  Several approaches have been developed for improving the ship energy
efficiency, thereby reducing operating costs and ensuring compliance with
climate change mitigation regulations. Many of these approaches will heavily
depend on measured data from onboard IoT devices, including operational and
environmental information, as well as external data sources for additional
navigational data. In this paper, we develop a framework that implements
time-series analysis techniques to optimize the vessel's speed profile for
improving the vessel's energy efficiency. We present a case study involving a
real-world data from a passenger vessel that was collected over a span of 15
months in the south of Sweden. The results indicate that the implemented models
exhibit a range of outcomes and adaptability across different scenarios. The
findings highlight the effectiveness of time-series analysis approach for
optimizing vessel voyages within the context of constrained landscapes, as
often seen in short-sea shipping.
