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Technology development in the field of the Internet of Things (IoT) and more specifically in Low-Power Wide-Area Networks (LPWANs) has enabled a whole set of new applications in several fields of Intelligent Transportation Systems. Among all, smart-railways represents one of the most challenging scenarios, due to its wide geographical distribution and strict energy-awareness. This paper aims to provide an overview of the state-of-the-art in LPWAN, with a focus on intelligent transportation. This study is part of the RAILS (Roadmaps for Artificial Intelligence integration in the raiL Sector) research project, funded by the European Union under the Shift2Rail Joint Undertaking. As a first step to meet its objectives, RAILS surveys the current state of development of technology enablers for smart-railways considering possible technology transfer from other sectors. To that aim, IoT and LPWAN technologies appear as very promising for cost-effective remote surveillance, monitoring and control over large geographical areas, by collecting data for several sensing applications (e.g., predictive condition-based maintenance, security early warning and situation awareness, etc.) even in situations where power supply is limited (e.g., where solar panels are employed) or absent (e.g., installation on-board freight cars).
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Low-Power Wide-Area Networks in Intelligent Transportation:
Review and Opportunities for Smart-Railways*
Ruth Dirnfeld1, Francesco Flammini1,2, Stefano Marrone3, Roberto Nardone4, Valeria Vittorini3
Abstract— Technology development in the field of the Internet
of Things (IoT) and more specifically in Low-Power Wide-Area
Networks (LPWANs) has enabled a whole set of new applica-
tions in several fields of Intelligent Transportation Systems.
Among all, smart-railways represents one of the most chal-
lenging scenarios, due to its wide geographical distribution and
strict energy-awareness. This paper aims to provide an overview
of the state-of-the-art in LPWAN, with a focus on intelligent
transportation. This study is part of the RAILS (Roadmaps for
Artificial Intelligence integration in the raiL Sector) research
project, funded by the European Union under the Shift2Rail
Joint Undertaking. As a first step to meet its objectives,
RAILS surveys the current state of development of technology
enablers for smart-railways considering possible technology
transfer from other sectors. To that aim, IoT and LPWAN
technologies appear as very promising for cost-effective remote
surveillance, monitoring and control over large geographical
areas, by collecting data for several sensing applications (e.g.,
predictive condition-based maintenance, security early warning
and situation awareness, etc.) even in situations where power
supply is limited (e.g., where solar panels are employed) or
absent (e.g., installation on-board freight cars).
The Internet-of-Things paradigm embraces some of the
fastest-growing technologies today, with a huge expected
number of smart connected devices populating our homes,
cities and transportation systems in the next years.
According to CISCO, the term “Internet of Things” (IoT)
first appeared between the years 2008 and 2009 [1], however,
the term was first mentioned by Kevin Ashton in 1999 [2]
- meaning that many devices are connected to the Internet
and communicate each other. In general, IoT refers to the
networked interconnection of everyday objects, which are
often equipped with ubiquitous intelligence [3].
The connection between IoT and “intelligence” is not
obvious. However, it is a matter of fact that IoT devices
are increasingly “smart” and “autonomous” compared to
traditional devices (e.g., those used in sensor networks). Fur-
thermore, they allow to collect - by sensing and transmitting
- big amounts of data that can be processed both locally
(the so-called “edge computing”) and at different levels (e.g.,
“fog” level or “cloud” level) [4].
A “Thing” in the context of IoT, might be any object that
can be assigned an IP address with the ability to transfer data
*This work was supported by Shift2Rail JU under G.A. n. 881782
1R. Dirnfeld and F. Flammini are with Linnaeus University, V¨
2F. Flammini is also with M¨
alardalen University, V¨
as, Sweden
3S. Marrone and V. Vittorini are with University of Naples Federico II,
Naples, Italy
4R. Nardone is with University Mediterranea of Reggio Calabria, Reggio
Calabria, Italy
and interoperate within the existing Internet infrastructure.
This paradigm is considered as the evolution of the Internet
which can change the way we live, work and travel [5].
The IoT leads towards positive business results, helps
with creating new revenue opportunities and minimizing
operational costs by managing the connected devices. The
IHS forecasts that the number of IoT devices on the IoT
market will grow from an installed base of 15.4 billion in
2015 to 30.7 billion in 2020, and 75.4 billion in 2025, with
a potential economic impact of around $11.1 trillion a year
[2], [6] (Fig. 1).
