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Popular research projects on IoT devices in Qatar are illustrated below.
1) An Intelligent Car Monitoring system
is developed by Jabbar
et.al[6] in collaboration with Qatar Foundation and Qatar
University, for road safety and traffic control in Qatar. The model is based on the naturalistic driver behavior using existing traffic
monitoring systems. The authors have used Deep Learning and Neural
Networks to collect and analyze
data to provide dynamic
information
about
road
conditions, high and low risk
locations.
2) Context aware
name discovery for block chain based services in IoTs
was proposed by
Roberto Di et. al [7] from HBKU, to easily identify services in IoT devices using universal multi-layer blockchains. The model is
based on the existing protocols and uses publicly available information from one block chain to gather meaningful knowledge from
the environment.
3) A Survey on IoTs, Protocols and Applications
by M. Guizani et. al, Qatar University [8]. This work summarizes the
technologies, most relevant protocols, and security issues of Internet of Things (IoT). The fundamental concepts of architecture
and building blocks are made clear in the beginning to comprehend further deep understanding of protocols. The working of the
protocols at each layer is mentioned with graphs and clear
illustration. Higher technical terms are used in simple English for
the reader to gain insight into terminologies used in IoTs. The
paper has covered large details on the standard protocols
proposed by IETF, IEEE and EPCglobal. This article helps
student and researchers to understand key IoT characteristics
and elements without much effort to quick start new research in
emerging areas like big data analytics, cloud fog computing.
4) A comprehensive survey on application of Deep Learning
methods for IoT Security
: by Amr Mohamed et. al., Qatar
University [9]. The work explores the issues and challenges in
implementing the security measures, such as encryption,
authentication, access control, network security and application
security for the IoT devices. It highlights how intelligent
techniques can be used to enhance the security. The research
suggests that intelligent monitoring provides a significant
solution to new or zero-day attacks. ML/DL are the robust methods for data exploration, management and for learning ‘normal’ and
‘abnormal’ behavior of the network. The authors have enlisted all the recent work done in IoT security using ML/ DL,
providinglimitations and advantages of each method to trigger new direction of research and implementation of IOT security.
Figure 2 Intelligent Car Monitoring system
Figure 3 Hierarchical structure of
attributes.
Figure 4
Horizontal and Vertical market integration of IoTs