Augmented Reality Based Smart City Services Using Secure IoT Infrastructure

Abstract

This paper presents an application of Augmented Reality (AR) within a smart city service to be deployed in the domain of public transport in the city of Novi Sad in Serbia. The described solution is focused on providing a simple and efficient method to citizens for accessing important information such as bus arrival times, bus routes and tourist landmarks using smart phones and AR technology. The AR information is triggered by image and geo-location markers and the data is provided via secure IoT infrastructure. The IoT infrastructure is based on bus-mounted IoT devices which utilize secure CoAP software protocol to transmit the data to the associated cloud servers. Description of the complete end-to-end solution is presented, providing the overall system set-up, user experience aspects and the security of the overall system, focusing on the lightweight encryption used within the low-powered IoT devices.

Full text

Augmented Reality based Smart City Services using Secure IoT Infrastructure
Boris Pokrić, Srđan Krčo, Maja Pokrić
DunavNET doo Novi Sad
Novi Sad, Serbia
e-mail: boris.pokric@dunavnet.eu, srdjan.krco@dunavnet.eu, maja.pokric@dunavnet.eu
Abstract— This paper presents an application of Augmented
Reality (AR) within a smart city service to be deployed in the
domain of public transport in the city of Novi Sad in Serbia.
The described solution is focused on providing a simple and
efficient method to citizens for accessing important
information such as bus arrival times, bus routes and tourist
landmarks using smartphones and AR technology. The AR
information is triggered by image and geo-location markers
and the data is provided via secure IoT infrastructure. The IoT
infrastructure is based on bus-mounted IoT devices which
utilize secure CoAP software protocol to transmit the data to
the associated cloud servers. Description of the complete end-
to-end solution is presented, providing the overall system set-
up, user experience aspects and the security of the overall
system, focusing on the lightweight encryption used within the
low-powered IoT devices.
Keywords- Augmented Reality, AR, Smart City, Smart
Transport, secure CoAP, secure IoT
I. INTRODUCTION
Today, more than 50% of people live in cities and UN
estimates that by year 2050 cities will be home to 70% of the
world's population. In order to accommodate such a large
number of people, cities would have to develop in a
sustainable fashion. Merely scaling up the existing resources
and services is neither physically possible nor economically
feasible. Instead, the services have to be automated, energy
efficient within existing infrastructure and information
acquired at different places in a city reused as much as
possible. Also, the expectations of citizens are high and they
increasingly expect more from the cities: to have better
quality of life, to have access to detailed information about
the city “health status” and to be able to influence various
aspects of city management, development and planning.
Being such a complex system, with people, businesses,
communities and city services interacting with each other,
the cities are increasingly relying on ICT for introduction of
new smart city services as well as upgrading existing ones.
Smart City ICT based services aim to provide wide spectrum
of solutions in different areas within the city such as
transport, public utility, public administration and health.
The solution presented in this paper focuses on providing
Augmented Reality (AR) powered smart transportation
services to the travelers aiming to increase the quality of the
public transport and at the same time offering benefits to
other stakeholders such as public transportation companies,
traffic authorities and city administrations.
II. AUGMENTED REALITY
AR technology is based on augmenting (supplementing)
the view of the real world with additional computer-
generated content such as images, videos, sound, GPS data
etc. The process of augmentation is triggered when AR
markers are detected, then appropriate AR content is
presented to the user based on the detected marker. The
markers can be in the form of pre-defined images which are
detected and tracked in a real-time using image processing
algorithms within the live video stream [1], [2], [3], [4].
Furthermore, the marker can be a certain GPS location and
orientation of the camera used for video stream capture. A
typical example is the wikitude app [5] which is used to
display additional information about restaurants, tourist
landmarks etc. in the user’s vicinity.
The AR technology was initially used for military,
industrial, and medical applications, but was soon applied in
the commercial and entertainment domains. According to
Gartner [6], AR is one of the top 10 strategic IT technologies
of our time. The technologies which AR encompasses are:
camera, location sensors, display and image processing
engine. Currently, the prominent devices supporting the AR
applications are the smartphones which have all the required
components integrated as well as the CPU, GPU and RAM
capable of executing demanding image processing
algorithms. Furthermore, application distribution channels
such as Google Play and iTunes enable fast and efficient
deployment of applications globally. Juniper Research [7]
forecasts $1.5 billion revenue by 2015 with more than 2.5
billion AR applications to be downloaded to smartphones per
annum by 2017. Furthermore, it is estimated that the AR
applications will generate $300 million in revenues globally
in 2013 and $1.5 billion by 2015. Recently, alternative
technological advances are being made in order to create
dedicated AR hardware such as Google Glasses which will
even further promote the AR applications and technology.
III. AUGMENTED REALITY IN SMART CITIES
Application of AR technology within the smart city
services and scenarios is not yet widely available. FP7