Fig. 1. Forecasting of the IoT market growth up to 2020 [6]
In such a context, any research initiative addressing in-
telligent data processing should also address the enabling
IoT technologies for data sensing and data transmission. The
study presented in this paper is part of the RAILS research
project funded by the European Union under the Shift2Rail
Joint Undertaking [7]. RAILS takes up the challenge of
developing roadmaps for fast uptake of Artificial Intelli-
gence (A.I.) in the railway sector by identifying effective
and suitable techniques and testing methods for A.I. and
assessing impacts towards improving the overall performance
of the railway system. RAILS addresses the research areas
of rail safety and automation, smart maintenance and defect
detection, traffic planning and management. For each of
them, the first step is to develop a comprehensive and up-to-
date overview of relevant innovative technologies and trends
applicable to smart railways considering possible technology
transfer from other sectors. In particular, RAILS has to com-
bine A.I. with the IoT, in order to leverage on the big amount
of data generated by smart sensors and applications. In fact,
the vast amount of data generated by networked monitoring
devices need to be collected and interpreted to generate
useful information and knowledge. More specifically, in the
field of Intelligent Transportation Systems (ITSs), like smart-
railways, the focus should be on those IoT technologies
enabling long-range communication over large geographical
areas with low-power requirements allowing usage on track-
side remote sites with no connection to the power grid (e.g.,
railway track routes in desert areas) or unpowered vehicles,
like most rail freight cars [8].
This is the reason why among the many IoT technologies,
in this paper we focus on Low-Power Wide-Area Networks
(LPWANs) like LoRa [9]. LPWAN technologies appear
as very promising for cost-effective remote surveillance,
monitoring and control over large geographical areas, by
collecting data for several sensing applications (e.g., pre-
dictive condition-based maintenance, security early warning
and situation awareness, etc.) even in situations where power
supply is limited (e.g., where solar panels are employed)
or absent (e.g., installation on-board freight cars) [10]. In
details, this work studies the applications of LPWANs in
ITSs by performing a systematic literature review.
The rest of this paper is organized as follows. Section II
introduces LoRa technology and provides an overview of its
implementation in ITS. Section III provides a more detailed
and systematic review of the related literature addressing
LPWAN applications in ITS. Section IV summarizes the
main outcomes of the review, briefly discussing research
trends and applications to smart railways. Finally, Section
V draws some conclusions and pointers to future work.
In the last years, the connectivity of smart devices has
been dominated by short-range technologies. However, it is
predicted that the importance of LPWAN technologies will
grow as the IoT market evolves. In particular, it is predicted
that by 2025, 25% of wireless industrial IoT connections
will be provided by LPWAN technologies, such as LoRa,
Sigfox, narrowband IoT (NB-IoT), and LTE-M [9]. LoRa is a
rising technology for the transfer of data when implementing
networks for sensor data collection and transmission from
end nodes to base stations [11]. One of the main advantages
of LoRa is its long-range capability. A single base station
enables transmissions over hundreds of square kilometres,
however, the actual coverage is highly dependent on the
obstructions and environment [12]. Other benefits are low
power and high robustness towards narrowband noise inter-
Due to all these reasons, LPWAN technologies such
as LoRa are a great option for building Wireless Sensor
Networks (WSN) for intelligent transportation systems like
smart-railways. They are seen as enablers for intelligent
transportation because they allow cost-effective long-range
communications at a low bit rate among connected objects,
such as sensors operated on a battery, which are common
in many practical applications. Intelligent transportation has
been extensively studied in recent years to enable users
and travellers to be more informed and make safer, more
coordinated, and smarter use of transport networks. For an
example of LoRa technology, and how it improves trans-
portation systems and makes travelling smarter and more
convenient, the reader can refer to the article by P. Guan
et al. A Real-Time Bus Positioning System Based on LoRa
Technology [13].
As previously stated, the main objective of this work is
to perform a literature review on Low-Power Wide-Area
Network technologies for Intelligent Transportation Systems.
To that aim, the main research questions are:
Who has been working on this field, when and where?
What are the most relevant communication technolo-
What are the main implementations?
The search for related literature has followed the approach
known as systematic literature review (SLR) based on both
qualitative and quantitative analysis methods Article Collec-
tion, Data Collection, and Data Analysis [14] [15].
The article collection started by defining a search string
composed of the following search terms: “smart OR intel-
ligent”, “transport* OR transit”, “lora* OR lpwan”, with
the logical operator “AND” between them. Two reference
databases were used: the IEEE Xplore digital library and
the Scopus abstract and citation database1. Articles included
in the SLR have been selected when the mentioned search
terms appeared in their title, abstract, and keywords. We have
excluded articles which appeared multiple times in one or
both databases, those not written in English, those which
were not research articles, and finally, articles not focusing
on Low Power Wide Area Network Technologies relevant
for Intelligent Transportation Systems.
After the exclusion rounds, the full-texts of the remaining
articles were analyzed. The articles finally included in the
SLR had to satisfy at least one of the following criteria:
The article presented a review or a survey related
to LPWAN technologies for Intelligent Transportation
The article aimed to solve a specific problem related
to LPWAN technologies for Intelligent Transportation
Systems - with theoretical propositions.
The article aimed to solve a specific problem related
to LPWAN technologies for Intelligent Transportation
Systems - with experimental solutions/laboratory exper-
The article aimed to solve a specific problem related
to LPWAN technologies for Intelligent Transportation
Systems - with practical solutions or implementations.
