Smart City Challenges and Problems: Resource Wastage in Cloud Domain
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This report delves into the challenges of resource wastage in smart cities, particularly concerning cloud computing and big data applications. It explores the increasing adoption of smart city concepts globally, highlighting the need for efficient resource management. The report provides an overview of the problem and its domain, followed by a literature review of relevant research papers. It then presents a revised problem statement, outlining project requirements and methodologies. A proposed solution for resource management using IoT is also discussed, along with supporting graphs. The report emphasizes the importance of addressing issues such as data management and the efficient use of resources within the context of smart city development. The core of the report focuses on how to mitigate the issues and challenges of resource wastage in cloud domain and big data application specifically in the field of smart city design and development. The secondary research method is applied for collecting information throughout the paper.

Running head: SMART CITY CHALLENGES AND PROBLEMS
Smart City Challenges and Problems: Resource Wastage in cloud domain and big data
challenges
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Smart City Challenges and Problems: Resource Wastage in cloud domain and big data
challenges
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1Smart City Challenges and ProblemsSmart City Challenges and Problems
Abstract
This paper depicts the challenges associated to the resources for bid data and cloud based
applications. The exponential growth if technology is converting the daily life style of the living
creatures. Future levels of different upholdments are associated to the smart city application. The
key of the technology that may interrupt the project success are illustrated in this paper. In other
hand, in order to conduct the research the methodology details that have to be followed are also
elaborated in this paper.
Abstract
This paper depicts the challenges associated to the resources for bid data and cloud based
applications. The exponential growth if technology is converting the daily life style of the living
creatures. Future levels of different upholdments are associated to the smart city application. The
key of the technology that may interrupt the project success are illustrated in this paper. In other
hand, in order to conduct the research the methodology details that have to be followed are also
elaborated in this paper.

2Smart City Challenges and ProblemsSmart City Challenges and Problems
Table of Contents
1. Introduction......................................................................................................................3
1.1 Introduction to the problem and domain...................................................................3
1.2 Structure of the report................................................................................................3
1.3 Background................................................................................................................4
2. Literature review..............................................................................................................5
3. Revised problem statement............................................................................................11
3.1 Requirements of the project.....................................................................................11
4. Methodologies...............................................................................................................13
4.1 Explanation of techniques used in past and present................................................13
4.2 Comparison of the techniques.................................................................................15
5. Proposed solution...........................................................................................................16
5.1 Explanation of technology suits the IoT application...............................................16
5.2 Graphs to support justification and arguments........................................................18
References..........................................................................................................................22
Table of Contents
1. Introduction......................................................................................................................3
1.1 Introduction to the problem and domain...................................................................3
1.2 Structure of the report................................................................................................3
1.3 Background................................................................................................................4
2. Literature review..............................................................................................................5
3. Revised problem statement............................................................................................11
3.1 Requirements of the project.....................................................................................11
4. Methodologies...............................................................................................................13
4.1 Explanation of techniques used in past and present................................................13
4.2 Comparison of the techniques.................................................................................15
5. Proposed solution...........................................................................................................16
5.1 Explanation of technology suits the IoT application...............................................16
5.2 Graphs to support justification and arguments........................................................18
References..........................................................................................................................22

3Smart City Challenges and ProblemsSmart City Challenges and Problems
1. Introduction
1.1 Introduction to the problem and domain
Since few years the concept and application smart city is grabbing the attention of the
consumers. Though, this application is costly and advanced as well but still certain challenges
are associated to it that are to be eliminated soon for the successful implementation of the smart
city. In most of the cases the combination between the automation, architecture, infrastructure
and environment are not properly formed as a result the entire process become costlier and time
consuming at the same time. From technical and privacy point of perspectives certain issues and
challenges are always identified related to smart city application. Resource management has
been identified as the main issue of cloud technology application in smart city. As cloud allows
huge storage thus data management always come up as a major challenge.
1.2 Structure of the report
Introduction: This section of the paper demonstrates the details of the topic to provide
idea to the readers about the application of IoT and the resource wastage in cloud domain and big
data challenges. Moreover, the readers will be able to understand the aim and objectives
regarding the problems and its relevant solution.
Literature review: In this section the concept of resource wastage in cloud domain and
big data challenges are evaluated through choosing 10 relevant peered review journal papers
(secondary data).
Revised problem statement: Depending on the literature the list of requirements for the
project are demonstrated in this section.
1. Introduction
1.1 Introduction to the problem and domain
Since few years the concept and application smart city is grabbing the attention of the
consumers. Though, this application is costly and advanced as well but still certain challenges
are associated to it that are to be eliminated soon for the successful implementation of the smart
city. In most of the cases the combination between the automation, architecture, infrastructure
and environment are not properly formed as a result the entire process become costlier and time
consuming at the same time. From technical and privacy point of perspectives certain issues and
challenges are always identified related to smart city application. Resource management has
been identified as the main issue of cloud technology application in smart city. As cloud allows
huge storage thus data management always come up as a major challenge.
1.2 Structure of the report
Introduction: This section of the paper demonstrates the details of the topic to provide
idea to the readers about the application of IoT and the resource wastage in cloud domain and big
data challenges. Moreover, the readers will be able to understand the aim and objectives
regarding the problems and its relevant solution.
Literature review: In this section the concept of resource wastage in cloud domain and
big data challenges are evaluated through choosing 10 relevant peered review journal papers
(secondary data).
Revised problem statement: Depending on the literature the list of requirements for the
project are demonstrated in this section.
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4Smart City Challenges and ProblemsSmart City Challenges and Problems
Methodology: In order to collect information in context with the topic proper research
methodology is needed to be selected
Proposed solution: Depending on the identified problems a solution has been proposed
for the resource management system using IoT in this section.
1.3 Background
This report demonstrates the resource wastage in cloud domain and big data application.
Within the urban agendas the concept of smart city is continuously incorporating which is
improving the technical atmosphere of the urban areas all over. The new concept of smart city is
being currently found in Asia, America and Europe as well. In order to design such smart cities
this is mandatory to utilize the advanced development strategies accordingly.
From the promising perspectives of smart city it can be said that, smart application of
Internet of things delivers quality life to those people who are associated to such ambiance. The
aims, objectives and the problem statement associated to the project are elaborated in this paper.
However, in order to conduct the topic this is mandatory to follow accurate research
methodology by the researchers in terms of research philosophy, approaches, and research
method. Secondary research method is applied for collecting information throughout.
Aim
The aim of the report is to demonstrate the resource wastage in cloud domain and big
data applications in the smart city. The challenges and issues of the smart city application are
defined and identified in this paper. This is very much important to mitigate the issues and
challenges of resource wastage in cloud domain and big data application specifically in the field
of smart city design and development.
Methodology: In order to collect information in context with the topic proper research
methodology is needed to be selected
Proposed solution: Depending on the identified problems a solution has been proposed
for the resource management system using IoT in this section.
1.3 Background
This report demonstrates the resource wastage in cloud domain and big data application.
Within the urban agendas the concept of smart city is continuously incorporating which is
improving the technical atmosphere of the urban areas all over. The new concept of smart city is
being currently found in Asia, America and Europe as well. In order to design such smart cities
this is mandatory to utilize the advanced development strategies accordingly.
From the promising perspectives of smart city it can be said that, smart application of
Internet of things delivers quality life to those people who are associated to such ambiance. The
aims, objectives and the problem statement associated to the project are elaborated in this paper.
However, in order to conduct the topic this is mandatory to follow accurate research
methodology by the researchers in terms of research philosophy, approaches, and research
method. Secondary research method is applied for collecting information throughout.
Aim
The aim of the report is to demonstrate the resource wastage in cloud domain and big
data applications in the smart city. The challenges and issues of the smart city application are
defined and identified in this paper. This is very much important to mitigate the issues and
challenges of resource wastage in cloud domain and big data application specifically in the field
of smart city design and development.

