Integrating Edge AI into subsea imaging

This OEM, a specialist in subsea technology and engineering, develops advanced solutions for demanding inspection and monitoring applications. Its imaging capabilities support systems where reliability, image quality and integration flexibility are essential.

For this application, the OEM needed to combine high-performance image capture with Edge AI processing within the constraints of an existing subsea system.

Company Highlights

• Develops engineered products and technology solutions for demanding subsea and industrial applications.
• Provides subsea imaging, surveillance and monitoring capabilities.
• Integrates advanced vision technologies for inspection and operational awareness.
• Supports operations across offshore energy, marine and other specialised markets.

The Challenge

Integrating cameras into subsea systems presents very different constraints from conventional industrial or security applications. Sensitive vision components must operate inside pressure-resistant enclosures, where available space, weight, power consumption and thermal management are tightly controlled. At the same time, the imaging system must perform reliably in extremely low-light underwater environments.

AI-generated image for illustrative purposes.

The application required a lightweight, compact board-level AI camera solution that could combine image capture with Edge AI processing. The system needed to analyse image and video data close to the point of capture while meeting the mechanical and environmental constraints of the existing subsea system.

Compatibility with the existing subsea infrastructure was equally important. The architecture needed to adapt to an established platform, limit development risk and provide a practical route from proof of concept to deployment without requiring a major redesign of the installed equipment.

The Solution: Bringing Imaging and Edge AI Together

Following technical evaluation and close collaboration with Videology engineering, the provider selected the SCAiLX 2 MP colour global-shutter camera together with the SCAiLX Edge AI Platform.

The platform’s system-on-module architecture, built around the NXP i.MX 8M Plus processor, provided the computing capability required for embedded vision and AI processing. Processing data locally at the edge reduced the need to transmit all image data to an external system and supported real-time analysis within the deployed architecture.

The compact mechanical profile of the SCAiLX platform fit the existing subsea design, while the camera’s image sensor provided the low-light sensitivity required for underwater operation.

Key Integration Factors

Several factors were important to the successful integration:

• A compact board-level camera footprint for a space-constrained enclosure.
• Low-light imaging suited to challenging underwater conditions.
• Edge processing for local image and video analysis.
• Mechanical compatibility with the existing subsea platform.
• A scalable architecture for future AI-enabled inspection and monitoring functions.
• Long-term product availability, configuration control and supply continuity.

Engineering Collaboration and Implementation

Videology worked directly with the provider’s engineering team to align the camera and processing platform with the existing subsea architecture. This collaboration helped reduce integration risk and supported the transition from initial evaluation to a deployable embedded vision solution.

The completed integration placed AI-enabled image capture and analysis inside the subsea inspection system. Processing data locally reduced bandwidth demands and enabled faster analysis within the deployed equipment.

AI-generated image for illustrative purposes.

The Outcome

The provider successfully integrated advanced imaging and real-time analytics into its existing subsea architecture without significant platform modification.

The resulting design met the application’s requirements for a compact footprint, low-light imaging and dependable operation. It also established a scalable foundation for future AI-enabled inspection, monitoring and autonomous decision-making capabilities.

Edge AI Solutions for Demanding Embedded Vision Applications

For specialised OEM applications, the camera is only one part of the design. Successful integration also depends on mechanical fit, processing architecture, firmware stability, configuration control and long-term availability.

Videology works directly with engineering teams to adapt imaging solutions to specific application requirements, providing responsive engineering support throughout integration while maintaining product continuity and dependable supply required for long-term programmes.