From the graph in Fig. 2, it is clear that - as intuitively
expected - there have been very few related publications
on the subjects of LPWAN and ITS before the year 2015
1The extracted searches and the filtered list of papers are
publicly available at:
Low-Power- Wide-Area- Networks-Review.
(approximately, one relevant paper per year). Then, in 2016
the trend started to change, with rapid growth in 2018.
The affiliations of the 47 included articles cover 21
countries in all continents and demonstrate the worldwide
growing interest in LPWAN applications to ITS. In particular,
researchers from the USA have authored most articles, and
more specifically the 14.6% of all included articles. However,
when considering how many articles were published per
continent, we found that Asia has published most articles,
29.2%, followed by Europe, where 25% of all included
articles were published. North America has the third place
in this ranking with 14.6%, followed by Africa, where 6.3%
articles were published and South America with 2.1% of all
included articles. It can be noted that the biggest growth
of deployed LoRaWAN networks happened in Asia-Pacific
and in European regions [16], which explains why the most
published articles come from researchers operating in these
The 47 included articles were published by 50 authors
from 37 different institutions.The institutions can be divided
into three main categories: 24 universities, which make 65%
of all institutions that published articles; the second category
consists in research centres, which make up 24%; and the
third category are corporate companies, which account for
the remaining 4 articles or 11% of all institutions.
Fig. 2. Publication years of the included articles
A. Communication technologies
A total of 68 communication technologies were collected
from the 47 included articles about Low-Power Wide-Area
Network technologies for Intelligent Transportation Systems.
As shown in Fig. 3, more than half of all communication
technologies, specifically 58%, appeared in only two or fewer
articles. The remaining 42% of technologies appeared in
three or more articles. Furthermore, in Fig. 3 the identified
technologies are reported together with the numbers of
included articles. These articles enumerate, compare, propose
improvements or discuss these communication technologies.
The communication technologies can be classified into the
following groups:
Low-Power Wide-Area Network (LPWAN): The main
technologies in this group are LoRa, LoRaWAN,
DASH7, Narrowband IoT (NB-IoT) and Sigfox. These
are the main technologies which appear in 72% of
all included articles. More information on the different
technologies within the group of Low Power Wide-Area
Networks can be found in [17].
Wireless Personal Area Network (WPAN): This group
includes the Wireless Sensor Network Technology
which appeared among the collection, namely ZigBee.
Wireless Local Area Network (WLAN): The most men-
tioned technologies within this group are Wi-Fi and
Bluetooth. When considering Bluetooth, the most men-
tioned technology was Bluetooth Low Energy (BLE)
and Bluetooth Low Energy Protocol.
Cellular Network: This group of technologies has the
advantage of wide coverage and suitable bandwidth,
especially the 5G. Widespread technologies for the Cel-
lular Network group are: 3G, 4G, Long Term Evolution
(LTE) and GSM-GPRS. More information on the fifth
generation of mobile communication (5G) can be read
in the work [18].
Satellite Network: The most relevant technology for
this group according to the collected literature is GPS,
although several other emerging technologies and posi-
tioning systems are expected in the next few years.
Messaging: The main messaging technology from all
included articles is the Message Queue Telemetry Trans-
port (MQTT), included in a total of 5 articles. The
advantage of MQTT is that it is a lightweight publish-
subscribe protocol and more on this topic can be found
in [19]. One article mentions also ALOHA [13], which
is a random-access protocol and operates at the datalink
Modulation Technology: Among the collected technolo-
gies, the most mentioned techniques used for transmis-
sion of data are Amplitude-shift keying (ASK) and the
narrowband BPSK modulation, which is the simplest
form of phase-shift keying (PSK).
Fig. 3. Main communication technologies
B. Implementations
An important purpose of this review on LPWAN for ITS
is to highlight research and experiments that have been
implemented in real-life environments. Most of the included
articles address implementation proposals, while only a mi-
nority actually addresses prototyping in real-world scenarios.
The following articles were found, which are explicitly
focused on LPWAN for ITS, and which not only suggest
improvements or implementations but actually perform ex-
periments with implementations in real-world environments:
A popular category addressing implementation is bus
tracking, monitoring, or localization systems using Lo-
RaWAN. Three articles [13] [20] [21] address spe-
cific implementations and perform experiments on this
subject. The first article [20] LoRaWAN based GPS
tracking of city-buses for smart public transport sys-
tem argues that making the available city-bus system
smarter by tracking, would make the public vehicles
more accessible. The paper details building a custom
gateway and server, which is beneficial since it provides
flexibility in designing the network parameters. The
authors of this paper built a prototype of their GPS
tracking system based on LoRa and performed tests with
it. The conclusion of the tests is that the tracking system
can be implemented in a real-life environment. The
second article [21] IoT-based Bus Location System Us-
ing LoRaWAN introduces a system that should improve
the service quality of the bus network. Furthermore,
the authors claim to improve the efficiency of the
operation management. In this paper, the authors also
built a prototype system and performed tests with it.
