AVIN is a configurable subsea platform that is two things at once: an edge AI / ML node and an advanced multi-sensor data logger. Through a managed PoE switch it connects up to eight Gigabit Ethernet devices — cameras, sonars, hydrophones and other sensors — synchronises them with IEEE 1588 PTP timing, and records their time-aligned streams to an internal NVMe SSD of up to 10 TB. The same platform runs computer vision, acoustic analysis and machine-learning models in real time, so it can store everything, or process at the edge and keep only what matters. Power is flexible: run it from an internal rechargeable battery (300 Wh or 1 kWh), as a compute-only node from external power, or paired with an ANIK pack for long-duration endurance. Everything sits in a pressure-rated Aluminium or Titanium enclosure, depth-rated to 6000 m, running an open Linux / Ubuntu stack for your own software.
- Edge AI / ML computingRuns computer vision, acoustic analysis, and machine-learning models locally for real-time decisions, with no dependence on cloud or surface processing.
- Advanced multi-sensor data loggerRecords time-synchronised acoustic, video, and sensor streams to internal NVMe SSD (up to 10 TB) — log everything, or process at the edge and keep only mission-relevant data.
- Managed PoE sensor hubA managed switch connects up to 8 Gigabit Ethernet / PoE devices — cameras, sonars, hydrophones — with per-port power control and VLAN / network management.
- Works with any sensor — not just PoEEach MCBH port is configurable: carry Ethernet / PoE, or dedicated DC power plus PPS / SYNC timing and auxiliary I/O instead — so sensors without PoE or PTP still power up and stay synchronised.
- Precision timing (IEEE 1588 PTP)Hardware PTP for time-aligned acquisition, plus configurable PPS / SYNC output to sub-nodes and external sensors; optional GNSS for a surface or subsea time reference.
- Flexible power architectureRun from an internal rechargeable battery (300 Wh / 1 kWh), as a compute-only node on external power, or paired with an ANIK subsea battery pack for extended endurance.
- Remote power managementSoftware-controlled power that can enable or disable individual sensor ports to cut consumption during autonomous deployments.
- Low-power / duty-cycled operationConfigurable duty cycling lets the computer and sensors sleep between acquisitions and wake on the mission schedule for long deployments.
- Service & recovery connectorA dedicated subsea service port provides force recovery, USB device / recovery, system power control, and serial debug — maintenance without opening the enclosure.
- Open Ubuntu softwareLinux / Ubuntu with Docker, ROS, Python, C++, TensorFlow, PyTorch, ONNX Runtime and OpenCV — deploy your own GPU-accelerated AI models, with optional RemoteCon integration support.
- Subsea-rated platformCompute, PoE networking, recording, timing and power in a pressure-rated Aluminium or Titanium enclosure, depth-rated to 6000 m.
Model range
| AVIN100 | AVIN500 | AVIN1800 | |
|---|---|---|---|
| Internal battery | — | 300 Wh | 1 kWh |
| System memory | 4–64 GB | 4–64 GB | 4–64 GB |
| SSD (NVMe) | 0 / 2 / 10 TB | 0 / 2 / 10 TB | 0 / 2 / 10 TB |
| Ports (configurable) | 2 / 4 / 8 GbE | 2 / 4 / 8 GbE | 2 / 4 / 8 GbE |
| Port modes | PoE / DC / PPS·SYNC | PoE / DC / PPS·SYNC | PoE / DC / PPS·SYNC |
| Timing | IEEE 1588 PTP | IEEE 1588 PTP | IEEE 1588 PTP |
| External battery | ANIK (opt.) | ANIK (opt.) | ANIK (opt.) |
| Operating system | Linux Ubuntu | Linux Ubuntu | Linux Ubuntu |
| Housing | Aluminium / Titanium | Aluminium / Titanium | Aluminium / Titanium |
| Depth options | 300–6000 m | 300–6000 m | 300–6000 m |
- Type
- Subsea edge AI computer & multi-sensor data logger
- Models
- AVIN100 / AVIN500 / AVIN1800
- System memory
- 4–64 GB
- Storage
- NVMe SSD, up to 10 TB
- Internal battery
- 300 Wh (AVIN500) / 1 kWh (AVIN1800)
- External battery
- ANIK subsea packs (optional)
- Networking
- 2 / 4 / 8 Gigabit ports — PoE (802.3af/at), or DC + PPS/SYNC per port
- Timing
- IEEE 1588 PTP; PPS / SYNC output; optional GNSS
- Power management
- Software-controlled, per-port
- Operating system
- Linux (Ubuntu)
- Housing
- Aluminium / Titanium
- Depth rating
- 300 / 1000 / 2000 / 6000 m
Specifications subject to change without notice.
System architecture
Interfaces & functional diagram
FAQ
Subsea edge AI & data logger FAQs
Is AVIN an AI computer or a data logger?
Both. AVIN runs AI / ML at the edge and also works as an advanced multi-sensor data logger, recording time-synchronised acoustic, video and sensor streams to internal NVMe storage — you can log everything, process at the edge, or both.
How much data can AVIN record?
Up to 10 TB on internal NVMe SSD, with hardware-timestamped, time-aligned recording of multiple video, acoustic and sensor streams for real-time processing or post-mission analysis.
Which sensors can AVIN connect and synchronise?
Up to eight Gigabit Ethernet / PoE devices — cameras, sonars, hydrophones and other Ethernet or serial sensors — through a managed PoE switch, with IEEE 1588 PTP timing and configurable PPS / SYNC to sub-nodes.
My sensor doesn't support PoE or PTP — can AVIN still power and synchronise it?
Yes. AVIN's MCBH ports are configurable per port: a port can deliver dedicated DC power instead of PoE, and AVIN can output PPS / SYNC timing to a sensor that does not speak IEEE 1588 PTP. So a sensor without PoE or PTP still gets the power it needs and stays time-aligned with the rest of the array.
How is AVIN powered?
From an internal rechargeable battery (300 Wh on AVIN500, 1 kWh on AVIN1800), as a compute-only node on external power, or paired with an ANIK subsea battery pack for long-duration endurance. Internal batteries charge over PoE or with our chargers.
Can AVIN run autonomously for long deployments?
Yes. Remote per-port power management and configurable duty-cycled operation let the computer and sensors sleep between acquisitions and wake on schedule, with automatic startup and watchdog recovery.
What software does AVIN run?
An open Linux / Ubuntu stack with Docker, ROS, Python, C++, TensorFlow, PyTorch, ONNX Runtime and OpenCV, so you can deploy your own GPU-accelerated AI / ML models; RemoteCon can also provide integration support.
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