Wayside Train Monitoring Systems

2019 ◽  
pp. 728-754
Author(s):  
Swastikaa Moudgil ◽  
Ashim Bhasin ◽  
Ankit Gupta
Keyword(s):  
Big Data ◽  
Monitoring System ◽  
Significant Role ◽  
Risk Control ◽  
Rolling Stock ◽  
Monitoring Systems ◽  
Rail Industry ◽  
Operational Safety ◽  
Transport Industry ◽  
Optimum Cost

The present competitive world of transport particularly the rail industry is driven by automation and centralization. New ways are being devised each day by the operators and managers to improve efficiency, operational safety, and risk control. Big Data and its multiple applications play a significant role in developing ways of analyzing and evaluating the rail data gathered and using it to enhance the transport industry. Wayside train Monitoring System is a field that is slowly gaining popularity through the different methods it provides to handle the big Data of the transport industry. It can measure the operational performance of rolling stock and infrastructure assets as well as the direct surroundings. The chapter addresses the problem of overall safety and optimum cost of railways transportation. Consequently, the chapter aims to resolve the following issues: How can the rail industry leverage the enormous amount of data available? How can industry players benefit from the data and use it to understand the real needs of travelers?

Wayside Train Monitoring Systems

2018 ◽  
pp. 67-93
Author(s):  
Swastikaa Moudgil ◽  
Ashim Bhasin ◽  
Ankit Gupta
Keyword(s):  
Big Data ◽  
Monitoring System ◽  
Significant Role ◽  
Risk Control ◽  
Rolling Stock ◽  
Monitoring Systems ◽  
Rail Industry ◽  
Operational Safety ◽  
Transport Industry ◽  
Optimum Cost

The present competitive world of transport particularly the rail industry is driven by automation and centralization. New ways are being devised each day by the operators and managers to improve efficiency, operational safety, and risk control. Big Data and its multiple applications play a significant role in developing ways of analyzing and evaluating the rail data gathered and using it to enhance the transport industry. Wayside train Monitoring System is a field that is slowly gaining popularity through the different methods it provides to handle the big Data of the transport industry. It can measure the operational performance of rolling stock and infrastructure assets as well as the direct surroundings. The chapter addresses the problem of overall safety and optimum cost of railways transportation. Consequently, the chapter aims to resolve the following issues: How can the rail industry leverage the enormous amount of data available? How can industry players benefit from the data and use it to understand the real needs of travelers?

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

10.2196/20921 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e20921
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

Background Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. Objective This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. Methods This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. Results By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. Conclusions Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

scholarly journals Monitoring System for Railway Automation Devices Based on the Industrial Internet of Things

2021 ◽  
Vol 18 (6) ◽  
pp. 118-134
Author(s):  
D. V. Efanov
Keyword(s):  
Monitoring System ◽  
Data Transmission ◽  
Radio Channel ◽  
Rolling Stock ◽  
Monitoring Systems ◽  
Limited Area ◽  
Technical Diagnostics ◽  
Design Work ◽  
Advantages And Disadvantages ◽  
Railway Infrastructure

The features of monitoring systems for railway infrastructure and rolling stock are considered. The main approaches to organisation of monitoring of railway infrastructure and rolling stock objects are described, their advantages and disadvantages are noted. The main objective of this work is to present to the reader a conceptual vision of a system for monitoring devices and systems for ensuring train traffic safety, using technologies for transmitting diagnostic information over a radio channel. The methods of the theory of technical diagnostics and monitoring were used. Attention is focused on the use of wireless data transmission technologies and the use of autonomous industrial automation sensors for monitoring systems for railway automation devices.The architecture of the monitoring system is presented. The description of the system itself and the monitoring technology is given, the main advantages of the presented approach are noted, which, first, are linked to reduction of the volume of design work and of energy consumption of the system as a whole. The disadvantages are associated with the need to replace autonomous power supply sources, ensure security of the data transmission network, to proceed with periodic verification and calibration of measuring instruments. The basic diagrams of connecting sensors for measuring physical quantities to the circuit units of railway automation are presented. A list of parameters necessary for high-quality and effective monitoring of railway automation devices is given. The need is noted for both the control of mechanical and geometric parameters of devices and the accounting of data from interconnected objects of railway infrastructure and rolling stock. The proposed approach can find its application in the field of railway automation and, first of all, at those facilities that are located in premises with limited area (e.g. at subway facilities).