The results of the tests confirmed that the system can
be implemented in a real-life environment at a lower
cost than the existing bus location systems using cellular
networks such as 3G/LTE. In the third article, [13]
A Real-Time Bus Positioning System Based on LoRa
Technology, the authors build as well a real-time bus
locating system based on LoRa technology. The authors
here used for the implementation of communication
the ALOHA protocol, which solves packet conflict
problems. Furthermore, a prototype was built and tested
and results in reduced power consumption, a more
reliable hardware system, low loss rate and an overall
lower cost. In [22] the authors propose similarly an IoT-
based public vehicle tracking system using LoRa and
ITS services, experiments were designed and executed
to adjust the parameters of the LoRa technology. The
results conclude that an implementation is suitable for
intermediate cities. The authors also found that the
relevant technical aspects which need to be taken into
account are an adequate LoS between the gateway
and the devices in the vehicles. Thus, the number of
obstacles between the roads and the gateway should be
as small as possible.
A similar category as the previous one is the tracking,
monitoring and location systems for boats. One article
addressing this topic is [23]. Maritime communication
is challenging due to the lack of supporting long-range
connectivity with the land. The general solution for
communication in high seas are satellite links, which
is rather expensive. There are solutions for areas closer
to the shore, where monitoring systems have been
implemented with cellular communication or wireless
sensor networks. However, these solutions have certain
drawbacks, and thus Sanchez-Iborra et al. [23] present a
tracking and monitoring system based on LoRa. The tar-
get group here are small sailboats, recreational boats and
radio control ships. The monitoring in their work was
performed on real-training sessions of Optimist Class
sailboats. The works [13], [22], [23] were financially
supported and thus there is a higher probability to be
further supported and having a possible future in being
The previous Section reviewed the current literature on
LPWAN mainly focusing on communication and imple-
mentation issues. Here below all the analysed papers are
reported in Table I, with the aim of providing a quick sight
before discussing the review results, the research trends and
applications to smart railways. The paper is grouped into
sections according to their main scientific focus (architecture,
middleware, protocols and surveys), application domain (ITS
- general, rail transport, air transport, etc,).
A. Related Surveys
Among the reviewed papers, it is worth mentioning two
references that can be classified as literature or technology
review articles, i.e., the work in [17] entitled Internet of
Mobile Things: Overview of LoRaWAN, DASH7, and NB-
IoT in LPWANs Standards and Supported Mobility and the
work in [30] entitled Internet of Things (IoT) communication
protocols: Review, belongs to the category of reviews. In
particular the survey article [17] addresses the mobility of
the things, how it can be achieved when transmitting and
receiving data, and the connectivity in LoRaWAN, DASH7,
and NB-IoT. Furthermore, the authors provide a general
and technical comparison of the three mentioned standards
and show various application scenarios where the mobility
is required. The authors also illustrate how to select the
most suitable standard and discuss the research challenges
and perspectives. The review article [30] reviews the fol-
lowing IoT communication protocols: 6LoWPAN, ZigBee,
Bluetooth LE, RFID, NFC, Sigfox, Cellular and Z-Wave.
The authors detail the specifications and benefits of these
communication protocols and conclude that it is difficult to
define which one is the best. Therefore, the authors discuss
that it is important to ask the questions “which technology
is best suitable for a specific application”.
The two research articles focus on the Internet-of-Things
and mention Low Power Wide Area Networks. However,
in the present literature, it was found that there is a lack
of a formal and objective systematic review that is focused
specifically on LPWAN for ITS, while all references col-
lected in the present review address analyses from multiple
perspectives on this specific topic.
B. Research Trends
From this literature review, it is clear that there has been
an increasing attention on LPWAN for ITS from all over
LPWAN Revised Papers
Application Domain Architectures Middleware Protocols Survey
ITS - general [24]–[26] [27] [19], [28], [29] [11], [17], [30]
Rail Transport [31] [32] - -
Air Transport - [33], [34] - -
Road Transport [35]–[37] [13], [20]–[22], [38]–[45] [46], [47] -
Water Transport - [23], [48]–[50] - -
Smart Infrastructure [51]–[53] [54]–[56] [57], [58] -
Waste Management [59] - - -
Agricultural Industry [60] [61] [62] -
the world in the last few years. The interest comes from
not only universities and research centres but also from
companies as well as private research institutions in all
continents. Furthermore, Fig. 2 shows that there is a fast-
growing number of contributions and implementations in the
field of LPWAN for ITS. In the same Figure, it is also visible
that the number of articles grew by a factor of over 400%
after 2017.
The data analysis answering research question number 2 il-
lustrates the different communication technologies addressed
by the included articles. The research and experimentation on
different communication technologies are particularly impor-
tant. For example, in article [13] the authors use the ALOHA
protocol for the implementation of bus communications,
which solved packet conflict problems; however, the results
provided in that paper also indicate that if the transmission
distance was higher than 1.8km, the packet loss rate also
increased. Thus, in general, it is essential to find the most
appropriate trade-off considering the performance, reliability
and coverage requirements in the operating conditions of any
specific ITS application. That consideration offers space for
further research in these areas.