5Smart City Challenges and ProblemsSmart City Challenges and Problems
2. Literature review
2.1 Smart Cities: Definitions, Dimensions, Performance, and Initiatives
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions,
performance, and initiatives. Journal of Urban Technology, 22(1), 3-21.
In this new of technology it is determined that for designing and developing new smart
city both the concept of big data analytics and cloud computing are widely used. According to (),
crucial measurements of data are required to keep the security and value of smart city. The
hidden possibilities as well as competitive advantages of data are aiming to be unlocked by the
enterprise owners nowadays. According to the Hadoop market and digital market analysis report
it is identified that the revenue structure may reach a rate of $99 Billion (approximately) by 2022
which is currently around $12.90 Billion (approximately) (Lee& Lee, 2015). On the other hand
the global business market of big data market can obtain $46.34 Billion by the end of 2018.
2.2 Internet of Things for Smart Cities
Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for
smart cities. IEEE Internet of Things journal, 1(1), 22-32.
The essence of this article is focused on using the concept of IOT application in the smart
cities for managing resources. The resources are all well managed with the help of the OOT
application. The dramatic growth is the major challenge in big data application which is another
fault in resource management (Zanella et al., 2015). Introduction of new process and storing
capacity can eliminate the issues of the big data challenge.
2. Literature review
2.1 Smart Cities: Definitions, Dimensions, Performance, and Initiatives
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions,
performance, and initiatives. Journal of Urban Technology, 22(1), 3-21.
In this new of technology it is determined that for designing and developing new smart
city both the concept of big data analytics and cloud computing are widely used. According to (),
crucial measurements of data are required to keep the security and value of smart city. The
hidden possibilities as well as competitive advantages of data are aiming to be unlocked by the
enterprise owners nowadays. According to the Hadoop market and digital market analysis report
it is identified that the revenue structure may reach a rate of $99 Billion (approximately) by 2022
which is currently around $12.90 Billion (approximately) (Lee& Lee, 2015). On the other hand
the global business market of big data market can obtain $46.34 Billion by the end of 2018.
2.2 Internet of Things for Smart Cities
Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for
smart cities. IEEE Internet of Things journal, 1(1), 22-32.
The essence of this article is focused on using the concept of IOT application in the smart
cities for managing resources. The resources are all well managed with the help of the OOT
application. The dramatic growth is the major challenge in big data application which is another
fault in resource management (Zanella et al., 2015). Introduction of new process and storing
capacity can eliminate the issues of the big data challenge.

6Smart City Challenges and ProblemsSmart City Challenges and Problems
2.3 Everything you wanted to know about smart cities: The Internet of things is the
backbone
Mohanty, S. P., Choppali, U., & Kougianos, E. (2016). Everything you wanted to know
about smart cities: The internet of things is the backbone. IEEE Consumer Electronics
Magazine, 5(3), 60-70.
According to the granters the data are predicted to grow by 800% in the upcoming next 5
years. Improper resource management has been identified as a major challenge in the application
of big data in cloud computing for effective decision making (Botta et al., 2016). Based on the
data those are collected in a large amount must be managed well to improve the opportunities.
For any application and technology resources can be discriminated in various segments such as
human resources, material resources etc. Proper management of these resources is very much
crucial from operational and functional perspectives.
2.4 Efficient Energy Management for the Internet of Things in Smart Cities
Ejaz, W., Naeem, M., Shahid, A., Anpalagan, A., & Jo, M. (2017). Efficient energy
management for the internet of things in smart cities. IEEE Communications
Magazine, 55(1), 84-91.
The ideas of Internet of Things (IoT) specifically in smart cities are extremely energy
efficient. This journal depicts the energy management for IOT in the smart cities (Ejaz et al.,
2017). The concern is compared considering some big data initiatives and big data applications
details in the field of public, private as well as other third sectors. Armstrong and Taylor (2014),
stated that, in order to design a smart city the concept if internet of things should have to be
considered and applied accurately. IOT has the ability to design sustainable structure for the
2.3 Everything you wanted to know about smart cities: The Internet of things is the
backbone
Mohanty, S. P., Choppali, U., & Kougianos, E. (2016). Everything you wanted to know
about smart cities: The internet of things is the backbone. IEEE Consumer Electronics
Magazine, 5(3), 60-70.
According to the granters the data are predicted to grow by 800% in the upcoming next 5
years. Improper resource management has been identified as a major challenge in the application
of big data in cloud computing for effective decision making (Botta et al., 2016). Based on the
data those are collected in a large amount must be managed well to improve the opportunities.
For any application and technology resources can be discriminated in various segments such as
human resources, material resources etc. Proper management of these resources is very much
crucial from operational and functional perspectives.
2.4 Efficient Energy Management for the Internet of Things in Smart Cities
Ejaz, W., Naeem, M., Shahid, A., Anpalagan, A., & Jo, M. (2017). Efficient energy
management for the internet of things in smart cities. IEEE Communications
Magazine, 55(1), 84-91.
The ideas of Internet of Things (IoT) specifically in smart cities are extremely energy
efficient. This journal depicts the energy management for IOT in the smart cities (Ejaz et al.,
2017). The concern is compared considering some big data initiatives and big data applications
details in the field of public, private as well as other third sectors. Armstrong and Taylor (2014),
stated that, in order to design a smart city the concept if internet of things should have to be
considered and applied accurately. IOT has the ability to design sustainable structure for the
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7Smart City Challenges and ProblemsSmart City Challenges and Problems
consumers. Most of the renewable resources such as solar energy, wave energy, and thermal
power are used for designing the smart city.
If traditional archetype design concept is used for developing a smart city different
challenges nay occur. The roles of big data initiatives should be properly analyzed so that the
issues of resource wastage can be mitigated accordingly (Fang et al., 2014) .
2.5 ICT and sustainability in smart cities management
Bifulco, F., Tregua, M., Amitrano, C. C., & D'Auria, A. (2016). ICT and sustainability in
smart cities management. International Journal of Public Sector Management, 29(2), 132-
147.
In order to manage a smart city successfully the application of internet communication
technology is very much crucial which is demonstrated in this journal (Bifulco et al., 2016). The
aim of IOT is to make the application of IOT more impressive and effective at the same time.
The way of communication data access and security will become stronger with the application of
the IOT for developing smart city.
The sensor technology will become stronger with the installation of surveillance cameras,
monitoring instances as well as smart home appliances. The development of the smart city will
be foster with the installation of actuators, display, vehicles etc (Kerzner & Kerzner, 2017). Not
only this but also, many different domains like home automation, industrial automation,
application based healthcare industry, traffic management are the other application of IOT those
are necessary for the successful design of the smart city (Arasu et al., 2016). In this journal
qualitative research methodology is applied.
consumers. Most of the renewable resources such as solar energy, wave energy, and thermal
power are used for designing the smart city.
If traditional archetype design concept is used for developing a smart city different
challenges nay occur. The roles of big data initiatives should be properly analyzed so that the
issues of resource wastage can be mitigated accordingly (Fang et al., 2014) .
2.5 ICT and sustainability in smart cities management
Bifulco, F., Tregua, M., Amitrano, C. C., & D'Auria, A. (2016). ICT and sustainability in
smart cities management. International Journal of Public Sector Management, 29(2), 132-
147.
In order to manage a smart city successfully the application of internet communication
technology is very much crucial which is demonstrated in this journal (Bifulco et al., 2016). The
aim of IOT is to make the application of IOT more impressive and effective at the same time.
The way of communication data access and security will become stronger with the application of
the IOT for developing smart city.
The sensor technology will become stronger with the installation of surveillance cameras,
monitoring instances as well as smart home appliances. The development of the smart city will
be foster with the installation of actuators, display, vehicles etc (Kerzner & Kerzner, 2017). Not
only this but also, many different domains like home automation, industrial automation,
application based healthcare industry, traffic management are the other application of IOT those
are necessary for the successful design of the smart city (Arasu et al., 2016). In this journal
qualitative research methodology is applied.

