid 3D model. We guarantee that the final image doesn't betray virtuality.

What's included

• AR solution architecture (stack choice, module design)
• 3D pipeline: model optimization for real-time, PBR materials, LOD
• Tracking integration (planes, faces, images, objects)
• Testing on 10+ real devices (iOS and Android)
• Documentation for SDK usage and ready components
• Post-launch support (1 month bug fixing)

Timeline and estimation

Simple AR scene with placing one 3D model on a plane — 1-2 weeks. Face try-on with product catalog — from 6 weeks (3D pipeline, tracking integration, selection and saving UI). Full AR shopping with cloud anchors and multiplayer — from 3 months. We'll estimate your project in 1 day — contact us to discuss your AR idea.