Railway Optical Detection and Obstructions-Tunnel & Station Monitoring
Railway Optical Detection and Obstructions-Tunnel & Station Monitoring
批准号:
971753
负责人:
金额:
$49.92万
依托单位:
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --
中文摘要
Vertex IoT是一家总部位于威尔士的屡获殊荣的中小企业,牵头的财团还包括威尔士网络铁路和运输公司、Kelos Amey公司、Balfour Beatty公司。该公司在产品开发方面拥有久经考验的记录,并组建了一支高素质的工程师团队,他们是物联网(IoT)、无线网状网和人工智能(AI)的专家。而其合作伙伴分别是主要铁路承包商和集成商以及网络铁路基础设施(铁路资产所有者/客户)。铁路旅客和货运客户对铁路基础设施和铁路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况监测(RCM)对于最大限度地提高铁路网的可靠性和可维护性至关重要,也是实现Network Rail的能力交付计划设定的“最小中断和延误”目标的关键推动因素。此次融资竞标的重点是获得额外资金,以加快RCM解决方案的“先行者”上市。拟议的项目-Rodio®-TSM(铁路光学障碍物和侵入检测-隧道和车站监控)-将在两个带电轨道地点部署和集成18个设备:由NRI提供的Melton带电1.2公里铁路隧道及其200米入口,以及南威尔士(Bargoed)的带电火车站,车站面积200米,城市隧道100米。该项目将测试激光雷达传感器网络的入侵/障碍检测能力,该传感器网络无线连接到传感器融合和人工智能引擎驻留的Rodio边缘网关,以处理数据并随后得出结果(例如,通知、威胁级别、…)被推向网络铁路电信(NRT)云服务器和泛在IP网络。该系统使用数据融合和深度学习分类器来识别入侵和障碍的类型和严重程度,旨在实现高召回率(敏感度)和高精度的误报警。该系统可以准确地检测、区分和分类(A)侵入-人类和动物移动(B)障碍物-石块坠落、树木倒塌、砖块坠落、碎片坠落,(C)岩土资产故障-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,促使进一步调查,作为咨询系统。由铁路行业准备水平(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®产品的当前位置提升到RIRL8。
英文摘要
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.
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