scholarly journals Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Qiang Pan ◽  
Damien Brulin ◽  
Eric Campo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Monitoring System ◽  
The Body ◽  
Monitoring Systems ◽  
Sleep Monitoring ◽  
Advantages And Disadvantages ◽  
System Solution

BACKGROUND Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. OBJECTIVE This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. METHODS This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. RESULTS By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. CONCLUSIONS Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

INVESTMENTS IN THE LOCOMOTIVE COMPLEX INFRASTRUCTURE. INFRASTRUCTURE NEEDS PLANS AND FORECASTS

2020 ◽  
Vol 1 (4) ◽  
pp. 106-110
Author(s):  
A. G. YEROYAN ◽  
Keyword(s):  
Significant Role ◽  
Rolling Stock ◽  
Infrastructure Development ◽  
Electric Locomotive ◽  
Maintenance And Repair ◽  
Technological Readiness ◽  
Railway Industry ◽  
Locomotive Repair

In connection with the prospects for the development of the railway industry until 2030, a significant role in improving the technological readiness of maintenance and repair of traction rolling stock belongs to diesel, electric locomotive repair and service depots. The article considers the main directions of development and modernization of the locomotive complex infrastructure. Possible methods of financing mechanisms for investment in infrastructure development have been identified.

scholarly journals Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 561
Author(s):  
Taehee Lee ◽  
Chanjun Chun ◽  
Seung-Ki Ryu
Keyword(s):  
Monitoring System ◽  
Poor Performance ◽  
Road Surface ◽  
Monitoring Systems ◽  
Advantages And Disadvantages ◽  
Acceleration Data ◽  
Road Surfaces ◽  
Road Surface Monitoring ◽  
Surface Monitoring ◽  
Acquisition Method

Road surfaces should be maintained in excellent condition to ensure the safety of motorists. To this end, there exist various road-surface monitoring systems, each of which is known to have specific advantages and disadvantages. In this study, a smartphone-based dual-acquisition method system capable of acquiring images of road-surface anomalies and measuring the acceleration of the vehicle upon their detection was developed to explore the complementarity benefits of the two different methods. A road test was conducted in which 1896 road-surface images and corresponding three-axis acceleration data were acquired. All images were classified based on the presence and type of anomalies, and histograms of the maximum variations in the acceleration in the gravitational direction were comparatively analyzed. When the types of anomalies were not considered, it was difficult to identify their effects using the histograms. The differences among histograms became evident upon consideration of whether the vehicle wheels passed over the anomalies, and when excluding longitudinal anomalies that caused minor changes in acceleration. Although the image-based monitoring system used in this research provided poor performance on its own, the severity of road-surface anomalies was accurately inferred using the specific range of the maximum variation of acceleration in the gravitational direction.

scholarly journals Which access to which assets for an effective liberalization of the railway sector?

2021 ◽  
pp. 178359172110123
Author(s):  
Patrice Bougette ◽  
Axel Gautier ◽  
Frédéric Marty
Keyword(s):  
Rolling Stock ◽  
Large Set ◽  
Rail Industry ◽  
Ex Ante ◽  
New Entrants ◽  
Complementary Assets ◽  
Favorable Conditions

In the European rail industry, to enable competition in the market, entrants should be granted access to a large set of complementary services, beyond access to the tracks. For an efficient and effective entry, temporary access to quasi-essential complementary assets like rolling stock, mechanical maintenance workshops, data, schedules, etc. is required. In the liberalized rail sector, several observed anticompetitive practices involve distorted access to these quasiessential facilities. Therefore, competition agencies must deal with litigation between the incumbent and new entrants. Most cases have been settled, resulting in commitments from the incumbent. We argue that such transitory and case-by-case remedies fail to produce favorable conditions for a secure and efficient entry. Thus, we propose to systematize such remedies through asymmetric and enduring ex-ante regulation.

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