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Figure 2. User experience when using the AR smartphone application.
Further to the direct benefits to the travelers as described
above, the system will be able to extrapolate a number of
high-level services that will be used by different stakeholders
or dedicated system components:
 Current traffic conditions along specified routes
based on the information received from the fleet
management devices located on the public vehicles.
This parameter can be calculated from the
difference between current travel time of public
transport vehicles and expected, kalong certain
routes.
 Current demand of travelers for certain routes (and
for certain means of transport once the system is
extended to multimodal transportation). This is
calculated from the information received from the
smart-phone application where travelers specify
transportation route
 Expected arrival times of public transport vehicles
at certain location calculated from the current
location of vehicles and current traffic conditions
 Current location and activity of travelers
Top-level architecture of the proposed system is shown
in Figure 3 indicating the main components within the
traveler smartphone, cloud infrastructure and fleet
management devices. The architectural model conforms to
the generic Internet of Things (IoT) reference model such as
the one developed within the FP7 IoT-A initiative. This
model aims to create the architectural foundations of the
future IoT, allowing seamless integration of heterogeneous
IoT technologies (e.g. fleet management devices, mobile
phones) into a coherent architecture [13].
The smartphone AR application is implemented initially
on Android platform, but it will also be available for the iOS
in the future. The AR marker detection engine is based on
Qualcomm’s Vuforia SDK [14] which is used to process live
video stream acquired from the smartphone’s camera. The
SDK is integrated within the mobile application and used for
the detection of the AR marker, currently in the form of QR
code placed at the bus stop (see Figure 2). The AR SDK
provides information on frame-to-frame basis on which AR
marker is identified in the field of view and its location so
that appropriate AR content can be rendered. Furthermore,
since marker position is detected within every captured
frame, smooth tracking and resulting AR content overlay is
performed. Alternatively, the location-based marker can be
defined so that once the traveler is at the certain location
(and within specified radius), AR information is displayed.
Once the marker (image or location-based) is detected, an
appropriate UI is used to present all the information to the
user such as bus arrival times enabling the route selection
based on different criteria, tourist landmark browsing and
other functionality. Communication with the cloud
infrastructure, utilizing appropriate web services, is
performed using the communication engine. The security
aspects of the smartphone application such as user
authentication, encryption and decryption are implemented
through the security component.
Figure 3. Proposed system top-level architecture.
Cloud infrastructure contains all the core security
components (i.e. secure storage and security engine) and