8Smart City Challenges and ProblemsSmart City Challenges and Problems
2.6 How “smart cities” will change supply chain management
Tachizawa, E. M., Alvarez-Gil, M. J., & Montes-Sancho, M. J. (2015). How “smart cities”
will change supply chain management. Supply Chain Management: An International
Journal, 20(3), 237-248.
The process of supply chain management will be changed if the smart cities are
successfully designed and implemented considering all the innovation factors (Tachizawa et al.,
2015). The ways through which the smart city can change the supply change management
approach are elaborated in this journal. However the paradigm of the smart city is not applicable
in the urban or rural locations. For managing the public traffics the so called application the
government is also pushing most of the industries to adopt the ICT based solutions.
A smart city is capable of delivering structural health, waste management, reduced traffic
congestion, energy consumptions, smart car parking system, automation on the public buildings
etc (Tao et al., 2014). Apart from this some other solutions offered by the smart city include
noise monitoring to reduce noise pollution, air quality management etc.
2.7 A Communications-Oriented Perspective on Traffic Management Systems for Smart
Cities: Challenges and Innovative Approaches
Djahel, S., Doolan, R., Muntean, G. M., & Murphy, J. (2015). A communications-oriented
perspective on traffic management systems for smart cities: Challenges and innovative
approaches. IEEE Communications Surveys & Tutorials, 17.
Communication related to the traffic management process in a smart city is elaborated in
this journal. It is comprises of the challenges and approaches of innovation in smart cities.
2.6 How “smart cities” will change supply chain management
Tachizawa, E. M., Alvarez-Gil, M. J., & Montes-Sancho, M. J. (2015). How “smart cities”
will change supply chain management. Supply Chain Management: An International
Journal, 20(3), 237-248.
The process of supply chain management will be changed if the smart cities are
successfully designed and implemented considering all the innovation factors (Tachizawa et al.,
2015). The ways through which the smart city can change the supply change management
approach are elaborated in this journal. However the paradigm of the smart city is not applicable
in the urban or rural locations. For managing the public traffics the so called application the
government is also pushing most of the industries to adopt the ICT based solutions.
A smart city is capable of delivering structural health, waste management, reduced traffic
congestion, energy consumptions, smart car parking system, automation on the public buildings
etc (Tao et al., 2014). Apart from this some other solutions offered by the smart city include
noise monitoring to reduce noise pollution, air quality management etc.
2.7 A Communications-Oriented Perspective on Traffic Management Systems for Smart
Cities: Challenges and Innovative Approaches
Djahel, S., Doolan, R., Muntean, G. M., & Murphy, J. (2015). A communications-oriented
perspective on traffic management systems for smart cities: Challenges and innovative
approaches. IEEE Communications Surveys & Tutorials, 17.
Communication related to the traffic management process in a smart city is elaborated in
this journal. It is comprises of the challenges and approaches of innovation in smart cities.

