Adapting real-time visual insights to offshore conditions

Connectivity is a challenge for the offshore industry. Although ships offer many ways to communicate with the mainland, like 4G, 5G or satellite, they must cope with temporarily offline scenarios. Therefore, insights from collected diagnostics are primarily used on the ship itself, on its local network. This is fine for the operators and engineers onboard but problematic for the developers on the mainland who need raw data and real-time insights – they traditionally had to settle for cumbersome and slow solutions like USB sticks or e-mail. Alten has implemented an IoT solution for Seaqualize to overcome the limitations of temporarily offline scenarios, offering real-time insights where possible.

Utrecht-based Seaqualize develops inline balanced heave compensators as an intelligent extension for regular cranes. These so-called heave chiefs keep the load balanced by compensating for the movement of ships caused by waves. This makes it possible, for instance, to mount windmill parts in the North Sea in rough weather conditions. The heave chiefs keep the balance up to 1,100 metric tons, with waves up to three meters and at a speed of half a meter per second, for over fifteen hours. To get a feel for how much weight this is, it’s like lifting almost seven Boeing 747 airplanes.

Edge computing

Seaqualize wants to measure how all moving parts of a heave chief operate, within the limits of construction and safety. Diagnostics are most valuable when insights are visualized in real-time with a historical database as backup. But how to do this for offshore locations where connectivity is often poor? A solution for sending heave chief diagnostic telemetry to the cloud was needed.

Alten was challenged to provide such a solution. Not only should the communication be controllable and reliable, but real-time dashboarding should also be available both on the ship and in the cloud. Furthermore, everything should be manageable remotely. When no internet connection is available, the solution must still collect diagnostic data and provide insights locally until the connection with the cloud is restored. Once restored, real-time data should be sent to the cloud again, including any previously collected data.

An edge solution is the logical choice for the heave chiefs. Diagnostic data must be collected from the internal logic and optimized in various ways. The telemetry should be stored (temporarily) on disk before being sent to the cloud. This has edge technology written all over it. Alten has already implemented edge devices for different clients in various environments like factories, plants and vehicles.

Edge computing typically runs local logic on an industrial PC (IPC), on the ‘edge’ of the local network with a secure connection to the cloud. It works in conjunction with the cloud but operates independently, which is ideal when no communication with the cloud is available. Edge makes it possible to both ingest and transform telemetry on the local network, so data is sent to the cloud in the most optimal way. Cloud-to-device communication is offered for remote control of edge devices.

Lego bricks

For the heave chiefs, Alten has chosen the Advantech Uno 148 edge IPC. This model fits well with current and future requirements and it has proven to be very reliable in previous projects. Also building on our earlier experience, we’ve installed Azure IoT Edge, using the Microsoft Azure cloud to manage it remotely.

Azure IoT Edge offers reusable custom containerized applications called modules. These make it possible to build, configure and connect local logic like Lego bricks. Microsoft also supports running off-the-shelf containers such as open-source databases and visualization tooling. By integrating these with custom logic, local dashboarding is available at almost no extra expense. From the cloud, all modules can be deployed to the edge IPCs. Edge functionality can be monitored remotely and a reliable data transfer is offered for all heave chiefs. Finally, Azure IoT Edge offers the desired offline scenario out-of-the-box by automatically persisting unsent data.

Real-time telemetry is available directly in Grafana dashboards running on the edge. Telemetry at a slower pace is sent to the Azure IoT Hub cloud gateway and represented in the cloud in Managed Grafana dashboards. For long-term historical insights, fine-grained diagnostic data is sent to the cloud via a different channel, as compressed files using Azure Blob Storage both on the edge and in the cloud. These files are ingested in the Azure Data Explorer time-series database where all the historical data can be queried for trends and anomalies. Here, too, dashboards can be used to provide insights to the engineers.

Security is of course very important. In the Seaqualize project, we’ve given each edge device its own credentials, set up communication outbound-only and encrypted communication channels. Furthermore, as the edge controls the cloud connection, other devices on the same local network can’t connect to the cloud directly.

Flexible solution

We tested the edge solution both in Rotterdam and in offshore conditions near France. These tests were all successful. Next, active devices were shipped to Canada and the US, with no connection available during transport. Upon reconnection, we experienced the real-time data coming in at a very low speed in the cloud dashboard. This was unexpected because we had decent connectivity and were able to connect with the devices for remote management. On the heave chief itself, everything was working fine; the local dashboard was performing as expected. So, why was the cloud dashboard not performing?

We realized that, during the weeks of transport, the heave chief had collected a lot of historical data of little to no interest. This massive amount of irrelevant data was now being offloaded alongside the latest real-time diagnostics, clogging up the bandwidth and making it difficult for real-time communication to come through. As we still had decent cloud-to-device communication, we adjusted the parameters of the file upload mechanism. There are several parameters to be set for the blob storage upload, making it possible to pause the upload and change the retention time. Without reprogramming the edge functionality, we could skip the uninteresting data and restore real-time communication. It took us only a few hours to fix this configuration issue, just by consulting the edge metrics and changing edge module parameters – a good example of how real-time visual insights make adjusting the system faster and easier.

Seaqualize now has a flexible, configurable solution offering visual insights on the edge and in the cloud with deep diagnostic query capabilities while allowing full control over data traffic. Logic running on the edge devices is deployable, configurable and maintainable from the cloud, with full support for challenging offline scenarios. The edge solution implemented here is applicable in many other use cases, anywhere in the world.