The secret to successful e-navigation

A glimpse into the future

The year is 2050. Autonomous ships are commonplace in the maritime shipping industry. These self-navigating vessels rely on intelligent maritime e-navigation applications.

To program these systems, fleet managers input various stipulations and goals, such as destination, departure time windows, vessel specifications, cargo type and weight, fuel prices, and emissions requirements.

These inputs are combined with reliable high-resolution weather forecasts that include both detailed current ocean-state data and highly accurate multi-model forecasts, which are dependent on reliable real-time earth observations.

These applications are powered by AI algorithms that process all of this data. They generate navigation plans that regularly auto-correct for disturbances in traffic, weather, or port operations, similar to how early GPS apps, like Waze and Google Maps, would automatically update routes with changes in traffic conditions.

The autonomous ships have fully integrated e-navigation systems that automatically receive and process location data, weather forecasts, and routing plans.

Compared to what was possible in the early part of the century, these applications save massive amounts of time, fuel, and emissions, all while reducing risks and operating costs. Large maritime companies know these technologies are an essential way to gain an edge on competitors. The most competitive companies look for new ways to drive efficiency and continually push the state-of-the-art forward.

Return to the present

It’s clear that advanced maritime e-navigation systems like this are coming, and they will revolutionize the maritime industry.

Let’s take a closer look at some of the technologies that will contribute to advanced e-navigation systems. Understanding some basics about the state of weather routing technology may help give you some ideas on how to improve your products and prepare for the future.

Avoiding extreme weather

One significant value of high-quality weather forecasts is being able to avoid extreme weather conditions, and therefore minimize fuel use, downtime, and risks. On a long voyage, avoiding extreme weather and planning strategically according to weather forecasts might save you days of time, thousands of gallons of fuel, and many staff-hours.

Radio-occultation GPS data, also known as GPS-RO or GNSS-RO, is changing how we make weather predictions. First applied in a weather context in 1995, this technology analyzes how radio waves change as they pass through Earth’s atmosphere. This provides detailed data about the state of the atmosphere, which can be used to make predictions.
As the technology has evolved, it is now possible, using a constellation of smallsats, to cover the planet and get this data in remote regions too.

Aside from forecast predictions, GNSS-R (reflectometry) can also be leveraged for winds over sea/ocean and soil moisture—an application that will continue to improve. And there will likely be many more uses for GPS-RO in the maritime industry.

Machine learning is also enabling the advancement of weather predictions. Neural networks, coupled with ever-growing computing power, have allowed us to analyze and discover patterns in large, historical data sets, a feat that wouldn’t have been possible a few years ago. Machine learning also brings value to other maritime calculations, such as plotting optimal routes and schedules when considering a vast number of factors.

Increasing efficiencies for everyday travel

Avoiding extreme weather is maybe the most obvious use for integrating weather predictions in your applications. But it’s likely that, in the long term, the most significant efficiencies and sources of savings will come from optimizations for voyages in non-extreme weather.

Even on everyday voyages, the combination of waves, currents, and winds can generate a lot of fluid resistance for a vessel. Better weather and ocean-state data, combined with machine learning, will result in e-navigation systems that choose routes of least resistance and also continuously make small adjustments throughout a trip. This might seem like a relatively minor optimization. But when you consider that winds, waves, and currents are often slowing down vessels, it’s easy to imagine how these small changes can add up to significant savings.

Here’s one example of how this could work. A routing system might see that a current several miles away offers less resistance than the vessel’s present path. The system calculates that choosing the lower-resistance path more than makes up for the extra travel time and fuel costs.

These systems will also use more peer-to-peer, localized data. For example, a ship transmits data to nearby vessels about a localized weather event, such as a passing cold front bringing strong broadside winds. Nearby ships can use this data immediately, and it can also be incorporated into a centralized navigation system for future reference to seasonality, satellite imagery, and time of day.

Esri’s Maritime Consultant, Guy Noll, adds that “you can begin to understand this seamless information environment by combining weather and other environmental content in The Living Atlas.”

Improvements in satellite AIS data will also help analyze resistance and determine optimal routes. Applications may take into account the real-time speed and acceleration of all ships in an area to establish more efficient paths.

High data resolution and frequency

An increase in the accuracy of data can help drive stronger maritime e-navigation systems.

More precisely, weather forecasts are informed by:

• An ever-growing satellite constellation
• Making more frequent observations
• From more regions, including rarely covered or unmonitored deep-sea areas
• At higher spatial resolutions

Frequent and high-resolution data is especially important for treacherous routes, where seas can change in minutes or even seconds. For example, the South China Sea is known for dangerous conditions, including large storms, high waves, and heavy shipping traffic. (And who knows what weather and traffic will be like in that area by 2050?) More frequent and detailed data collection will make it possible to compose on-the-fly navigation adjustments.

Not all sources of maritime weather forecasts are of the same accuracy or veracity. Some weather service providers have more advanced algorithms and multi-model numerical weather products. Others are more basic. This is not to denigrate any weather service. After all, not every organization needs the most advanced data or forecasts. But it points to the fact that different businesses require different qualities of data.

Next steps

Groundbreaking advancements in maritime weather routing aren’t science fiction. They’re happening now. If maritime software makers want to survive and thrive, they’ll want to pay attention to how reliable and accurate weather can help build sophisticated navigation engines. They’ll need to look for ways to incorporate new state-of-the-art solutions in their offerings, so they’re not left behind.