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Given the plethora of individual preferences and requirements of public transport passengers for travel, seating, catering, etc., it becomes very challenging to tailor generic services to individuals’ requirements using the existing service platforms. As tens of thousands of sensors have been already deployed along roadsides and rail tracks and on...
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... IoT systems cannot be protected using traditional security techniques because of their computational limitations and inherent resources [26][27][28][29]. ML approaches in IDSs identify unknown and known attacks on IoT devices in real time [30,31]. IoT protocols and network structure are not relevant to an IDS proposed in [32]. ...
The Internet of Railways (IoR) network is made up of a variety of sensors, actuators, network layers, and communication systems that work together to build a railway system. The IoR’s success depends on effective communication. A network of railways uses a variety of protocols to share and transmit information amongst each other. Because of the widespread usage of wireless technology on trains, the entire system is susceptible to hacks. These hacks could lead to harmful behavior on the Internet of Railways if they spread sensitive data to an infected network or a fake user. For the previous few years, spotting IoR attacks has been incredibly challenging. To detect malicious intrusions, models based on machine learning and deep learning must still contend with the problem of selecting features. k-means clustering has been used for feature scoring and ranking because of this. To categorize attacks in two datasets, the Internet of Railways and the University of New South Wales, we employed a new neural network model, the extended neural network (ENN). Accuracy and precision were among the model’s strengths. According to our proposed ENN model, the feature-scoring technique performed well. The most accurate models in dataset 1 (UNSW-NB15) were based on deep neural networks (DNNs) (92.2%), long short-term memory LSTM (90.9%), and ENN (99.7%). To categorize attacks, the second dataset (IOR dataset) yielded the highest accuracy (99.3%) for ENN, followed by CNN (87%), LSTM (89%), and DNN (82.3%).
... IoT systems cannot be protected using traditional security techniques because of their computational limitations and inherent resources [26][27][28][29]. ML approaches in IDSs identify unknown and known attacks on IoT devices in real time [30,31]. IoT protocols and network structure are not relevant to an IDS proposed in [32]. ...
The Internet of Railways (IoR) network is made up of a variety of sensors, actuators, network layers, and communication systems that work together to build a railway system. The IoR’s success depends on effective communication. A network of railways uses a variety of protocols to share and transmit information amongst each other. Because of the widespread usage of wireless technology on trains, the entire system is susceptible to hacks. These hacks could lead to harmful behavior on the Internet of Railways if they spread sensitive data to an infected network or a fake user. For the previous few years, spotting IoR attacks has been incredibly challenging. To detect malicious intrusions, models based on machine learning and deep learning must still contend with the problem of selecting features. k-means clustering has been used for feature scoring and ranking because of this. To categorize attacks in two datasets, the Internet of Railways and the University of New South Wales, we employed a new neural network model, the extended neural network (ENN). Accuracy and precision were among the model’s strengths. According to our proposed ENN model, the feature-scoring technique performed well. The most accurate models in dataset 1 (UNSW-NB15) were based on deep neural networks (DNNs) (92.2%), long short-term memory LSTM (90.9%), and ENN (99.7%). To categorize attacks, the second dataset (IOR dataset) yielded the highest accuracy (99.3%) for ENN, followed by CNN (87%), LSTM (89%), and DNN (82.3%).
... Furthermore, data collected at stops can be used to evaluate how often those locations are frequented [53]. Eiza et al. [54] proposed rail IoT (RIoT), which applies to the railway context. The authors proposed an architectural platform and demonstrated how passenger experiences could be improved. ...
... To successfully implement IoT-based public transportation solutions that deliver high-quality data with high reliability, specific architectural designs are needed. Hence, a high-level architectural platform was suggested in [54], consisting of five components: trains, tracks, stations, passengers, and a rail control center. The trains contain technologies, such as heat and capacity sensors, beacons, and WiFi devices. ...
Public transportation is expensive to operate and maintain and is often unsatisfactory. The attractiveness of public transportation can be enhanced by making it more seamless, which, in turn, would reduce financial constraints and inefficiencies. The adoption of mobile devices for ticketing solutions is promising. However, current solutions are often inflexible and require manual interactions that produce evanescent data. Therefore, using leading-edge technologies and infrastructure, it is desirable to develop a solution to fully automate fare collection. In this paper, we provide a comprehensive literature review to understand the state of public transportation and to facilitate the development and implementation of automated fare collection solutions. First, we discuss existing mobile technologies and their common ticketing implementations. Second, we provide a predictive behavior model with sensor analytics to better understand customer needs. Finally, we highlight how machine learning can harness transactional ticketing data to create valuable business intelligence. Overall, developing and implementing automated fare collection solutions in urban transportation is expected to have a significant positive impact on customer experiences, the emergence of new business models and the reduction of pollutant emissions.
... The suggested methodology is anticipated to meet the requirement of high spectrum and high-data-rate efficiency. Eiza et al. (2015) suggested a communication model which was named as "RIoT" (Rail Internet of Things) to enhance railway services and discussed the user needs. The RIoT system included a number of components, such as trains, tracks, stations, passengers, and rail control center. ...
... The study proposed an IoT-based system for mass passenger rail transit that relied on information The suggested methodology is anticipated to meet the requirement of high spectrum and high-datarate efficiency. 10 Eiza et al. (2015) Develop the "RIoT" (Rail Internet of Things). ...