The data analysis for research question number 3 identified
only 5 articles, which account for approximately 10% of all
included articles, that present implementations and exper-
iments in a real-life environment. Moreover, all 5 articles
focus on tracking, monitoring, or localization systems using
LoRaWAN. Four articles, i.e., references [13] [20], [21]
and [22], suggest individual implementations and perform
experiments on tracking public transportation vehicles, such
as busses. The fifth article [23] monitors lightweight boats.
In all cases, the main focus area for the researchers who
implemented systems and performed related experiments was
C. Applications to Smart-Railways
As mentioned, the literature review provided in this pa-
per represents a preliminary study for the RAILS research
project, focusing on AI applications in railways in the three
main areas of: driverless, autonomous and cooperative driv-
ing; smart-maintenance and defect detection; and advanced
traffic management [7]. It is rather intuitive that results
achieved in other transportation fields might be transferred
to railways wherever the operating conditions are similar. In
particular, the aforementioned ongoing experimentations in
public transportation (e.g., connected busses) and maritime
applications (e.g., connected boats) may prove useful for a
comparison of operating conditions, expected issues for long
distances, power requirements, etc. For instance, it should be
noted that the limitations emerged when monitoring buses
over distances longer than typical urban areas might affect
railways where distances are typically longer than a few
kilometres unless more gateways are installed along the
lines, as it happens nowadays with GSM-R base transceiver
stations used in ERTMS/ETCS (European Railway Traffic
Management System / European Train Control System) [63].
Although that cannot be considered a mature field based on
the results of this review, we expect a growth of research
and applications in the automotive field with the increasing
interest in connected cars. The results, in that case, might be
more easily transferred to railways considering the analogy
between highways and railways in terms of distances and
longitudinal distribution.
Regarding the most promising railway applications of LP-
WAN technologies, we already mentioned remote monitoring
and surveillance as the main application [64] [65]; however,
depending on performability, vehicle-to-vehicle (i.e., train-
to-train) communications might also be considered as a
promising field of experimentation for cooperative driving
and virtual coupling [66] [67] [68]. While LPWAN monitor-
ing applications in ITS are cross-domain to a certain extent,
there are some considerations that are domain dependant,
e.g., harsh environmental conditions requiring ruggedized
hardware, or possible presence of strong electromagnetic in-
terference in the proximity of high-voltage catenary contacts
in railways [69]. Furthermore, device and data security as-
pects are critical when transporting safety-critical signalling
information, that is important if LPWAN technologies are
used to support autonomous and cooperative driving in ap-
plications related to ATC (Automatic Train Control), which
is a combination of Automatic Train Protection (ATP) plus
Automatic Train Operation (ATO), ATS (Automatic Train
Supervision), CBTC (Communication Based Train Control),
as well as computer-based interlocking systems (IXL) [70].
However, it is worth mentioning that modern railway stan-
dards like ERTMS/ETCS already and successfully addressed
the issue of transmitting safety-critical data over possible
unreliable and insecure networks (i.e., open/wireless data
networks like the existing GSM-R) by means of specific pro-
tocols (e.g., Euroradio) ensuring data integrity and security
at the application level of the ISO/OSI protocol stack [63]
[71] [72] [73].
The objective of this paper was to provide a brief literature
review with a focus on Low Power Wide Area Network Tech-
nologies applicable to Intelligent Transportation Systems.
This work is to be considered within the scope of the RAILS
research project funded by the European Union through the
Shift2Rail Joint Undertaking, considering that the IoT and in
particular LPWANs represent essential enabling technologies
for sensor data collection and distributed control over large
geographical areas in future generation smart-railways. We
believe that the preliminary literature review provided in
this paper constitutes a first step towards the analysis of
transferability and the definition of roadmaps for the imple-
mentation of intelligent railways. We plan to further extend
and update the present SLR as a result of the ongoing RAILS
project activities of state-of-the-art definition and technology
roadmapping planned for the next years.
This work has received funding from the Shift2Rail Joint
Undertaking (JU) under grant agreement No 881782. The JU
receives support from the European Union’s Horizon 2020
research and innovation programme and the Shift2Rail JU
members other than the Union. The information and views
set out in this document are those of the authors and do
not necessarily reflect the official opinion of Shift2Rail Joint
Undertaking. The JU does not guarantee the accuracy of the
data included in this article. Neither the JU nor any person
acting on the JU’s behalf may be held responsible for the use
which may be made of the information contained therein.
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... The authors introduced a new network architecture to improve the efficiency of radio access technologies in the railway field conditions. Dirnfeld et al. (2020) discussed Low-Power Wide-Area Networks (LPWAN) with a specific emphasis on smart railways. It was underlined that both IoT and LPWAN would be very promising technologies for cost-effective remote monitoring, surveillance, and control over large geographical areas even in case of situations where the power supply is restricted. ...
