PANGIA

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Project challenge & objective:

The general objective of the PANGIA project is to develop a service for stakeholders in the shipping industry. PANGIA enables the synergy between advanced data-driven analysis and expert human input to deliver:
a) reduced service and maintenance costs via proactive maintenance planning;
b) protection of the natural environment through the reduction of fuel consumption and emissions via sea vessel performance optimization;
c) health and safety of crew and passengers via early detection and mitigation of safety or health hazards.
The PANGIA system is the evolution of the Performance Optimization Control Room (POCR) (a service developed by Columbia Shipmanagement) towards the international market. The PANGIA service represents a significant enhancement of the current POCR solution via modern techniques in data gathering (IoT) and data science (AI/ML) in order to allow Columbia Shipmanagement to offer best-in-class services to its global shipping clients. This will focus on cost optimization and improvement of margins, for Columbia Shipmanagement and their customers, and also helps them to align with directives of the International Maritime Organisation (IMO).

Role of CMMI:

The role of CMMI is to develop a cloud AI platform by designing the data lake, which aggregates all data from the field ships, and implementing a custom cognitive fusion software system through innovative ML software decision tools. CMMI also contributes to engaging stakeholders, who assist in defining the business objectives, identifying new sensor needs (and the associated suppliers), and defining the solutions’ operational boundaries.

Consortium:

This project has received funding from the ‘INNOVATE – RESTART 2016-2020 Programme for Research, Technological Development and Innovation’ of the Research and Innovation Foundation (RIF). It is in ‘Development and Promotion of Internationally Competitive Innovative Products and Services from Existing Enterprises’ specific programme under grant agreement No: INNOVATE/0719(B)/0044