9Smart City Challenges and ProblemsSmart City Challenges and Problems
Different challenges are associated to the application of big data in the smart cities. According to
Djahel et al., (2015), before entering to any battle generally it is important for the designer and
developers to design the concept in such a way so that it can meet all the expected objectives.
Big data is defined as a technical tool that is mainly used by the business organizations or
making effective decisions. Accurate strategies can structure the technology and develop the
solution. The challenges identified for the big data application and cloud computing technology
in resource management are as follows:
2.8 A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in
Smart Cities
Tang, B., Chen, Z., Hefferman, G., Wei, T., He, H., & Yang, Q. (2015, October). A
hierarchical distributed fog computing architecture for big data analysis in smart cities.
In Proceedings of the ASE BigData & SocialInformatics 2015 (p. 28). ACM.
For successful management of resources in the smart city project the application of fog
computing and cloud computing is mandatory. This journal defines the role of distributed fog
computing in smart city (Tang et al., 2015). It may happen that the system developer and the
analyzer are not having enough knowledge regarding the application of the bid data based
solution. Rather it can also be defined as lack of numbers if experts.
It is found that without proper understanding if big data application is adopted to any
project then it will lead to project failure. Lots of time and resources that are assigned for the
successful implementation of the project will be a waste if the project designer fails to apply
them in the right way (Bi, Da Xu & Wang, 2014).
2.9 Smart Cities: A Survey on Data Management, Security, and Enabling Technologies
Different challenges are associated to the application of big data in the smart cities. According to
Djahel et al., (2015), before entering to any battle generally it is important for the designer and
developers to design the concept in such a way so that it can meet all the expected objectives.
Big data is defined as a technical tool that is mainly used by the business organizations or
making effective decisions. Accurate strategies can structure the technology and develop the
solution. The challenges identified for the big data application and cloud computing technology
in resource management are as follows:
2.8 A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in
Smart Cities
Tang, B., Chen, Z., Hefferman, G., Wei, T., He, H., & Yang, Q. (2015, October). A
hierarchical distributed fog computing architecture for big data analysis in smart cities.
In Proceedings of the ASE BigData & SocialInformatics 2015 (p. 28). ACM.
For successful management of resources in the smart city project the application of fog
computing and cloud computing is mandatory. This journal defines the role of distributed fog
computing in smart city (Tang et al., 2015). It may happen that the system developer and the
analyzer are not having enough knowledge regarding the application of the bid data based
solution. Rather it can also be defined as lack of numbers if experts.
It is found that without proper understanding if big data application is adopted to any
project then it will lead to project failure. Lots of time and resources that are assigned for the
successful implementation of the project will be a waste if the project designer fails to apply
them in the right way (Bi, Da Xu & Wang, 2014).
2.9 Smart Cities: A Survey on Data Management, Security, and Enabling Technologies
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10Smart City Challenges and ProblemsSmart City Challenges and Problems
Gharaibeh, A., Salahuddin, M. A., Hussini, S. J., Khreishah, A., Khalil, I., Guizani, M., & Al-
Fuqaha, A. (2017). Smart cities: A survey on data management, security, and enabling
technologies. IEEE Communications Surveys & Tutorials, 19(4), 2456-2501.
This articles demonstrates the security issue and data management level issues associated
to IOT application in the smart cities (Gharaibeh et al., 2017). Again lots of loss in resources will
impact the budget structure of the projects. On job training and development program about the
big data application can reduce this specific challenge. The big data solution should have to be
monitored and controlled by the top business management authority and the smart city designer.
The big data technology has lots of variety thus, most of the cases the developer become
confuse about which one of the tools will be suitable for the specific solution (Yan, Zhang &
Vasilakos, 2014). Incorrect selection of the big data tool may lead the project towards business
failure. If due to any technical failure any information loss from the server or storage then that
cannot be fetched or retrieved easily. In order to resolve this issue backup services should have
to be adopted.
2.10 Smart cities concept and challenges: Bases for the assessment of smart city projects
Monzon, A. (2015, May). Smart cities concept and challenges: Bases for the assessment of
smart city projects. In Smart Cities and Green ICT Systems (SMARTGREENS), 2015
International Conference on (pp. 1-11). IEEE.
The essence of this specific article defines the challenges and concepts related to smart
city design based on IOT (Monzon, 2015). Though, big data gives the users a public platform
thus, security is referred to as a major components that much be considered by the project
designer to avoid further project escalation. If proper security channels and security mechanisms
Gharaibeh, A., Salahuddin, M. A., Hussini, S. J., Khreishah, A., Khalil, I., Guizani, M., & Al-
Fuqaha, A. (2017). Smart cities: A survey on data management, security, and enabling
technologies. IEEE Communications Surveys & Tutorials, 19(4), 2456-2501.
This articles demonstrates the security issue and data management level issues associated
to IOT application in the smart cities (Gharaibeh et al., 2017). Again lots of loss in resources will
impact the budget structure of the projects. On job training and development program about the
big data application can reduce this specific challenge. The big data solution should have to be
monitored and controlled by the top business management authority and the smart city designer.
The big data technology has lots of variety thus, most of the cases the developer become
confuse about which one of the tools will be suitable for the specific solution (Yan, Zhang &
Vasilakos, 2014). Incorrect selection of the big data tool may lead the project towards business
failure. If due to any technical failure any information loss from the server or storage then that
cannot be fetched or retrieved easily. In order to resolve this issue backup services should have
to be adopted.
2.10 Smart cities concept and challenges: Bases for the assessment of smart city projects
Monzon, A. (2015, May). Smart cities concept and challenges: Bases for the assessment of
smart city projects. In Smart Cities and Green ICT Systems (SMARTGREENS), 2015
International Conference on (pp. 1-11). IEEE.
The essence of this specific article defines the challenges and concepts related to smart
city design based on IOT (Monzon, 2015). Though, big data gives the users a public platform
thus, security is referred to as a major components that much be considered by the project
designer to avoid further project escalation. If proper security channels and security mechanisms

11Smart City Challenges and ProblemsSmart City Challenges and Problems
are not adopted then, the confidentiality of the system will be interrupted. In order to resolve this
challenge it is mandatory for the project manager to adopt mandatory encryption technology,
firewall mechanism etc.
Proper quality management of the information is identified as a major challenge for the
big data application. Data integration issues can be resolved by the project leads if the
comparison is failed to meet the success criteria and objectives (Shrouf, Ordieres & Miragliotta,
2014). Before using any data that should be compared with rest of the data to make sure that the
absolute suitable solution of data has been chosen for designing the final solution
3. Revised problem statement
3.1 Requirements of the project
As per the details in order to design the resource management system using the concept
of IOT it is found that all accurate resources are to be identified by the project manager. The
concept of IOT involves RFID, near field communication, universal accessibility of mobility and
wireless sensor network (Jennings & Stadler, 2015). The information that is stored in the server
using cloud technology must have the ability to get retrieved by the users regardless of their
location and time as well. The android application users can collect data from the stored server.
In case of financial field of application authorized users are only allowed to access data from the
server and none of the unwanted users are allowed to retrieve any data without permission. The
requirements are again discriminated in two segments such as functional and non functional
requirements (Hashem et al., 2015). The details of the requirements are as follows:
are not adopted then, the confidentiality of the system will be interrupted. In order to resolve this
challenge it is mandatory for the project manager to adopt mandatory encryption technology,
firewall mechanism etc.
Proper quality management of the information is identified as a major challenge for the
big data application. Data integration issues can be resolved by the project leads if the
comparison is failed to meet the success criteria and objectives (Shrouf, Ordieres & Miragliotta,
2014). Before using any data that should be compared with rest of the data to make sure that the
absolute suitable solution of data has been chosen for designing the final solution
3. Revised problem statement
3.1 Requirements of the project
As per the details in order to design the resource management system using the concept
of IOT it is found that all accurate resources are to be identified by the project manager. The
concept of IOT involves RFID, near field communication, universal accessibility of mobility and
wireless sensor network (Jennings & Stadler, 2015). The information that is stored in the server
using cloud technology must have the ability to get retrieved by the users regardless of their
location and time as well. The android application users can collect data from the stored server.
In case of financial field of application authorized users are only allowed to access data from the
server and none of the unwanted users are allowed to retrieve any data without permission. The
requirements are again discriminated in two segments such as functional and non functional
requirements (Hashem et al., 2015). The details of the requirements are as follows:

