IoT-enabled Platform for Rail Assets Monitoring and Predictive Maintenance (i-RAMP)

2016年，在英国计划的720万次铁路旅行中，有超过23.3万次被取消(公路和铁路办公室，2016)。这些中断中的大部分是由资产故障和铁路网计划外维护造成的。因此，乘客向运营商索赔超过2800万GB的服务中断。来自铁路网络资产和用户的数据是解决乘客和车站运营商所面临挑战的洞察力来源；遗憾的是，这些数据尚未用于此目的(Network Rail 2016)。该项目将开发一个支持物联网的铁路资产监控和预测性维护平台(i-Ramp)。I-RAMP系统由两个输出组成：(I)基于人工智能(AI)的模拟物联网平台(ASIP)，它将提供一个交互的整体模拟平台，以虚拟评估整个火车站，提醒潜在故障并生成最佳维护方案。(Ii)增强现实工具包，它将使用移动增强现实设备和头盔显示器，为火车站的维护提供支持。I-ramp系统将采用人工智能(AI)、物联网(IoT)和增强现实(AR)技术，以实现预测性和预防性维护。该项目的产出将大大减少修复故障的时间，并将为最终用户提供更好的价值。此外，i-Ramp系统将使人们能够更深入地了解客户的行为，并预测如何动态扩展服务以满足乘客的需求。_**关键词**_：用于铁路维护的预测性增强现实，基于物联网的智能铁路车站，增强铁路车站的客户体验。

In 2016, there were more than 233,000 cancelled rail journeys in the UK out of a total of 7.2 million planned journeys (Office of Road and Rail - ORR, 2016). The majority of these disruptions were caused by asset failures and unscheduled maintenance on the rail network. As a result, over £28 million was claimed by passengers from operators for service disruptions. Data available from rail network assets and users are sources of insight to address challenges experienced by passengers and station operators; unfortunately, this data has not been leveraged for this purposes (Network Rail 2016).This project will develop an IoT-enabled Platform for Rail Assets Monitoring and Predictive Maintenance (i-RAMP). The i-RAMP system is composed of two outputs: (i) Artificial Intelligence (AI)-based Simulation IoT Platform (ASIP), which will provide an interactive and holistic simulation platform to virtually evaluate the entire railway station, alert of potential failures and generate optimal maintenance regimes. (ii) Augmented Reality (AR) Toolkit, which will use mobile AR devices and Head Mounted Displays will support rail station maintenance. The i-RAMP system will employ techniques in Artificial Intelligence (AI), Internet of Things (IoT) and Augmented Reality (AR) to enable predictive and preventive maintenance. The project's outputs will significantly reduce time to fix failures and it will provide better value to the end users. In addition, the i-RAMP system will enable a deeper understanding of customers' behaviours and to predict how services can be dynamically scaled to meet the demand of the passengers._**Keywords**_: Predictive Augmented Reality for Rail Maintenance, IoT-based Intelligent Rail Stations, Enhancing Customer Experience in Rail Stations.