Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways

[Abstract] Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación (España); TEC2013-47141-C4-1-RAgencia Estatal de Investigación (España); TEC2015-69648-REDCAgencia Estatal de Investigación (España); TEC2016-75067-C4-1-

A deep learning approach towards railway safety risk assessment

Railway stations are essential aspects of railway systems, and they play a vital role in public daily life. Various types of AI technology have been utilised in many fields to ensure the safety of people and their assets. In this paper, we propose a novel framework that uses computer vision and pattern recognition to perform risk management in railway systems in which a convolutional neural network (CNN) is applied as a supervised machine learning model to identify risks. However, risk management in railway stations is challenging because stations feature dynamic and complex conditions. Despite extensive efforts by industry associations and researchers to reduce the number of accidents and injuries in this field, such incidents still occur. The proposed model offers a beneficial method for obtaining more accurate motion data, and it detects adverse conditions as soon as possible by capturing fall, slip and trip (FST) events in the stations that represent high-risk outcomes. The framework of the presented method is generalisable to a wide range of locations and to additional types of risks

Automated Level Crossing System: A Computer Vision Based Approach with Raspberry Pi Microcontroller

In a rapidly flourishing country like Bangladesh, accidents in unmanned level crossings are increasing daily. This study presents a deep learning-based approach for automating level crossing junctions, ensuring maximum safety. Here, we develop a fully automated technique using computer vision on a microcontroller that will reduce and eliminate level-crossing deaths and accidents. A Raspberry Pi microcontroller detects impending trains using computer vision on live video, and the intersection is closed until the incoming train passes unimpeded. Live video activity recognition and object detection algorithms scan the junction 24/7. Self-regulating microcontrollers control the entire process. When persistent unauthorized activity is identified, authorities, such as police and fire brigade, are notified via automated messages and notifications. The microcontroller evaluates live rail-track data, and arrival and departure times to anticipate ETAs, train position, velocity, and track problems to avoid head-on collisions. This proposed scheme reduces level crossing accidents and fatalities at a lower cost than current market solutions. Index Terms: Deep Learning, Microcontroller, Object Detection, Railway Crossing, Raspberry PiComment: 4 pages, 7 figures, accepted at the 12th International Conference on Electrical and Computer Engineering (ICECE 2022) to be held on 21-23rd December in Dhaka, Banglades

Njord: a fishing trawler dataset

Fish is one of the main sources of food worldwide. The commercial fishing industry has a lot of different aspects to consider, ranging from sustainability to reporting. The complexity of the domain also attracts a lot of research from different fields like marine biology, fishery sciences, cybernetics, and computer science. In computer science, detection of fishing vessels via for example remote sensing and classification of fish from images or videos using machine learning or other analysis methods attracts growing attention. Surprisingly, little work has been done that considers what is happening on board the fishing vessels. On the deck of the boats, a lot of data and important information are generated with potential applications, such as automatic detection of accidents or automatic reporting of fish caught. This paper presents Njord, a fishing trawler dataset consisting of surveillance videos from a modern off-shore fishing trawler at sea. The main goal of this dataset is to show the potential and possibilities that analysis of such data can provide. In addition to the data, we provide a baseline analysis and discuss several possible research questions this dataset could help answer

