Key Trends in Maritime Data Analytics: Predictive Models, Data Fusion, and Green Shipping
Last week, I had the pleasure of attending Shipping 2030 Europe event in Copenhagen. Two subjects really stood out for me at this event: Green Shipping and Maritime Data Analytics. I was fortunate enough to participate in a panel discussing the latter.
Fresh with new ideas and enthusiasm for the industry, I thought I would continue the momentum by sharing my observations of the nascent maritime digital transformation and maritime data analytics.
Data analytics and maritime intelligence
The subject of the panel was “Data analytics and prediction – discussing the role of data mining and tools to analyze and apply the right use of information flow to working practices”. I was pleased that Spire Maritime was involved in this conversation as we are confident in our strategy to push forward with predictive analytics and believe its role is crucial for the digitalization of the maritime industry.
Better than real-time
The benefits of predictive models span improved decision making, optimized route planning and increased energy efficiency. We are developing the Spire Sense Cloud API to be at the center of this evolution. Fusing AIS data with curated datasets and designing machine learning algorithms to deliver next-generation maritime intelligence.
4 Key Takeaways
Know the problem you want to solve
This may seem obvious, but is still worth mentioning because finding answers with data fast and efficiently requires knowing your desired outcome. What information and process you do you want to prioritize needs to determined. Some examples of issues being solved with data include: supply chain optimization, security, trade or performance improvement.
If we want to build a digital maritime intelligence product we must look beyond AIS data. Fusing different data sources together. Then employ machine learning algorithms to adapt the delivery depending on the use case.
Enabling actionable data
At Spire Maritime we recommend using APIs for data delivery because this enables simple application integration and a more efficient workflow. APIs allow you to skip the tedious step of processing and refining your data lake and easily add additional curated data for a full maritime picture.
Prevent a data swamp
This last point ties to the previous one, data dumps. In particular, AIS data can be susceptible to becoming a data swamp due to its cluttered and arguably inaccurate nature. Machine learning algorithms, like those in the Spire Sense Cloud API, are built to improve the quality and therefore the value of data over time. Another argument in favor of AIS data APIs.
Maritime Digital Transformation Trends
Beyond the valuable insights learned from our panel, the exchanges with my peers gave me a deeper understanding of the important conversations and changes currently taking place in the industry. Here are my observations:
1. Green Shipping Technology is a hot topic!
Indeed half of the event’s program was dedicated to this subject discussing topics like tackling ocean plastic, renewable energy and reducing emissions in the shipping sector. Notably the regulations being implemented: EU MRV (Monitoring Reporting Verification) regulation in combination with IMO DCS (Data Collection Systems).
2. Surge in data streams
Everybody is talking about the importance of data to drive innovation and there is an uptick of data streams. Three approaches of collecting and processing data from vessels stood out:
- Having boxes on a ship to collect data (i.e. IoT) and backhaul that via communication satellites and or terrestrial communications.
- Digital twins; making a twin of the vessel and simulate all performance indications (fuel performance, friction, etc.).
- Combining and aggregating other data sources, like AIS, weather, cargo data, etc.
3. Everyone wants data in different ways
All areas of the industry want data, however there are already evident differences in requirements between shipowners, charters and ship operators. Even though they all want data, everyone has their own use cases. As innovation increases, I suspect use cases will become even more specific.
4. Incumbents are grouping to compete with global giants
We are seeing a trend in consolidation amongst shipowners. Partly to compete with global giants and outsiders like Amazon or Alibaba that are entering and influencing the maritime transport industry.
5. Interoperability of data
This is key to digitalizing the industry and further application integrations. Currently, there is a lack of interoperability between players.
6. E-navigation and route planning is a popular topic
The development of e-navigation and route planning is a popular topic because it will influence many aspects of the industry including autonomous shipping and emission efficiency. I look forward to following these three key innovators in the field: Napa and GNS Solutions. We also believe that Spire Stratos Cloud, Spire’s weather data product will make a difference in maritime navigation very soon.
7. Cargo vessel in the spotlight
Even though databases count more than 300,000 vessels, most people are interested in the 65,000 merchant vessels. This merchant fleet competes in essence with alternative transportation methods such as road and air. We expect to see a growth in demand for additional curated cargo vessel data in maritime applications. Let’s talk about the weather.
8. Let’s talk about the weather
I cannot discuss trends in maritime intelligence without mentioning weather, partly because Spire Maritime has invested in weather models for quite some time. I was very pleased to hear such a buzz around weather data and fusing this with maritime data analytics. Spire Maritime is already integrating weather data into its predictive model. Weather will play a big role in the future of maritime data analytics. As a result, we will introduce our proprietary weather data to our products in the near future.
In summary, the digital shift in the industry is accelerating. Shipping 2030 further confirmed our convictions to prioritize API data delivery, continue to integrate curated datasets and press forward with innovative predictive data analytics.
I feel enriched by my attendance and hope to keep these important conversations going with my team, our customers and our partners. Did I miss anything?
Feel free to reach out to me on LinkedIn to continue the conversation.