12Smart City Challenges and ProblemsSmart City Challenges and Problems
Functional requirements:
Purpose of the design of the bug data and cloud based resource management
system
Business process
Security requirements
Performance
Data migration
Data conversion
Non functional requirements:
Reliability
Scalability
Security
Interoperability
For this project the factor which is chosen is security requirements. In order to maintain
the confidentiality of the services and financial details this is mandatory to adopt the mechanism
of application firewall and encryption. In this technique a shared key is used by the developers
and that must not be shared by any of the external third party. The access for the information are
restricted and customized as well. The approach of IOT will be a successful one if all the
components are installed accurately for a successful resource management.
Functional requirements:
Purpose of the design of the bug data and cloud based resource management
system
Business process
Security requirements
Performance
Data migration
Data conversion
Non functional requirements:
Reliability
Scalability
Security
Interoperability
For this project the factor which is chosen is security requirements. In order to maintain
the confidentiality of the services and financial details this is mandatory to adopt the mechanism
of application firewall and encryption. In this technique a shared key is used by the developers
and that must not be shared by any of the external third party. The access for the information are
restricted and customized as well. The approach of IOT will be a successful one if all the
components are installed accurately for a successful resource management.
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13Smart City Challenges and ProblemsSmart City Challenges and Problems
4. Methodologies
4.1 Explanation of techniques used in past and present
As the project is based on smart city and the problem identified is about resource wastage
in cloud domain as well as big data challenges. The smart city applications are being developed
to manage the urban flows in addition to flow for real time purposes. Smartainability approach is
used as methodology for estimating with qualitative as well as quantitative information to
determine extent the smart cities are sustainable for deployment of smart IoT technologies.
Mackey and Gass (2015) stated that there are various tools for analyzing and evaluating
performance of smart city to provide with innovative technological solutions. In this particular
framework, Smartainability is developed to support the decision makers the benefits of IoT
system enables smart services for cities.
Fuzzy method
This method is used in the article “Smart cities: Definitions, dimensions, performance,
and initiatives”. It is used to determine relative importance of indicators as well as sub-
indicators. This particular method is dealt with medium sized cities along with perceptions for
further development. In order to predict town towards the smart city, various parameters are to
be used for the purpose of feasibility of the smart city (Brinkmann, 2014). Fuzzy logic is an
efficient way to map input space into the output space. It is easier to understand the basic rules
that the rules are to be derived from experts.
4. Methodologies
4.1 Explanation of techniques used in past and present
As the project is based on smart city and the problem identified is about resource wastage
in cloud domain as well as big data challenges. The smart city applications are being developed
to manage the urban flows in addition to flow for real time purposes. Smartainability approach is
used as methodology for estimating with qualitative as well as quantitative information to
determine extent the smart cities are sustainable for deployment of smart IoT technologies.
Mackey and Gass (2015) stated that there are various tools for analyzing and evaluating
performance of smart city to provide with innovative technological solutions. In this particular
framework, Smartainability is developed to support the decision makers the benefits of IoT
system enables smart services for cities.
Fuzzy method
This method is used in the article “Smart cities: Definitions, dimensions, performance,
and initiatives”. It is used to determine relative importance of indicators as well as sub-
indicators. This particular method is dealt with medium sized cities along with perceptions for
further development. In order to predict town towards the smart city, various parameters are to
be used for the purpose of feasibility of the smart city (Brinkmann, 2014). Fuzzy logic is an
efficient way to map input space into the output space. It is easier to understand the basic rules
that the rules are to be derived from experts.

14Smart City Challenges and ProblemsSmart City Challenges and Problems
Advanced analytics and algorithmic method
This method is used in the article “Everything You wanted to know about Smart Cities”.
The big data is being processed with use of this particular methods as well as tools for retrieving
of useful data and information. According to Flick (2015), this method is started with single case
and it is included of application of innovative methods for data transformation as well as analysis
of unrecognized trends as well as patterns into the data. Linear regression analysis is one of the
basic algorithms of the advanced analytics by which people can observe how the input data are
related to the output data. It is highlighting the existing literature as well as empirical evidences
to redefine existing framework towards the Smart cities.
Decomposition method
This method is used in the article “Efficient energy management for the internet of things
in smart cities”. Decomposition method is focused on analyzing the components of individuals of
time series. This method is used to solve with large scale problems related to big data. In this
article, this method is used to handle of big data. As IoT devices into the smart city applications
are operated on limited battery, therefore lower power design infrastructure is better for
addressing energy management into the IoT based smart cities (Ledford & Gast, 2018). The
existing application protocols for the devices are not as per the energy efficiency perspective.
Therefore, this method is explored to reduce radio duty cycle of the IoT devices and result to
achieve of energy efficiency environment.
Machine learning
This method is used in the article “How “smart cities” will change supply chain
management”. It is used to measure the performance of the city. The big data is being analyzed
Advanced analytics and algorithmic method
This method is used in the article “Everything You wanted to know about Smart Cities”.
The big data is being processed with use of this particular methods as well as tools for retrieving
of useful data and information. According to Flick (2015), this method is started with single case
and it is included of application of innovative methods for data transformation as well as analysis
of unrecognized trends as well as patterns into the data. Linear regression analysis is one of the
basic algorithms of the advanced analytics by which people can observe how the input data are
related to the output data. It is highlighting the existing literature as well as empirical evidences
to redefine existing framework towards the Smart cities.
Decomposition method
This method is used in the article “Efficient energy management for the internet of things
in smart cities”. Decomposition method is focused on analyzing the components of individuals of
time series. This method is used to solve with large scale problems related to big data. In this
article, this method is used to handle of big data. As IoT devices into the smart city applications
are operated on limited battery, therefore lower power design infrastructure is better for
addressing energy management into the IoT based smart cities (Ledford & Gast, 2018). The
existing application protocols for the devices are not as per the energy efficiency perspective.
Therefore, this method is explored to reduce radio duty cycle of the IoT devices and result to
achieve of energy efficiency environment.
Machine learning
This method is used in the article “How “smart cities” will change supply chain
management”. It is used to measure the performance of the city. The big data is being analyzed