... The authors introduced a new network architecture to improve the efficiency of radio access technologies in the railway field conditions. 26 Dirnfeld et al. (2020) Investigate the LPWAN potential for smart railways. ...
Full-text available
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.
... can cover vehicle speed, traffic flow, road occupancy rate, and vehicle type. Every link matters for timely and effective data collection, transmission, processing, and forecast [3]- [5]. The first link will be traffic data collection, against which multiple models and systems are available. ...
... In the vehicle positioning problem, the loss function of the network is modified to the Euclidean distance function. Assuming that there are multi-class problems in class C, and the number of contained training samples is N, the loss function can be expressed in Eq. (5). In Eq. (5), t n k refers to the k th dimension of the label according to the n th sample, and y n k denotes the k th output according to the n th sample in the network output. ...
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In implementing the Intelligent Traffic Monitoring System (ITMS), timely and effective access to road traffic information is an essential link. It requires an effective traffic Information Acquisition System (IAS) to collect real-time data and transmit the collected information to the background for processing. Therefore, this paper studies on-road vehicle information recognition based on Deep Learning (DL). Firstly, a framework of traffic IAS is proposed. Then, an improved MT-GooGleNet model based on Convolutional Neural Network (CNN) is proposed to locate and recognize vehicles in traffic images. Finally, the performance of the model is analyzed by simulation. The experimental results of vehicle position recognition show that the classification accuracy of Multi-Task (MT)-GooGleNet after fine-tuning is 99.5%. Compared with other models, the MT-GooGleNet model proposed is the best in vehicle position recognition, and its positioning accuracy is very high. The results of vehicle identification show that after data enhancement and pre-training, the testing set accuracy of the MT-GooGleNet model is 79.96%. The results show that the model’s accuracy has been dramatically improved after processing. The research provides a reference for establishing IAS in the future.
... In similar research [5], smartphones are used for the detection of road bumps, speed breakers, and potholes. Finally, recent surveys on Low-Power Wide-Area Networks applications in ITS and on advances in mobile networking for IoT are provided in references [6] and [1] respectively. ...
... Using the BUS, roaming transport vehicles can access the collected data processed by the AI module at the core of the system (6). The role of the AI module is the analyses of collected data, using techniques such as neural networks, deep learning, etc., in order to propose the fastest, safest, and optimal routes to the drivers. ...
... In this section we provide a brief overview of relevant paradigms and technologies enabling ITC. Since a multitude of disciplines and research areas are connected to ITC, we will focus on those who are mainly connected with AI such as artificial vision and information fusion, rather than surveying all enabling communication and networking paradigms such as IoT and 5G (see, e.g., references [5] and [16]). ...
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The progressive adoption of artificial intelligence and advanced communication technologies within railway control and automation has brought up a huge potential in terms of optimisation, learning and adaptation, due to the so-called “self-x” capabilities; however, it has also raised several dependability concerns due to the lack of measurable trust that is needed for certification purposes. In this paper, we provide a vision of future train control that builds upon existing automatic train operation, protection, and supervision paradigms. We will define the basic concepts for autonomous driving in digital railways, and summarise its feasibility in terms of challenges and opportunities, including explainability, autonomic computing, and digital twins. Due to the clear architectural distinction, automatic train protection can act as a safety envelope for intelligent operation to optimise energy, comfort, and capacity, while intelligent protection based on signal recognition and obstacle detection can improve safety through advanced driving assistance.
... The development of technologies related to the Internet of Things (IoT) paradigm, especially Low-Power Wide-Area Networks (LPWANs) protocols, has enabled a whole set of monitoring applications. Commercially available LPWAN technologies, like LoRA, are promising for implementing Wireless Sensor Networks (WSN) for remote rail assets monitoring applications [3]. However, the low-power consumption characteristic of LP-WAN is partly due to their communication protocol with short messages and the fact that these do not need to be transmitted constantly. ...
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The digitalisation of freight rail is an essential improvement to create modern functions that offer a cost-effective, attractive service and improved operational opportunities to operators. These modern functions need intelligence, detection, actuation and communications. For this, generally, it is possible to process raw data in the Edge and send meaningful data over a communication link. However, the power supply is not granted in a freight wagon and so low power strategies need to be adopted. This paper presents the implementation and testing of a wireless connected heterogeneous multiprocessing architecture. From the power consumption point of view, this system has been stressed by means of a generic FFT function to evaluate the different on-board computing devices that have been decided. From the communication point of view, the LPWAN LoRa technology has been tested and validated on robustness and coverage. Thanks to the heterogeneous nature of this architecture and its configurability, it allows us to propose the most suitable computing ressources, data analysis and communication strategy in terms of efficiency and performance for the functions that this wagon on board unit needs to host and support. With this approach, operation data are reported to the centralised freight driver assistant system.
