Railway Optical Detection and Obstructions-Tunnel & Station Monitoring

Vortex IoT是一家屡获殊荣的威尔士中小企业，领导着一个财团，该财团还包括威尔士网络铁路和运输，Kelos Amey, Balfour Beatty。该公司在产品开发方面有着良好的记录，并组建了一支高素质的工程师团队，他们是物联网（IoT），无线网状网络和人工智能（AI）的专家。而其合作伙伴分别是主要的铁路承包商和集成商和网络铁路基础设施（铁路资产所有者/客户）。铁路客运和货运客户对铁路基础设施和机车车辆资产的高可用性的需求日益增加。铁路基础设施的远程状态监测（RCM）对于最大限度地提高铁路网络的可靠性和可维护性至关重要，是实现网络铁路能力交付计划设定的“最小干扰和延迟”目标的关键推动因素。此次融资投标的重点是获得额外的资金，以加速“先发者”RCM解决方案的上市。拟议的项目- RODIO®- tsm（铁路障碍物和侵入物光学探测-隧道和车站监测）-将在两个实时铁路地点部署并集成18个设备：由NRI提供的位于Melton的1.2公里实时铁路隧道及其两个入口的200米，以及位于南威尔士（Bargoed）的一个实时火车站，该火车站拥有200米的车站面积和100米的城市隧道。该项目将用户测试激光雷达传感器网络的入侵/障碍物检测能力，该网络无线连接到传感器融合和人工智能引擎所在的RODIO边缘网关，以处理数据，然后将结果（例如通知、威胁级别等）推送到网络铁路电信（NRT）云服务器和无处不在的IP网络。该系统使用数据融合和深度学习分类器识别入侵和阻塞类型和严重程度，旨在实现高召回率（灵敏度）和高误报精度。该系统可以准确地检测、区分和分类(a)入侵-人类和动物的运动；(b)障碍物-岩石坠落、树木坠落、砖块坠落、碎片坠落；(c)岩土工程资产故障-局部快速土方工程、洪水、山体滑坡，然后向铁路控制中心发送实时情况警报，以作为咨询系统促使进一步调查。铁路行业准备水平（RIRL）定义的NRl产品验收框架是我们产品成熟度的重要指标。RODIO- tsm项目将把RODIO®产品的当前地位提升到RIRL8。

Vortex IoT is an award-winning Wales based SME heading up a consortium that also includes Network Rail and Transport for Wales, Kelos Amey, Balfour Beatty. The company has a proven record in product development and has assembled a highly qualified team of Engineers who are specialist Internet of Things (IoT), wireless mesh networks and Artificial Intelligence (AI). Whilst its partners are a prime rail contractor and integrator and Network Rail Infrastructure respectively (Railway asset owner/ customer). There is an increasing demand for high availability of rail infrastructure and rolling stock assets for rail passenger journeys and freight customers. Remote Condition Monitoring (RCM) of rail infrastructure is essential to maximise the reliability and maintainability of the rail network and is a key enabler for achieving the goal of 'Minimal Disruption and Delay' set by Network Rail’s Capability Delivery Plan. This funding bid is focussed on securing additional funds to accelerate a ‘first mover’ RCM solution to market. The proposed project - RODIO®-TSM (Railway Optical Detection of Obstructions and Intrusions-Tunnel and Station Monitoring) - will deploy and integrate 18 devices in two live rail locations: a live 1.2km rail tunnel and 200m of its either entrance at Melton offered by NRI and a live train station in South Wales (Bargoed) with 200m station area and 100m urban tunnel. The project will user test the intrusion/obstruction detection capability of the LiDAR sensor network, that are wirelessly connected to RODIO edge gateway where the sensor fusion and AI engine resides to process the data and then results (e.g. Notifications, Threat level, …) are pushed to Network Rail Telecom (NRT) cloud server and ubiquitous IP Network. The system uses data fusion and Deep Learning classifiers to identify intrusion and obstruction types and severities aiming for high recall (sensitivity) and high precision against false alarms. This system can accurately detect, differentiate and classify (a) Intrusions – Human and Animal movements (b) Obstructions – Rock fall, tree fall, brick fall, debris fall, (c) Geotechnical asset failures – localised rapid earthworks, flooding, landslides and then sends real time situational alerts to the rail control centre to prompt further investigation as an advisory system. The NRl Product Acceptance Framework defined by Rail Industry Readiness Level (RIRL) is a vital indicator of our product maturity. The RODIO-TSM project will advance the current position of the RODIO® product to RIRL8.