15Smart City Challenges and ProblemsSmart City Challenges and Problems
for the insights which lead to get better decisions as well as strategic movers. The machine
learning is considered as field of AI by use of the software applications that can increase
accuracy to get expected outcomes.
Qualitative methods
This method is used in the article “ICT and sustainability in smart cities management”. It
is required to perform interviews by use of qualitative before an in-depth interview is gaining an
understanding to the answers (Silverman, 2016). The smart city concept is based on developed
cities such as Asia, Europe and America. This research is included of respondents from those
organizations. The focused is based on Asia, Europe and America countries due to complexity of
environment towards development of Smart city. Qualitative research method is based on taking
interviews of the managers for various organizations so that the main issues in cloud domain
related to resource management are identified (Ledford & Gast, 2018). It is used for analyzing
and evaluating the non-numerical data. It is applied to such study where there is involvement of
relationships among the individuals and business environments (Smith, 2015).
4.2 Comparison of the techniques
Factors Fuzzy
method
Advanced
analytics and
algorithmic
method
Decomposition
method
Machine
learning
Qualitative
methods
Definition It is used to
determine
relative
importance
of indicators
as well as
sub-
indicators
It is included
of application
of innovative
methods for
data
transformation
as well as
analysis of
unrecognized
Decomposition
method is
focused on
analyzing the
components of
individuals of
time series.
The big data
is being
analyzed for
the insights
which lead to
get better
decisions as
well as
strategic
It is based on
taking
interviews of
the managers
for various
organizations
so that the
main issues in
cloud domain
for the insights which lead to get better decisions as well as strategic movers. The machine
learning is considered as field of AI by use of the software applications that can increase
accuracy to get expected outcomes.
Qualitative methods
This method is used in the article “ICT and sustainability in smart cities management”. It
is required to perform interviews by use of qualitative before an in-depth interview is gaining an
understanding to the answers (Silverman, 2016). The smart city concept is based on developed
cities such as Asia, Europe and America. This research is included of respondents from those
organizations. The focused is based on Asia, Europe and America countries due to complexity of
environment towards development of Smart city. Qualitative research method is based on taking
interviews of the managers for various organizations so that the main issues in cloud domain
related to resource management are identified (Ledford & Gast, 2018). It is used for analyzing
and evaluating the non-numerical data. It is applied to such study where there is involvement of
relationships among the individuals and business environments (Smith, 2015).
4.2 Comparison of the techniques
Factors Fuzzy
method
Advanced
analytics and
algorithmic
method
Decomposition
method
Machine
learning
Qualitative
methods
Definition It is used to
determine
relative
importance
of indicators
as well as
sub-
indicators
It is included
of application
of innovative
methods for
data
transformation
as well as
analysis of
unrecognized
Decomposition
method is
focused on
analyzing the
components of
individuals of
time series.
The big data
is being
analyzed for
the insights
which lead to
get better
decisions as
well as
strategic
It is based on
taking
interviews of
the managers
for various
organizations
so that the
main issues in
cloud domain
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16Smart City Challenges and ProblemsSmart City Challenges and Problems
trends. movers. related to
resource
management
are identified.
Feature It is form of
valued logic
where the
truth values
of the
variables are
real number
in between 0
and 1.
It is
measuring the
predictor
variables into
the business
models.
This method is
developed to
discover
aggregate
attributes as
well as
descriptions.
It is
measurable
to the
phenomenons
which are
observed. It
is consisted
of effective
algorithms
into the
pattern
recognitions.
It is based on
understanding
the situations
and
elimination
responds to
the
opportunities
towards new
paths.
5. Proposed solution
5.1 Explanation of technology suits the IoT application
The smart city is described as city which allows real world urban data to collect as well
as analyze by use of software or IoT system, server architecture and network infrastructure along
with client services. In this study, IoT applications are implemented as proposed solution to the
smart city project. It is consisted of solutions with support of instrumentation as well as
interconnection of sensors along with mobile devices (Tao et al., 2014). It is included with
service production which exploits of accessible information and adopts of information flows
among the urban regions. The proposed problem in this paper is about resource wastage in the
cloud domain and big data challenges.
The smart city is consisted of optimal utilization of natural resources, safer and better
cities by efficient regulation of traffic system in addition to well-organized emergency
trends. movers. related to
resource
management
are identified.
Feature It is form of
valued logic
where the
truth values
of the
variables are
real number
in between 0
and 1.
It is
measuring the
predictor
variables into
the business
models.
This method is
developed to
discover
aggregate
attributes as
well as
descriptions.
It is
measurable
to the
phenomenons
which are
observed. It
is consisted
of effective
algorithms
into the
pattern
recognitions.
It is based on
understanding
the situations
and
elimination
responds to
the
opportunities
towards new
paths.
5. Proposed solution
5.1 Explanation of technology suits the IoT application
The smart city is described as city which allows real world urban data to collect as well
as analyze by use of software or IoT system, server architecture and network infrastructure along
with client services. In this study, IoT applications are implemented as proposed solution to the
smart city project. It is consisted of solutions with support of instrumentation as well as
interconnection of sensors along with mobile devices (Tao et al., 2014). It is included with
service production which exploits of accessible information and adopts of information flows
among the urban regions. The proposed problem in this paper is about resource wastage in the
cloud domain and big data challenges.
The smart city is consisted of optimal utilization of natural resources, safer and better
cities by efficient regulation of traffic system in addition to well-organized emergency

17Smart City Challenges and ProblemsSmart City Challenges and Problems
system(Qu et al., 2016). The smart city concept is included with the application of IoT system
that allows cities to better use of urban networking. It supports better economic growth which is
resulted into efficient and technological solution to deal with the city challenges. The IoT system
is installed near buildings where there is exchange of information with others and sends of
information to server through use of wireless communication (Thota et al., 2018). The IoT
system processes some of data management activities such as query, storage, and execution of
semantics to capture proper meaning of information from the massive data efficiency. There is
improvement of resource usage in IoT by use of resource management system where the smart
devices are being accessed on single platform and also handle of real time information for the
smart devices.
IoT resource management system is given reliable way to remote monitoring as well as
controlling of sensor devices with no overridden of resources (Fan et al., 2014). The proposed
system enables resources to access and control along with manage the business operations of
Smart city project. IoT system serves communities across various domains. Because of huge
number of network elements interacted and worked used of IoT based information system, there
is required of resource management system to run IoT operations. The resources are managed by
implementation of protocols, and processes to enhance reliability into the IoT operations (Bera et
al., 2018). There is domain of resource management throughout operations of IoT based on the
information systems.
system(Qu et al., 2016). The smart city concept is included with the application of IoT system
that allows cities to better use of urban networking. It supports better economic growth which is
resulted into efficient and technological solution to deal with the city challenges. The IoT system
is installed near buildings where there is exchange of information with others and sends of
information to server through use of wireless communication (Thota et al., 2018). The IoT
system processes some of data management activities such as query, storage, and execution of
semantics to capture proper meaning of information from the massive data efficiency. There is
improvement of resource usage in IoT by use of resource management system where the smart
devices are being accessed on single platform and also handle of real time information for the
smart devices.
IoT resource management system is given reliable way to remote monitoring as well as
controlling of sensor devices with no overridden of resources (Fan et al., 2014). The proposed
system enables resources to access and control along with manage the business operations of
Smart city project. IoT system serves communities across various domains. Because of huge
number of network elements interacted and worked used of IoT based information system, there
is required of resource management system to run IoT operations. The resources are managed by
implementation of protocols, and processes to enhance reliability into the IoT operations (Bera et
al., 2018). There is domain of resource management throughout operations of IoT based on the
information systems.