Enabling technologies and cyber-physical systems for mission-critical scenarios

Programa Oficial de Doutoramento en Tecnoloxías da Información e Comunicacións en Redes Móbiles . 5029P01[Abstract] Reliable transport systems, defense, public safety and quality assurance in the Industry 4.0 are essential in a modern society. In a mission-critical scenario, a mission failure would jeopardize human lives and put at risk some other assets whose impairment or loss would significantly harm society or business results. Even small degradations of the communications supporting the mission could have large and possibly dire consequences. On the one hand, mission-critical organizations wish to utilize the most modern, disruptive and innovative communication systems and technologies, and yet, on the other hand, need to comply with strict requirements, which are very different to those of non critical scenarios. The aim of this thesis is to assess the feasibility of applying emerging technologies like Internet of Things (IoT), Cyber-Physical Systems (CPS) and 4G broadband communications in mission-critical scenarios along three key critical infrastructure sectors: transportation, defense and public safety, and shipbuilding. Regarding the transport sector, this thesis provides an understanding of the progress of communications technologies used for railways since the implantation of Global System for Mobile communications-Railways (GSM-R). The aim of this work is to envision the potential contribution of Long Term Evolution (LTE) to provide additional features that GSM-R would never support. Furthermore, the ability of Industrial IoT for revolutionizing the railway industry and confront today's challenges is presented. Moreover, a detailed review of the most common flaws found in Radio Frequency IDentification (RFID) based IoT systems is presented, including the latest attacks described in the literature. As a result, a novel methodology for auditing security and reverse engineering RFID communications in transport applications is introduced. The second sector selected is driven by new operational needs and the challenges that arise from modern military deployments. The strategic advantages of 4G broadband technologies massively deployed in civil scenarios are examined. Furthermore, this thesis analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where defense and public safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. The last part is devoted to the shipbuilding industry. After defining the novel concept of Shipyard 4.0, how a shipyard pipe workshop works and what are the requirements for building a smart pipe system are described in detail. Furthermore, the foundations for enabling an affordable CPS for Shipyards 4.0 are presented. The CPS proposed consists of a network of beacons that continuously collect information about the location of the pipes. Its design allows shipyards to obtain more information on the pipes and to make better use of it. Moreover, it is indicated how to build a positioning system from scratch in an environment as harsh in terms of communications as a shipyard, showing an example of its architecture and implementation.[Resumen] En la sociedad moderna, los sistemas de transporte fiables, la defensa, la seguridad pública y el control de la calidad en la Industria 4.0 son esenciales. En un escenario de misión crítica, el fracaso de una misión pone en peligro vidas humanas y en riesgo otros activos cuyo deterioro o pérdida perjudicaría significativamente a la sociedad o a los resultados de una empresa. Incluso pequeñas degradaciones en las comunicaciones que apoyan la misión podrían tener importantes y posiblemente terribles consecuencias. Por un lado, las organizaciones de misión crítica desean utilizar los sistemas y tecnologías de comunicación más modernos, disruptivos e innovadores y, sin embargo, deben cumplir requisitos estrictos que son muy diferentes a los relativos a escenarios no críticos. El objetivo principal de esta tesis es evaluar la viabilidad de aplicar tecnologías emergentes como Internet of Things (IoT), Cyber-Physical Systems (CPS) y comunicaciones de banda ancha 4G en escenarios de misión crítica en tres sectores clave de infraestructura crítica: transporte, defensa y seguridad pública, y construcción naval. Respecto al sector del transporte, esta tesis permite comprender el progreso de las tecnologías de comunicación en el ámbito ferroviario desde la implantación de Global System for Mobile communications-Railway (GSM-R). El objetivo de este trabajo es analizar la contribución potencial de Long Term Evolution (LTE) para proporcionar características adicionales que GSM-R nunca podría soportar. Además, se presenta la capacidad de la IoT industrial para revolucionar la industria ferroviaria y afrontar los retos actuales. Asimismo, se estudian con detalle las vulnerabilidades más comunes de los sistemas IoT basados en Radio Frequency IDentification (RFID), incluyendo los últimos ataques descritos en la literatura. Como resultado, se presenta una metodología innovadora para realizar auditorías de seguridad e ingeniería inversa de las comunicaciones RFID en aplicaciones de transporte. El segundo sector elegido viene impulsado por las nuevas necesidades operacionales y los desafíos que surgen de los despliegues militares modernos. Para afrontarlos, se analizan las ventajas estratégicas de las tecnologías de banda ancha 4G masivamente desplegadas en escenarios civiles. Asimismo, esta tesis analiza el gran potencial de aplicación de las tecnologías IoT para revolucionar la guerra moderna y proporcionar beneficios similares a los alcanzados por la industria. Se identifican escenarios en los que la defensa y la seguridad pública podrían aprovechar mejor las capacidades comerciales de IoT para ofrecer una mayor capacidad de supervivencia al combatiente o a los servicios de emergencias, a la vez que reduce los costes y aumenta la eficiencia y efectividad de las operaciones. La última parte se dedica a la industria de construcción naval. Después de definir el novedoso concepto de Astillero 4.0, se describe en detalle cómo funciona el taller de tubería de astillero y cuáles son los requisitos para construir un sistema de tuberías inteligentes. Además, se presentan los fundamentos para posibilitar un CPS asequible para Astilleros 4.0. El CPS propuesto consiste en una red de balizas que continuamente recogen información sobre la ubicación de las tuberías. Su diseño permite a los astilleros obtener más información sobre las tuberías y hacer un mejor uso de las mismas. Asimismo, se indica cómo construir un sistema de posicionamiento desde cero en un entorno tan hostil en términos de comunicaciones, mostrando un ejemplo de su arquitectura e implementación