Page 163 - Demo

To what extent do data analytics and predictive models contribute to the reduction of fuel consumption and CO2 emissions on a day-to-day basis? Data analytics contribute to daily emissions reduction through precision and repeatability. Predictive models assist in determining optimal speed settings under varying weather patterns, identifying performance drifts in propulsion systems, and refining voyage planning to minimise unnecessary consumption. These decisions are made continuously and influence fuel consumption on every leg of a voyage. The key impact of analytics lies in reducing operational deviation. Even minor discrepancies between planned and actual performance accumulate over time. By identifying these deviations early, analytics prevent small inefficiencies from becoming systemic losses. This disciplined optimisation process delivers measurable improvements across fleets without requiring major capital interventions.However, day-to-day optimisation operates within technological limits. While analytics refine performance within current propulsion frameworks, the broader decarbonisation trajectory depends on fuel transition pathways. The limited availability of scalable alternative fuels presents practical constraints. When regulatory expectations outpace fuel supply readiness, operational optimisation alone cannot bridge the gap. In such circumstances, financial compliance mechanisms risk becoming economic pressure points rather than catalysts for innovation. Sustainable emissions reduction requires alignment between regulatory ambition and technological feasibility.How is the role of seafarers and shorebased teams evolving with the introduction of AI, remote operations, and smart vessels? The integration of AI, remote monitoring, and smart vessel technologies is fundamentally reshaping operational roles by shifting the emphasis from manual execution toward analytical supervision and decision validation. Seafarers are increasingly operating within data-rich May 2026 161