LeisAIR: Leisure watercraft AI Image Recognition

纳什海事公司是航运、航海和海事风险方面的专家。为了管理安全和最大限度地提高港口的运力，必须通过航行风险评估（NRA）过程来识别、衡量和减轻风险。NRA是海上安全管理的关键部分，也是任何海上基础设施项目批准过程中的重要步骤。NRA不可或缺的是对船舶交通数据的分析。通过自动识别系统（AIS），商业和一些大型娱乐船只可以随时获得可靠的位置和运动数据。然而，对于小型船只、小艇、划艇、皮划艇等娱乐用水者，没有这样的数据。相反，有关娱乐用水者的活动和数量的数据是通过与利益相关者协商和直接观察收集的。前者主观性强，后者资源密集、时间有限。拥有娱乐用水用户的准确数据将使NRA过程的准确性提高一个数量级，促进适当风险控制的使用，实现多个海事利益相关者的和谐共存，并最大限度地提高所有用水用户的能力。NASH海事公司和布鲁内尔大学将利用人工智能图像识别能力的最新进展来自动化娱乐船只数据收集过程，该项目将建立在NASH海事公司现有的人工智能模型的基础上，以改进和扩展其从港口和港口闭路电视馈电中准确识别和记录各种不同类型娱乐船只数量的能力。该模型将用于提高nra的准确性和降低交付成本。这将大大提高航行风险评估的准确性，使评估过程更具成本效益，最大限度地提高海上运输能力，提高海上安全。除了NRA之外，这项技术还有其他应用，NASH将探索使用娱乐船图像识别来支持：*其他海上作业的风险评估*用水管理/测绘研究*地方法规的执行*安全性*导航决策支持

NASH Maritime are specialists in shipping, navigation and maritime risk. To manage safety and maximise capacity in ports and harbours, it is essential that risks are identified, measured and mitigated through a process of Navigation Risk Assessment (NRA). The NRA is a key part of the management of maritime safety and an essential step in the consenting process of any maritime infrastructure project.Integral to NRA is the analysis of vessel traffic data. Robust, reliable location and movement data for commercial, and some large recreational, vessels are readily available via the Automatic Identification System (AIS). However no such data are available for recreational water users -- small craft, dinghies, rowers, kayakers etc.Instead, data on the movements and volumes of recreational water users is gathered through stakeholder consultation and by direct observation. The former is very subjective, the latter resource intensive and time-limited. Having accurate data on recreational water users would improve the accuracy of the NRA process by an order of magnitude, promoting the use of appropriate risk controls, enabling the harmonious coexistence of multiple maritime stakeholders and maximising capacity for all water users.NASH Maritime and Brunel University will use recent advances in the capability of AI image recognition to automate the process of recreational vessel data collection The project will build on NASH Maritime's existing AI model to improve and extend its capability to accurately identify and record volumes of various different types of recreational craft from port and harbour CCTV feeds. The model will be used to increase the accuracy and reduce the cost of delivering NRAs.This will deliver a step-change in the accuracy of delivering navigation risk assessments and make the process more cost-effective, maximising maritime transport capacity and improving maritime safety.There are applications for this technology beyond NRA, and NASH will explore the use of recreational vessel image recognition to support:* Risk assessment for other maritime operations* Water use management/ mapping studies* Enforcement of local regulations* Security* Navigation decision support