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DeepSea: Leveraging AI and Weather Data for Optimal Maritime Fuel Consumption
技术
- 分析与建模 - 预测分析
适用行业
- 海洋与航运
- 可再生能源
用例
- 车辆性能监测
挑战
DeepSea 是一家领先的人工智能海事实体,面临着利用高度准确和详细的海洋天气数据源增强其船舶特定性能模型的挑战。目标是预测风、波浪、洋流和其他航海现象对燃料消耗的影响。然而,这项任务并非没有困难。世界上 80% 的海洋仍未绘制地图和观测,这使得准确预测所需的数据存在相当大的缺口。此外,现有的海洋风浪条件数据往往不一致。这是因为它是通过浮标和游船上部署的仪器收集的,导致风天气观测结果存在差异。
关于客户
DeepSea 是一家领先的人工智能海事实体,专门从事航程优化。他们利用先进技术开发特定于船舶的性能模型,可以预测各种航海现象对船舶性能的影响。他们的目标是通过准确预测风、波浪和水流等因素的影响来优化海上作业,特别是在燃料消耗方面。为了实现这一目标,他们需要高度准确和详细的海洋天气数据,他们用这些数据来增强他们的预测模型和算法。
解决方案
为了克服这些挑战,DeepSea 与 Spire Global 合作。通过将 Spire 的天气数据集成到其预测航程规划算法中,DeepSea 能够覆盖公海的全球范围。这使得我们能够更全面、更准确地了解海洋状况,从而增强其性能模型的预测能力。 DeepSea 随后分析了中风和强风条件下船速与电力需求增加(进而导致燃料消耗)之间的关系。该分析使他们能够根据不同的风况更好地预测和优化燃油消耗。
运营影响
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