these are described in more detail in the section below.
Communication engine is in charge of communication with
smartphone clients, fleet management devices and other
users of the system via secure channels. Access to the AR
content (i.e. bus arrival times, tourist landmark data) is
provided by the AR content engine. This component also
enables the public transport company and city authorities to
create dynamic AR content that can be presented to the
users. Component dedicated to bus arrival time and route
calculation is utilizing the data from the fleet management
devices and travelers routing plans respectively. Bus arrival
times are calculated using the real-time bus locations,
distance to the bus stop, current estimate of the traffic
conditions as well as previous knowledge about arrival times
at certain time of the day. In order to allow other users of the
system (i.e. city authorities, police) to access the cloud
infrastructure, web server and appropriate web applications
(web portals) are implemented and deployed.
The core component of the fleet management device is
the GPS/GPRS modem which is used to provide GPS
location and communication link to the GSM network
operator. The embedded microcontroller and flash memory
provide the limited processing capabilities which are used in
executing the program code. The security engine component
provides lightweight encryption and decryption algorithms in
order to ensure secure data transmission to the cloud
infrastructure via communication engine. All the data
processing, local storage, parsing and packing tasks are
performed within the data handling component.
V. SECURE IOT INFRASTRUCTURE
The proposed system generates and handles sensitive
data and therefore it is important to consider security
mechanisms that must be implemented within the IoT
platform. The sensitive data include travel plans specified by
the travelers, their location, bus location data generated by
the fleet management devices, and all the information and
data extrapolated from this data. Access to all this
information should be restricted to authorized users with
appropriate access mechanisms. Furthermore, transfer of the
data via communication channels must be done in a secure
way in order not to compromise privacy aspects of the
travelers as well as the security of the public transport
company infrastructure.
Since IoT solutions and architectures greatly differ in
implementation and the security requirements, there is a
number of studies addressing this issue such as [15], [16] and
[17]. As described, many existing security mechanisms for
the IT systems can be applied at different levels and for
different purposes within the IoT architectural stack, namely
protocol and network security, privacy, identity
management, trust and governance. Furthermore, different
layers of the IoT infrastructure require different types of
security mechanisms, for example web applications and data
storage within the cloud require one type of security whereas
the IoT devices might need different types of algorithms and
rules.
For the proposed system, a set of the security
mechanisms is being implemented to cover the three main
areas, namely:
 Secure storage within the cloud infrastructure
 Data privacy and access control mechanisms for
the users and IoT devices
 End-to-end communication from mobile and
web applications to the IoT devices across the
back-end cloud platform
Secure storage is very important aspect to consider when
dealing with sensitive data within distributed systems
including the IoT systems [18]. The generic architecture for
the secure storage consists of three main components: a data
processor (DP), that processes data before it is sent to the
cloud; a data verifier (DV), that checks whether the data in
the cloud has been tampered with; and a token generator
(TG), that generates tokens that enable the cloud storage
provider to retrieve segments of customer data; and a
credential generator that implements an access control policy
by issuing credentials to the various parties in the system
(these credentials will enable the parties to decrypt encrypted
data according to the policy). This generic architecture will
be instantiated within the proposed system focusing on the
efficiency of the cryptographic primitives due to the resource
restricted nature of the fleet management devices that will
implement parts of the cryptographic algorithm.
Data privacy and access control are interconnected and
very important issues to be considered in the proposed
system, and in the IoT in general [19]. The data generated by
the fleet management devices are owned by the public
transportation company and the access to this data should be
highly restricted only to authorized users. Furthermore,
citizens will be generating private data indicating the GPS
location as well as their travel plans. This data stored within
the cloud infrastructure should also be treated sensitive and
access to this data should not be made publicly available.
Furthermore, it should be prevented that any unauthorized
fleet management devices are connected to the system.
Therefore, it is necessary to establish access control policies
for both end users (citizens) and the IoT devices (i.e. fleet
management devices) connecting to the back-end cloud
platform. For the authorization and access control of citizens
and other users (e.g. administrators, transport company and
other stakeholders) it would be possible to use standard role-
based techniques already deployed within the standard
network infrastructure such as RADIUS, LDAP, IPSec,
Kerberos, SSH [20]. Using these techniques, the identity of
the user is established and then the access privileges are
determined based on the user’s role defined within the
overall eco-system. This technique relies on HTTP cookies
stored in a user’s browser after their identity has been
verified. However, for the IoT devices, role based access
control systems are not suitable as the identity of individual
device may not be known or may not be important.
Therefore, in this case, access control is typically based on
other criteria, such as location, proximity, and other
operational parameters [21]. Subsequently, the mechanism
that will be deployed within the proposed system is based on

