The Mobile Vision System (MVS) is a flexible vision platform designed to work across mobile, fixed, and robotic applications.
MVS combines device-based image capture with server-side processing. An operator, or an automated system, captures images from a defined inspection area using a mobile device, fixed camera, or robot-mounted camera. Images are sent to a server where AIS Vision Studio processes them using a combination of deep learning and traditional machine vision tools.
Once analyzed, results are returned to the originating device in near real time. The full capture-to-result cycle typically completes in under one second, supporting fast, in-process decision making on the production floor.
MVS is not limited to mobile use. The same processing architecture supports fixed and robotic camera installations, allowing teams to deploy a consistent vision strategy across multiple formats and environments.
Deep learning
MVS uses machine learning algorithms designed for the variability common in industrial vision applications. The system identifies unique elements within an inspection using images captured from mobile devices, fixed cameras, or both.
Unlike systems limited to a single capture method, MVS supports multiple image sources within the same application. All image processing is performed on premises. No internet connection or cloud services are required, and firewall configurations remain unchanged.
Communication
MVS is a fully localized system that operates without internet connectivity. It can be triggered manually or integrated directly with a PLC.
Prebuilt PLC communication blocks simplify integration and reduce setup time. With signaling and event triggering already in place, connecting MVS into an existing automation environment is straightforward.
Data
The user interface supports configurable metadata fields, along with pass/fail results, date, time, and part identification data. Recipe management, user verification, and reporting are available as services.
MVS stores images and inspection data in an integrated SQL database, enabling efficient search, analysis, and auditing. Batch review and traceability are significantly faster and less labor-intensive than managing individual image files.
Hardware
MVS runs on an industrial PC acting as a central server for deep learning processing. Image acquisition is supported through Android devices, fixed cameras, and robot-mounted cameras.
Licensing is per site. MVS can integrate with existing GigE image devices, allowing teams to reuse current equipment rather than replace it.
Core competencies
Mobile vision inspections
Operates across multiple device types
Adapts to product variation
Uses deep learning–based inspection algorithms
Cost-effective inspection solution
No required floor space footprint
Technical specifications
Interface to standard Industrial Protocols like Profonet or Ethernet IP. Digital I/O, or direct to controller such as Stanley, Bosch or Atlas Copco.