The Internet of Things (IoT) symbolizes numerous devices which are connected globally through the internet technology and are able to collect and share relevant data. The IoT has thus achieved a significant advancement in the field of sensors, networks, and communication technologies, such as long-term evolution (LTE) technology, fifth generation (5G) technology, wireless sensor networks (WSN), and others. Apart from technological advancements, the ability of IoT to run fully embedded (with or without an operating system), gather real-time data, estimate physical parameters, facilitate decision making based on the data gathered, use of various networks (e.g., local area networks (LAN), low-power wide-area network (LPWAN), cellular LPWAN) has provided enormous opportunities for its applications in the railway industry and other domains. The current study performs a comprehensive holistic survey of various IoT technologies that can be used in railway operations, management, maintenance, video surveillance, and safety at level crossings. This study also discusses current trends in the IoT, emerging IoT technologies, green IoT applications, and various research studies that have been conducted in the areas related to railway applications. Furthermore, various challenges that are associated with the IoT applications are discussed along with potential efforts that can be made to overcome these challenges. The outcomes of this work are expected to offer important insights regarding the applicability of IoT technologies for sustainable railway transportation, their future potential, operational benefits to relevant stakeholders and authorities, as well as critical future research needs that have to be addressed in the following years.
... Firstly authors describe main components of IRTS (M H Eiza et al., 2015) and then provide some solution of these components with the help of IoT technology and tools for improvement in this system. Stations: Place where passengers can get on and off trains and/or goods may be loaded or unloaded, also different objects and systems can be found in a rail station including the rail information system, ticketing system, Wi-Fi, Waiting room, Toilets, Cameras, Check in/out system etc. ...
... These devices contain many sensors that could provide specific information related to the journey requirements for the passengers, like location, destination, journey preferences, Seats Availability, Food information on next stoppage etc. (M. H. Eiza et al., 2015). IoT technology will further improve the passengers experience on public transit by offering real time tracking system, indicating exactly how many more minutes their train is away from pulling into the station and which platform it is approaching, also notifications if any unexpected events, and personalized travel news to passengers, So the passenger becomes a smart passenger. ...
... Firstly authors describe main components of IRTS (M H Eiza et al., 2015) and then provide some solution of these components with the help of IoT technology and tools for improvement in this system. Stations: Place where passengers can get on and off trains and/or goods may be loaded or unloaded, also different objects and systems can be found in a rail station including the rail information system, ticketing system, Wi-Fi, Waiting room, Toilets, Cameras, Check in/out system etc. ...
... These devices contain many sensors that could provide specific information related to the journey requirements for the passengers, like location, destination, journey preferences, Seats Availability, Food information on next stoppage etc. (M. H. Eiza et al., 2015). IoT technology will further improve the passengers experience on public transit by offering real time tracking system, indicating exactly how many more minutes their train is away from pulling into the station and which platform it is approaching, also notifications if any unexpected events, and personalized travel news to passengers, So the passenger becomes a smart passenger. ...
In this chapter, the authors have introduced the use of Internet of Things (IoT) applications and services in Indian Railway Transportation System (IRTS). Railway transportation infrastructure is one of the most important factors for the development of any country. India is a developing country and we have a vision to transform India into a developed nation by 2020 using different technologies and tools. Therefore, we
need to adopt smart and secure technology for advancement in each area especially in railway transportation for growth and betterment of the country. Further, authors has introduced Vehicular Ad-Hoc Network (VANET) concept for automatic railway gate controlling system to reduce number of accidents over railway premises and enhance the system components for the Indian railway transportation system to provide the comfort, security, safety and infotainment services to the passengers.
... Firstly authors describe main components of IRTS (M H Eiza et al., 2015) and then provide some solution of these components with the help of IoT technology and tools for improvement in this system. Stations: Place where passengers can get on and off trains and/or goods may be loaded or unloaded, also different objects and systems can be found in a rail station including the rail information system, ticketing system, Wi-Fi, Waiting room, Toilets, Cameras, Check in/out system etc. ...
... These devices contain many sensors that could provide specific information related to the journey requirements for the passengers, like location, destination, journey preferences, Seats Availability, Food information on next stoppage etc. (M. H. Eiza et al., 2015). IoT technology will further improve the passengers experience on public transit by offering real time tracking system, indicating exactly how many more minutes their train is away from pulling into the station and which platform it is approaching, also notifications if any unexpected events, and personalized travel news to passengers, So the passenger becomes a smart passenger. ...
In this chapter, the authors have introduced the use of Internet of Things (IoT) applications and services in Indian Railway Transportation System (IRTS). Railway transportation infrastructure is one of the most important factors for the development of any country. India is a developing country and we have a vision to transform India into a developed nation by 2020 using different technologies and tools. Therefore, we need to adopt smart and secure technology for advancement in each area especially in railway transportation for growth and betterment of the country. Further, authors has introduced Vehicular Ad-Hoc Network (VANET) concept for automatic railway gate controlling system to reduce number of accidents over railway premises and enhance the system components for the Indian railway transportation system to provide the comfort, security, safety and infotainment services to the passengers.
... RGB-D sensors) which provide large and complex data. Eiza et al. [19] investigate the Internet of Things concept on railroad transportation. They discussed the security issues and unstable dynamics of IoT. ...
Nowadays, huge amounts of data have been captured along with the day-to-day operation of assets including railway systems. Hence, we have come to the era of big data. The utilization of big data technologies for asset condition information management is becoming indispensable for improving asset management decision making. The vital information such as precursor information collected on failure modes and knowledge that may be available for analysis is hidden within the large extent of data. There are analysis tools incorporated with techniques such as multiple regression analysis and machine learning that are facilitated by the availability of big data. Therefore, the utilization of big data technologies for asset condition information management is becoming indispensable for improving asset management decision making. This paper provides a review of the requirements and challenges for big data analytics applications to railway asset management. The review focuses on railway asset data collection, data management, data applications with the implementation of Blockchain technology as well as big data analytics technologies. The need for, and the importance of big data analytics in railway asset management; and the requirement for the asset condition data collection in the railway industry are highlighted. Research challenges in railway asset management via application of big data analytics are identified and the future research directions are presented.