attribute-based encryption (ABE) scheme for fine-grained
access control without a lengthy user authorization process
as described in [22]. In an ABE system, the keys and
ciphertexts are labeled with sets of descriptive attributes and
a particular key can decrypt a particular ciphertext only if
there is a match between the attributes of the ciphertext and
the key. In this way the sensitive (and encrypted) data can be
selectively shared at a fine-grained level allowing the multi-
level access to different users (in this case fleet management
devices) granting them associated access rights for only the
data (or parts of the system) they are allowed to use. This
technique will be adopted for the fleet management devices
and integrated within the overall security framework of the
platform.
End-to-end communication security ensures
confidentiality within the IoT system in order to provide
messages that are sent from the source to the destination to
be hidden from the intermediate entities (i.e. preventing
potential eavesdropping). Confidentiality within the IoT
system is implemented through suitable encryption and
decryption algorithms at different levels within the system’s
architectural stack. For the upper layers of the stack covering
the web and mobile applications, standard security
mechanisms are deployed, namely IPsec or SSL/TLS where
HTTP protocol is used. However, a particular challenge
when considering the security aspects within the lower layers
of the architectural IoT stack, where IoT devices are located,
is that they are often resource restricted devices with limited
battery life, memory, low communication bandwidth, low
CPU processing power etc. For these reasons, the main
communication protocol used for the communication
between IoT devices and back-end infrastructure is
connection-less UDP, instead of stream-oriented TCP. The
synchronous HTTP is designed for TCP and is not feasible
for use in the UDP-based IoT. Therefore, the Constrained
Application Protocol (CoAP), a subset of HTTP is being
standardized as a web protocol for the IoT [23]. To protect
the transmission of sensitive information, secure CoAP
mandates the use of datagram transport layer security
(DTLS) as the underlying security protocol for authenticated
and confidential communication. DTLS, however, was
originally designed for comparably powerful devices that are
interconnected via reliable, high-bandwidth links which is
often not the case. In order to address this issue, various
activities such as [24] leveraging the 6LoWPAN standard are
on-going in order to create light-weight security methods to
protect the CoAP-based communication. The proposed
system aims to implement searchable encryption method in
which the encrypted data is remotely stored in a distributed
system and the owner of such data is able to perform query
operations while maintaining the information confidentiality
and not allowing the access to the data to the external entities
[25], [26]. The core of the security system is the
cryptographic primitive which can be successfully scaled up
and down to provide variable level of protection at the
expense of using more or less resources (i.e. processing
power, memory, generated overhead). Such a primitive can
then be applied at the various levels within the proposed
system architectural stack, namely within the cloud
infrastructure and IoT devices. The ISO/IEC 29192
standards aim to provide lightweight cryptography for
constrained devices, including block and stream ciphers and
asymmetric mechanisms [27]. This method will be further
optimized in order to reduce the key size and make the
algorithm more efficient in terms of computational
requirements and still provide the satisfactory level of the
security. In particular the planned approach is to use the
curves with keylength between 32 and 64 bits as opposed to
typical 128 bits leading to the Short Elliptic Curves based
cryptosystem as shown in [28].
Furthermore, the method will be based on the
cryptographic primitive “signcryption” which
simultaneously fulfils the integrated function of public
encryption and digital signature with a computing and
communication cost significantly smaller than required by
the “signature-then-encryption” method [29].
VI. CONCLUSION
The work presented in this paper is focused on
implementation of novel smart city service within the public
transportation powered by the Augmented Reality (AR)
technology. The service will be deployed within the city of
Novi Sad in Serbia together with the local public
transportation company. Overall system is presented with the
focus on the security aspects to be addressed within the
system. Once the system is deployed, the plans are to
enhance it with the possibility to include purchase of the bus
tickets as well as to enable integrated ticketing system
covering the multi-modal transportation. This will include
payments for the rental bicycles, car parks, trams etc.
Furthermore, the application will enable routing calculation
using these additional modes of transport (i.e. bikes, cars and
trams).
ACKNOWLEDGMENT
Parts of the activities will be performed within the EU-
funded project Secure and sMArter ciTIes data management,
SMARTIE, Contract Number: CNECT-ICT-609061,
Area of Activity: Framework Programme 7, ICT Objective
1.4 IoT (Smart Cities), Period: 1st September 2013 - 31st
August 2016.
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