... In this section we provide a brief overview of relevant paradigms and technologies enabling ITC. Since a multitude of disciplines and research areas are connected to ITC, we will focus on those who are mainly connected with AI such as artificial vision and information fusion, rather than surveying all enabling communication and networking paradigms such as IoT and 5G (see, e.g., references [6] and [17]). ...
Preprint accepted for publication in the proceedings of "The 4th International Conference on Reliability, Safety and Security of Railway Systems" (RSSRail'22). Please cite as: Francesco Flammini, Lorenzo De Donato, Alessandro Fantechi, Valeria Vittorini. A Vision of Intelligent Train Control. Proc. 4th International Conference on Reliability, Safety and Security of Railway Systems (RSSRail’22).
... The caused problems by increased traffic can be divided into three categories: traffic congestion (delay and fuel prices increment), safety (accidents and emergencies), and pollution (air pollution increment) [115]. IoT development has become a new opportunity for the elimination of transportation problems by introducing smart transportation [116]. Smart transportation develops a wide variety of sensors to gather information about the roads, vehicles, and drivers. ...
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Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.
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Detecting anomalies in computer-based systems, including Cyber-Physical Systems (CPS), has attracted a large interest recently. Behavioral anomalies represent deviations from what is regarded to as the nominal expected behavior of the system. Both Process Science and Data Science can yield satisfactory results in detecting behavioral anomalies. Within Process Mining, Conformance Checking addresses data retrieval and the connection of data to behavioral models with the aim to detect behavioral anomalies. Nowadays, computer-based systems are increasingly complex and require appropriate validation, monitoring and maintenance techniques. Within complex computer-based systems, European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) represents the specification of a standard Railway System integrating heterogeneous hardware and software components, with the aim of providing international interoperability with trains seemingly interacting within standardized infrastructures. Compliance to the standard as well as expected behavior is essential, considering the criticality of the system in terms of performance, avail-ii Run-time Anomaly Detection with Process Mining ability and safety. To that aim, a Process Mining Conformance Checking process can be employed to validate the requirements through run-time model-checking techniques against design-time process models. A Process Mining Conformance Checking methodology has been developed and applied with the goal of validating the behavior exposed by an ERTMS/ETCS system during execution of specific scenarios. The methodology has been tested and demonstrated correct classification of valid behaviors exposed by the ERTMS/ETCS system prototype. Results also showed that the Fitness metric developed in the methodology allows the classification of the anomalies based on their severity and physical localization.
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Nowadays, data mining is widely used to mine business information and make them very strategic for decision. Many data mining techniques can be according to the large variety of datasets. Our paper aims to optimize the prediction of telemarketing target calls for selling bank long-term deposits in smart cities using improved KNN model. The dataset used come from Portuguese retail bank which addressed from 2008 until 2013, data on its clients, products and social-economic attributes not without ignoring the effects of the financial crisis. From original set of 150 features which has been explored, only 20 realistic features which are known before the call are retained for this work including label. We use optimized KNN algorithm which is one of the simplest data mining techniques based on similarity that are used for prediction. To optimize its performance and to accelerate its process, we propose speeded KNN algorithm based on preprocessing and significant attributes filtering and normalization. It also includes another improvement based on variation of neighbors (k) and similarity model which insures a more accurate classification. Thus, the contributions of this paper are three-fold: (i) introduce high preprocessing method separately each type of features and imputation of missing values of attributes; the automation of features normalization (ii) the selection of realistic and most significant attributes which are known before the call, and (iii) the combination of optimal k and similarity models which gives the best performances. Our approach largely improve the performance of other algorithms used, with average more than 96.91% of f1-measure and vary reduced time processing.
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Internet of Things (IoT) low power and long range wireless technologies play a key role as an enabling technology for the development of the communication backbone for future smart cities, which will be increasingly based on multi-sensor intelligent data analytics. At the current state-of-the-art, a number of technologies collectively known as Low Power Wide Area Networks (LPWANs) can provide connectivity for IoT applications. Among LPWAN technologies, Long Range Wide Area Network (LoRaWAN) has been effectively used in a wide range of application domains. An important factor that accelerates the process of LoRaWAN implementation in IoT systems is the use of LoRaWAN simulation tools. Most simulation tools are widely used to simulate various networking technologies. As for LoRaWAN, their focus is on simulation of PHY and MAC layers. In this chapter, we address the possible use of virtualization technologies to simulate LoRaWAN at the application layer. Virtual network laboratories based on virtual technologies have existed for over a decade. These laboratories have been used for the purpose of educational and test environments. This chapter presents a novel model based on virtualization technology for the design, development and testing of the application for roaming in LoRaWAN networks in the context of future smart cities to enable continuous intelligent infrastructure monitoring and surveillance using moving devices such as those wearables or installed on-board vehicles and drones. The virtual network and its architecture for the simulation of LoRaWAN applications are presented in this chapter together with example use case scenarios.
