1. Data Analytics in Shipping Opportunities and Challenges

The first area includes shipbuilding and propulsion systems; the second includes sensors, big data analytics, advanced materials, and communications.

Approximately 4%.

Low-quality data can lead to errors in interpretation and tracking new entries.

Traditional data is typically in terabytes, while big data can be in petabytes and exabytes.

Security and privacy, especially when sensitive data is shared externally.

Smart ships, connected ships, and autonomous vehicles.

How frequently and which data will be stored or discarded.

Access to ship data for safety and congestion monitoring.

A cyber-attack on the sensor network.

It will be the driving force shaping the industry's future.

Approximately 180 Mt.

It can create a significant impact by improving safety, environmental performance, and efficiency.

The different forms and formats in which datasets are stored.

It discovers correlations and hidden patterns, impacting vessel performance monitoring and decision-making.

Integration of data from different sources such as fuel consumption, GPS, and engine data.

Large and complex data sets that are difficult to process and analyze using traditional techniques.

A shift towards a transparent industry with data-driven systems.

Increasing requirements for safety, environmental, and efficiency performance.

They are expected to come into force and help the industry transition into the big data era.

It may be implemented globally by the International Maritime Organization (IMO) in the near future.

The capability of a system to support any type of dataset.

The massive quantity of data produced, often in terabytes, petabytes, and beyond.

Around 90% of commercial demand.

Data acquisition, management, processing, storage, and analysis.

Difficulties in capturing, sorting, analyzing, and managing large and complex data sets.

4300%.

Data needs to be accessible at any time for analysis.

It is expected to reduce emissions by up to 2% and lead to a net cost reduction of up to €1.2 billion.

The accuracy and trustworthiness of the data.

Detects the need for maintenance to avoid potential failures.

How values are presented and formatted, related to the source of the data.

It will direct the future of the industry through digital technology and automation.

Ensuring appropriate communication bandwidth for sensors.

Maintenance, navigation, and communications managed by onboard data analytics connected to decision support systems.

Flexible and alternative energy systems, including battery-operated vessels.

51% in the EU and 200% globally.

Based on fuel consumption and the appropriate carbon emission factor for the fuel type.

To analyze asset data and provide early warnings for maintenance needs.

Data processing, reliability, and data security.

To understand hidden features and benefits of available data.

It can obstruct data analysis and reduce the value of the original data.

Continuously from remote locations using remote sensor networks.

Around 3%.

It expands the capability of machinery control and vessel optimization.

They provide information on vessel maneuvering to avoid collisions.

Volume, Variety, Velocity, and Veracity.

It allows access to read, create, update, and delete entries, ensuring traceability through the data lifecycle.

Naval and fishing vessels, and ships undertaking more than 300 voyages within the reporting periods.

Through the use of wireless sensors and extensive satellite communication systems.

Most data scientists spend 75%-80% of their time cleaning up data.

Increased connectivity between crew and shore staff will be essential for operational efficiency and safety.

Reliable forecasts of wind and ocean current data.

They will be applied for efficient and safe operations.

Upcoming regulations, climate change, energy shortages, and technological revolutions.

Quantifying CO2 emissions for ships above 5000 gross tonnage.

It detects the vessel’s operational mode automatically based on sensor data.

Bunker Delivery Note, tank sounding, flow meters, and direct emission measurements.

To filter data and reduce volume by eliminating redundancy.

It facilitates operations such as monitoring emissions and predictive analysis of vessel performance.

The speed at which data is created and moved, often in real-time.

It presents opportunities for improved operations and compliance with regulations.

Increased capability of performance monitoring and reduced human error.

To connect data from various datasets for analysis.

In real-time by analyzing ship data.

Switching fuel in emission-controlled areas with a Sulphur content not exceeding 0.1%.

To monitor, report, and verify CO2 emissions from vessels greater than or equal to 5000 gross tonnage.

To provide reliable information on CO2 emissions in the maritime sector.

Collection methods and definition of measurements.

To protect data networks from external threats like piracy and viruses.