Supporting Low-Bandwidth Video Streaming for Autonomous Maritime Operations

Videosoft is working with Marine AI to provide low-bandwidth video streaming capabilities designed for autonomous and remotely operated maritime missions. The collaboration began during development of Marine AI’s first autonomous platform, Mayflower, and has progressed through the integration of Videosoft’s ultra-low bandwidth streaming technology into more recent autonomous systems. 

The partnership focuses on supporting reliable video transmission in offshore environments where communications infrastructure presents operational constraints. By combining Marine AI’s autonomy capabilities with Videosoft’s video compression and streaming technologies, the companies are addressing connectivity requirements for remote maritime operations while supporting situational awareness and mission oversight.

Addressing Offshore Communication Constraints

Maritime operations face communication challenges that differ significantly from land-based environments. Offshore deployments frequently rely on bandwidth-limited and high-cost connectivity methods, particularly satellite communications. At the same time, dependable video transmission remains essential for remote supervision, operational decisions, and control of autonomous platforms.

Videosoft’s video compression and data streaming technology is intended to support secure and efficient real-time video delivery under constrained conditions. The system is designed to maintain performance levels while reducing the bandwidth burden associated with transmitting video from remote locations.

Integration with GuardianAI™ ORION

Videosoft’s technology has been integrated with GuardianAI™ Inspect, a component of Marine AI’s GuardianAI™ ORION autonomy control suite.

Through this integration, operators can manage video streams for autonomous and remote activities within a unified command and control environment. The platform architecture also supports deployment across different vessel categories and operational platforms, allowing video management capabilities to be applied across varied maritime use cases.

Supporting Inspection and Computer Vision Applications

The integrated system also contributes to inspection processes and Computer Vision (CV) workflows. Video streams can be processed onboard autonomous vessels, within the Remote Operations Centre (ROC), or during post-mission analysis activities.

This approach supports advanced inspection functions while minimizing data transmission requirements. Maintaining low bandwidth demands is particularly important for autonomous maritime systems operating in regions where communications availability is restricted.

Demonstration at Oceanology International

The collaboration was demonstrated during Oceanology International, where live video feeds from the Oceanus 12 in Plymouth Sound were streamed together with a live drone feed.

Using GuardianAI™ Inspect, operators monitored multiple camera inputs simultaneously through the user interface, providing real-time situational awareness. Demonstrations and operational testing have contributed to improvements in video compression efficiency, stream reliability, and vessel connectivity across a range of communication pathways, including satellite links.

Supporting Situational Awareness in Maritime Autonomy

The combined capabilities developed through the partnership are intended to support several operational objectives, including dependable real-time video transmission over constrained maritime networks, lower satellite communication requirements, improved operational visibility, and scalable deployment across autonomous and remote systems.

The ongoing collaboration between Videosoft and Marine AI reflects continued development efforts focused on enhancing situational awareness and operational visibility for autonomous maritime platforms operating in challenging communication environments.

Read ‘Videosoft Global & Marine AI: Enabling Low-Bandwidth Video Streaming for Maritime Autonomy’ on the Videosoft Global website.