A review of the state of the art of improving fuel efficiency using artificial intelligence based on full-scale operational data

Reducing crew boat fuel consumption is of the highest concern. Not only since operational data highlights that the cost of fuel is about 60% of total operational costs, but also due to the fossil fuel contribution to green house gas emissions which tend, to increase is not taken into consideration. Therefore, the use of a system to understand and provide the opportunity to control energy usage is highly recommended. This paper describes the approach of reducing fuel consumption using accurate estimates of wind, wave, and sea current effects, together with data collection from actual ship operations. Unfortunately the implication of such equipment to fill all data is expensive and complicated. Therefore, data analysis is needed together with the combination of engine records in order to fine art the improvment of fuel efficiency. In order to solve the problem, such solutions may to minimize data collection and will be equipt with motion sensor in existing SHIMOS^® system. The current paper describes a step by step process of solving the above problem, together with the use of artificial intellience (AI) methods with adequate data collated from published literature.