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In view of developing smart cities, all the infrastructure of the city should be integrated with intelligent system. Transportation is one of the main constraints to the development of cities. Roads maintenance is one of the key factors for transportation system. In developing countries due to the increased vehicular population the maintenance becoming a complex task. Here we propose a system which detects potholes and humps on roads and send the information to higher authorities using LoRa technology. We designed a system with three modules like user module, gateway module and cloud module. User module includes an ultrasonic sensor and Lora GPS shield which should be deployed on vehicles. Through sensor we can detect the pothole and humps on roads, Lora GPS will capture the location and the information will be sent to the gateway using LoRa communication. Gateway can be anywhere in the range of 15km as LoRa module can send the information throughout this range. This information is uploaded to cloud which will be available for higher authorities to repair and maintain the roads effectively.
Full-text available
Systems trying to solve mobility issues in cities, such as high levels of accidents and traffic congestion, have been developed worldwide. Intelligent Transportation Systems (ITS) services focused on urban public transport are an option contributing to solve such issues. A few intermediate cities in the Latin American context have developed some of these ITS services, which are mainly based on a tracking system for public transport vehicles. Such tracking systems have great limitations in terms of coverage, availability, and operational cost. In addition, they are commonly isolated mobility solutions, which cannot be easily integrated with other mobility services in the city because they are not based on an ITS architecture. In order to improve public transportation systems in intermediate cities, we proposed the development of an IoT-based public vehicle tracking system, using LoRa (Long Range) and ITS services. In this research, we developed the proposed system as a proof of concept. We designed and executed some experiments, in order to adjust parameters of the LoRa technology and to test its operation. This article presents the methods we followed for developing the proof-of-concept model, a description of the experiments, and their results. The results lead to conclude that the LoRa technology and an IoT-based system are adequate for implementation of a mobility service such as the one we propose, once important technical restrictions related mainly to Line of Sight (LoS) are considered. Key aspects for implementation were also identified for deploying the service (as a prototype) in the city of Popayán .
Conference Paper
Full-text available
The Internet of Things (IoT) is poised to revolutionize how people, industries, and enterprises connect to customers and individuals. Network Protocols, Technology and Standards such as Narrowband IoT (NB-IoT), LTE-M, 5G, LoRaWAN, Message Queue Telemetry Transport (MQTT), Constrained Application Protocol (CoAP), Device management such as Open Mobile Alliance (OMA) for Machine to Machine (M2M) are being developed to support a variety of IoT applications and services. IoT ecosystem is creating tremendous business opportunities and opening the doors for innovation. With the explosive growth of connected devices, approximately five quintillion bytes of data is estimated to be generated by the Internet every day. Not all these connections and ecosystems are secure; the security vulnerabilities are steadily increasing in parallel due to the lack of secure updating mechanisms especially for IoT ecosystem. This paper proposes three different models using the CoAP and MQTT application protocol, which aims at providing efficient mechanisms and methods for Over the Air delivery of Software Updates and Security Patches to IoT devices and evaluates which protocol is better suited for proposed models and applications.
This paper proposes for the first time the use of an Internet of Things solution for the accurate recovery of incapacitated commercial and retail delivery drones. Since the use of drones will increase in popularity for a variety of uses, the problem of locating and recovering delivery drones is necessary. Using the emerging LoRaWAN and Sigfox networks (as examples of Low Power Wide Area Network (LPWAN) technology), we investigate the opportunity to locate and recover delivery drones that have crashed either due to technical issues or outside malign intervention. Location and recovery of a test drone using LoRa technology was trialed over three distinct terrains (urban, suburban, and rural) at five different sites in each terrain. These 15 trials evaluate ease of recovery on arrival at the crash site, accuracy of location coordinates given, and a subsequent analysis of the channel statistics for the LoRa network. The experiment was repeated using the Sigfox network as a comparison. The drone was able to be recovered at 14 of the 15 tests sites for both LoRa and Sigfox; in every case the drone's location was successfully transmitted to the secure server via the LPWAN networks. The paper investigates the reported location accuracy from the drone and also uses RMSE as an accuracy metric. The paper furthermore divulges lessons learned and presents a drone recovery algorithm.
Conference Paper
This paper represents an overview on activities done in real Smart Cities scenarios using IoT Technologies for Intelligent Transportation Systems (ITS). Nowadays, there are several use cases related to IoT for ITS, such as connected and autonomous vehicles, cooperative transportation networks and smart roads in order to improve data propagation, create heterogeneous connectivity and low latency applications in high capacity environments. ITS techniques can be also applied on logistics, so accuracy on delivery and timing can be improved consider all the involved ecosystems, baseline and standardized architectures in interconnected Smart Cities for future development and integration. Secure correlations between vehicles and smart roads can optimize road safety and traffic flow, reduce incidents, avoid congestions etc. These technologies comprise also V2X (Vehicle to Everything). In this scenario, the cloud-based LoRa (Long Range) and mesh networks technologies, can play an important role for the propagation of intelligent sensed data and localization. The Smart Roads scenario is considered as one of the most attractive field in a Smart City environment. The right choice on technology, delay and frequency represents an important factor to be considered for standardization and engineering activities.