18Smart City Challenges and ProblemsSmart City Challenges and Problems
Figure 1: IoT based Resource Management System
(Source: Aazam& Huh, 2015, pp-689)
5.2 Graphs to support justification and arguments
The main activities of resource management system are resource modelling, discovery,
estimation, allocation as well as resource monitoring. Based on the resource wastage issues, the
data management activities are involved such as queries which are used to filter data required
and data extracted from the query are being stored into the folder and space in IoT devices. It
also helps to manage power as well as processing time (Aazam& Huh, 2015). By use of IoT
Application
model
Application
requirements
Modelling Discovery Estimation Allocation
Monitoring
Resource
model
Resource
instance
Resource
historical data
Figure 1: IoT based Resource Management System
(Source: Aazam& Huh, 2015, pp-689)
5.2 Graphs to support justification and arguments
The main activities of resource management system are resource modelling, discovery,
estimation, allocation as well as resource monitoring. Based on the resource wastage issues, the
data management activities are involved such as queries which are used to filter data required
and data extracted from the query are being stored into the folder and space in IoT devices. It
also helps to manage power as well as processing time (Aazam& Huh, 2015). By use of IoT
Application
model
Application
requirements
Modelling Discovery Estimation Allocation
Monitoring
Resource
model
Resource
instance
Resource
historical data
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19Smart City Challenges and ProblemsSmart City Challenges and Problems
system, sensors as well as IoT devices are not integrated with cloud by enabled to utilize of cloud
related services.
Figure 2: The growth revenue of the system
(Source:Zanella et al., 2014, pp-30)
IoT resources are become a part of the cloud resource pool along with shared of service
cloud resources. Therefore, IoT based resource management system is considered as best
solution for resources wastage issue and big data challenges (Fan et al., 2014). There are huge
amount of data that are generated by the sensor objects of real world into the IoT system. The
IoT applications are complex processing which are included of historical data along with time
series analysis.
system, sensors as well as IoT devices are not integrated with cloud by enabled to utilize of cloud
related services.
Figure 2: The growth revenue of the system
(Source:Zanella et al., 2014, pp-30)
IoT resources are become a part of the cloud resource pool along with shared of service
cloud resources. Therefore, IoT based resource management system is considered as best
solution for resources wastage issue and big data challenges (Fan et al., 2014). There are huge
amount of data that are generated by the sensor objects of real world into the IoT system. The
IoT applications are complex processing which are included of historical data along with time
series analysis.

20Smart City Challenges and ProblemsSmart City Challenges and Problems
Figure 3: Global growth of smart city application and percentage of revenue till
2018
(Source: Lee & Lee, 2015, pp-436)
Factors of
IoT system
Description
Functional
requirement
Wireless connections, devices which are ranged with higher
performance systems. There is also required of proper security of the
system (Thota et al., 2018).
Platform There is such an IoT platform with protocol support for data
integration.
Hardware
requirements
Power sources, memory storage, wireless communication,
sensors and Smartphone (Aazam& Huh, 2015).
Figure 3: Global growth of smart city application and percentage of revenue till
2018
(Source: Lee & Lee, 2015, pp-436)
Factors of
IoT system
Description
Functional
requirement
Wireless connections, devices which are ranged with higher
performance systems. There is also required of proper security of the
system (Thota et al., 2018).
Platform There is such an IoT platform with protocol support for data
integration.
Hardware
requirements
Power sources, memory storage, wireless communication,
sensors and Smartphone (Aazam& Huh, 2015).

21Smart City Challenges and ProblemsSmart City Challenges and Problems
From the above table, it is seen that the proposed IoT system should be helpful to
manage with the resource wastage as well as big data issues in Smart city project work.
From the above table, it is seen that the proposed IoT system should be helpful to
manage with the resource wastage as well as big data issues in Smart city project work.
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22Smart City Challenges and ProblemsSmart City Challenges and Problems
References
Aazam, M., & Huh, E. N. (2015, March). Fog computing micro datacenter based dynamic
resource estimation and pricing model for IoT. In Advanced Information Networking and
Applications (AINA), 2015 IEEE 29th International Conference on (pp. 687-694). IEEE.
Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K., ... &Widom, J. (2016).
Stream: The stanford data stream management system. In Data Stream Management (pp.
317-336). Springer, Berlin, Heidelberg.
Armstrong, M., & Taylor, S. (2014). Armstrong's handbook of human resource management
practice. Kogan Page Publishers.
Bera, S., Misra, S., Roy, S. K., &Obaidat, M. S. (2018). Soft-WSN: Software-defined WSN
management system for IoT applications. IEEE Systems Journal, 12(3), 2074-2081.
Bi, Z., Da Xu, L., & Wang, C. (2014). Internet of things for enterprise systems of modern
manufacturing. IEEE Transactions on industrial informatics, 10(2), 1537-1546.
Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet
of things and analytics. In Big data and internet of things: A roadmap for smart
environments (pp. 169-186). Springer, Cham.
Botta, A., De Donato, W., Persico, V., &Pescapé, A. (2016). Integration of cloud computing and
internet of things: a survey. Future Generation Computer Systems, 56, 684-700.
Brinkmann, S. (2014). Interview. In Encyclopedia of critical psychology (pp. 1008-1010).
Springer New York.
References
Aazam, M., & Huh, E. N. (2015, March). Fog computing micro datacenter based dynamic
resource estimation and pricing model for IoT. In Advanced Information Networking and
Applications (AINA), 2015 IEEE 29th International Conference on (pp. 687-694). IEEE.
Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K., ... &Widom, J. (2016).
Stream: The stanford data stream management system. In Data Stream Management (pp.
317-336). Springer, Berlin, Heidelberg.
Armstrong, M., & Taylor, S. (2014). Armstrong's handbook of human resource management
practice. Kogan Page Publishers.
Bera, S., Misra, S., Roy, S. K., &Obaidat, M. S. (2018). Soft-WSN: Software-defined WSN
management system for IoT applications. IEEE Systems Journal, 12(3), 2074-2081.
Bi, Z., Da Xu, L., & Wang, C. (2014). Internet of things for enterprise systems of modern
manufacturing. IEEE Transactions on industrial informatics, 10(2), 1537-1546.
Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet
of things and analytics. In Big data and internet of things: A roadmap for smart
environments (pp. 169-186). Springer, Cham.
Botta, A., De Donato, W., Persico, V., &Pescapé, A. (2016). Integration of cloud computing and
internet of things: a survey. Future Generation Computer Systems, 56, 684-700.
Brinkmann, S. (2014). Interview. In Encyclopedia of critical psychology (pp. 1008-1010).
Springer New York.

