The Use of Internet of Things for Smart Cities
Jaime Lloret Mauri
Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politecnica de Valencia, Spain
Keywords: Internet of Things, Sensors, Smart Cities, Communication Protocols, Artificial Intelligence.
Abstract: This paper includes the information for the keynote speech of Jaime Lloret.
1 INTRODUCTION
Recent advances in new technologies jointly with
the appearance of low cost sensors with computing
and communication capacities have made possible to
implement new systems to improve citizens daylife.
Although the main constraints of Wireless Sensor
Networks are the power consumption and the
computing capacity (Sendra, 2011)(Azizi, 2016),
their flexibility and adaptability make them very
useful for any type of environment (Lloret,
2009)(Khaleeq, 2016). Data networks are evolving
towards the transport of large amounts of
information from sensor networks and the Internet of
Things (IoT). Through IoT, we can monitor and
control many sensors and devices, with the aim of
collecting information and acting on them. IoT
allows monitoring from everywhere at any time.
Technological advances, the implementation of
future fifth generation (5G) mobile networks and the
reduction of manufacturing costs of IoT devices
have boosted their use growth in a wide variety of
applications.
In order to build smart city, it is required three
basic components (see Figure 1):
• Sensors and (Wireless) Sensor Networks
• Communication Protocols and Algorithms
• Artificial Intelligence applied to Big Data
Figure 2 shows that sensors and internet of things
gather data from urban environments, so network
protocols, algorithms and architectures are required
to provide the most updated data in a big database.
The knowledge acquired by these sensors can be
tackled in order to improve the electric consumption,
the water wastage and even any type of lakes in gas,
electricity or water. Big data and artificial
intelligence techniques can be used to optimize the
resources of the cities and improve their
performance.
Figure 1: Basic IoT components to build a Smart City.
Lloret Mauri J.
The Use of Internet of Things for Smart Cities.
DOI: 10.5220/0007239600000000
In Proceedings of the 8th International Joint Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2018), pages 15-18
ISBN: 978-989-758-322-3
Copyright
c
 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Figure 2: Information exchange between basic elements when using IoT for smart Cities.
2 SENSORS AND (WIRELESS)
SENSOR NETWORKS
Along the years, the hardware technology to develop
sensors and wireless sensor networks have evolved
hugely. In about 10 years, sensor node deployments
with few KBytes of Flash Memory and just 11 Mbps
of data transfer rate (e.g. XPort and Matchport
(Martchport, 2018), from Lantronicx, Figure 3), to
some hundreds of Kbytes 5 years ago (e.g. Flyport
(Flyport, 2018) and Waspmote (Waspmote, 2018),
Figure 4).
Currently, Arduino (Arduino, 2018) and
raspberry Pi (Raspberry, 2018) platforms are
allowing a wide range of applications because of
their low cost, computing capacity, modularity, and
flexibility. Figure 5 shows Arduino Mega 2560 and
Raspberry Pi 3.
Figure 3: XPort and Matchport, from Lantronix.

Figure 4: Flyport and Waspmote (Libelium).
Figure 5: Arduino Mega 2560 and Raspberry Pi 3.
3 COMMUNICATION
PROTOCOLS AND
ALGORITHMS
In order to deliver the collected data from the
sensors to a database one or several communication
technologies are required. The connectivity from IoT
can be from anywhere at any time (Lopez, 2017).
Moreover, some specific protocols are needed for
data, message frequency and alarms. The choice of
the technology depends on multiple factors such as
the type of data, the field of deployment, economical
aspect, etc. The amount of protocols that can be used
is high. Moreover, it is increasing constantly. Some
of them are well known communication standards,
and others are proprietary and developed exclusively
for water or electricity metering. They provide two-
way communications with the IoT, allowing sending
commands from the database to the smart meter for
multiple purposes, including monitor real time
values and change the frequency of readings among
others (Lloret, 2016). Communication protocols for
IoT should allow the network management,
improving their ability to operate autonomously,
flexibly and robustly.
Given the information obtained through IoT, it is
necessary to classify and differentiate the flows with
the objective of offering an appropriate treatment to
the priority and the relevance of the information
managed. Moreover, IoT must face aspects related to
privacy and information security. Furthermore,
network infrastructures require mechanisms and
protocols to discriminate the different needs of IoT
data.
4 ARTIFICIAL INTELLIGENCE
APPLIED TO BIG DATA
The amount of data collected from a single
environment could be huge (Bakhshad et al, 2018).
There must be one or several databases deployed in
the smart city to facilitate the process of saving and
treating high volume of data. Once the data has been
saved in a database, it is very important to use the
most powerful techniques to extract the useful data
from it. Given a series of inputs the system has to be
able to detect certain circumstances that require any
type of intervention. Here is where artificial
intelligence (AI) is required. Techniques such as
artificial neural networks or inductive inference
methods, that are able to anticipate the future based
on past observed data, are used (Hernández et al.,
2014). Machine learning employs statistical
techniques with the goal of enabling machines to
understand the set of data. AI can be applied to a
wide variety of sensor data and environments.

Moreover, the traffic generated by the IoT
devices must be determined and integrated into
different types of flows. Based on this information,
there should be a prioritization criteria and traffic
safety levels corresponding to each flow in order to
be able to be properly treated by the network
devices. Machine learning / deep learning techniques
can be used to apply the traffic classification criteria.
AI algorithms can be responsible for determining the
required Quality of Service (QoS) parameters and
priorities in order to make modifications to the
network device configurations required at each
instant and for each type of specific traffic flow. An
example of an algorithm that takes into account the
aforementioned issues is shown in Figure 6.
Figure 6: Algorithm that takes into account sensor data
and traffic behavior to perform actions in the network.
5 CONCLUSIONS
The amount of technology introduced in the cities is
growing hugely. The sensor devices are cheaper,
smaller and with higher computing capacity, which
allow them to be used to gather data from a wide
variety of environments. Wireless technologies
allow higher data transfer rates at higher distances
and the communication protocols are quite more
robust than years ago. All these issues are
facilitating the deployment of many IoT devices to
collect the data used by AI techniques to achieve a
smarter city.
ACKNOWLEDGEMENTS
This work has been partially supported by the
"Ministerio de Economía y Competitividad" in the
"Programa Estatal de Fomento de la Investigación
Científica y Técnica de Excelencia, Subprograma
Estatal de Generación de Conocimiento" within the
project under Grant TIN2017-84802-C2-1-P.
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