23Smart City Challenges and ProblemsSmart City Challenges and Problems
Deelman, E., Vahi, K., Juve, G., Rynge, M., Callaghan, S., Maechling, P. J., ... & Wenger, K.
(2015). Pegasus, a workflow management system for science automation. Future
Generation Computer Systems, 46, 17-35.
Fan, Y. J., Yin, Y. H., Da Xu, L., Zeng, Y., & Wu, F. (2014). IoT-based smart rehabilitation
system. IEEE transactions on industrial informatics, 10(2), 1568-1577.
Fang, S., Da Xu, L., Zhu, Y., Ahati, J., Pei, H., Yan, J., & Liu, Z. (2014). An Integrated System
for Regional Environmental Monitoring and Management Based on Internet of
Things. IEEE Trans. Industrial Informatics, 10(2), 1596-1605.
Flick, U. (2015). Introducing research methodology: A beginner's guide to doing a research
project. Sage.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The
rise of “big data” on cloud computing: Review and open research issues. Information
Systems, 47, 98-115.
Jennings, B., & Stadler, R. (2015). Resource management in clouds: Survey and research
challenges. Journal of Network and Systems Management, 23(3), 567-619.
Kerzner, H., & Kerzner, H. R. (2017). Project management: a systems approach to planning,
scheduling, and controlling. John Wiley & Sons.
Ledford, J. R., & Gast, D. L. (2018). Single case research methodology: Applications in special
education and behavioral sciences. Routledge.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and
challenges for enterprises. Business Horizons, 58(4), 431-440.
Deelman, E., Vahi, K., Juve, G., Rynge, M., Callaghan, S., Maechling, P. J., ... & Wenger, K.
(2015). Pegasus, a workflow management system for science automation. Future
Generation Computer Systems, 46, 17-35.
Fan, Y. J., Yin, Y. H., Da Xu, L., Zeng, Y., & Wu, F. (2014). IoT-based smart rehabilitation
system. IEEE transactions on industrial informatics, 10(2), 1568-1577.
Fang, S., Da Xu, L., Zhu, Y., Ahati, J., Pei, H., Yan, J., & Liu, Z. (2014). An Integrated System
for Regional Environmental Monitoring and Management Based on Internet of
Things. IEEE Trans. Industrial Informatics, 10(2), 1596-1605.
Flick, U. (2015). Introducing research methodology: A beginner's guide to doing a research
project. Sage.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The
rise of “big data” on cloud computing: Review and open research issues. Information
Systems, 47, 98-115.
Jennings, B., & Stadler, R. (2015). Resource management in clouds: Survey and research
challenges. Journal of Network and Systems Management, 23(3), 567-619.
Kerzner, H., & Kerzner, H. R. (2017). Project management: a systems approach to planning,
scheduling, and controlling. John Wiley & Sons.
Ledford, J. R., & Gast, D. L. (2018). Single case research methodology: Applications in special
education and behavioral sciences. Routledge.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and
challenges for enterprises. Business Horizons, 58(4), 431-440.

24Smart City Challenges and ProblemsSmart City Challenges and Problems
Mackey, A., &Gass, S. M. (2015). Second language research: Methodology and design.
Routledge.
Qu, T., Lei, S. P., Wang, Z. Z., Nie, D. X., Chen, X., & Huang, G. Q. (2016). IoT-based real-
time production logistics synchronization system under smart cloud manufacturing. The
International Journal of Advanced Manufacturing Technology, 84(1-4), 147-164.
Shrouf, F., Ordieres, J., &Miragliotta, G. (2014, December). Smart factories in Industry 4.0: A
review of the concept and of energy management approached in production based on the
Internet of Things paradigm. In Industrial Engineering and Engineering Management
(IEEM), 2014 IEEE International Conference on (pp. 697-701). IEEE.
Silverman, D. (Ed.). (2016). Qualitative research. Sage.
Smith, J. A. (Ed.). (2015). Qualitative psychology: A practical guide to research methods. Sage.
Tao, F., Cheng, Y., Da Xu, L., Zhang, L., & Li, B. H. (2014). CCIoT-CMfg: cloud computing
and internet of things-based cloud manufacturing service system. IEEE Transactions on
Industrial Informatics, 10(2), 1435-1442.
Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of
manufacturing resource toward cloud manufacturing. IEEE Trans. Industrial
Informatics, 10(2), 1547-1557.
Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of
manufacturing resource toward cloud manufacturing. IEEE Trans. Industrial
Informatics, 10(2), 1547-1557.
Mackey, A., &Gass, S. M. (2015). Second language research: Methodology and design.
Routledge.
Qu, T., Lei, S. P., Wang, Z. Z., Nie, D. X., Chen, X., & Huang, G. Q. (2016). IoT-based real-
time production logistics synchronization system under smart cloud manufacturing. The
International Journal of Advanced Manufacturing Technology, 84(1-4), 147-164.
Shrouf, F., Ordieres, J., &Miragliotta, G. (2014, December). Smart factories in Industry 4.0: A
review of the concept and of energy management approached in production based on the
Internet of Things paradigm. In Industrial Engineering and Engineering Management
(IEEM), 2014 IEEE International Conference on (pp. 697-701). IEEE.
Silverman, D. (Ed.). (2016). Qualitative research. Sage.
Smith, J. A. (Ed.). (2015). Qualitative psychology: A practical guide to research methods. Sage.
Tao, F., Cheng, Y., Da Xu, L., Zhang, L., & Li, B. H. (2014). CCIoT-CMfg: cloud computing
and internet of things-based cloud manufacturing service system. IEEE Transactions on
Industrial Informatics, 10(2), 1435-1442.
Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of
manufacturing resource toward cloud manufacturing. IEEE Trans. Industrial
Informatics, 10(2), 1547-1557.
Tao, F., Zuo, Y., Da Xu, L., & Zhang, L. (2014). IoT-based intelligent perception and access of
manufacturing resource toward cloud manufacturing. IEEE Trans. Industrial
Informatics, 10(2), 1547-1557.
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25Smart City Challenges and ProblemsSmart City Challenges and Problems
Thota, C., Sundarasekar, R., Manogaran, G., Varatharajan, R., &Priyan, M. K. (2018).
Centralized fog computing security platform for IoT and cloud in healthcare system.
In Exploring the convergence of big data and the internet of things (pp. 141-154). IGI
Global.
Yan, Z., Zhang, P., &Vasilakos, A. V. (2014). A survey on trust management for Internet of
Things. Journal of network and computer applications, 42, 120-134.
Zanella, A., Bui, N., Castellani, A., Vangelista, L., &Zorzi, M. (2014). Internet of things for
smart cities. IEEE Internet of Things journal, 1(1), 22-32.
Thota, C., Sundarasekar, R., Manogaran, G., Varatharajan, R., &Priyan, M. K. (2018).
Centralized fog computing security platform for IoT and cloud in healthcare system.
In Exploring the convergence of big data and the internet of things (pp. 141-154). IGI
Global.
Yan, Z., Zhang, P., &Vasilakos, A. V. (2014). A survey on trust management for Internet of
Things. Journal of network and computer applications, 42, 120-134.
Zanella, A., Bui, N., Castellani, A., Vangelista, L., &Zorzi, M. (2014). Internet of things for
smart cities. IEEE Internet of Things journal, 1(1), 22-32.
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