Mobile Crowd Sensing for Performance Assessment of IoT in Smart City: A Literature Review

Literature Review (Secondary Research) Template
Student Name & CSU
ID
Project Topic Title
Mobile crowd sensing for performance assessment of IoT in smart city
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Version 1.0 _ Week 1
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Reference in APA format Li, X., & Goldberg, D. W. (2018). Toward a mobile crowdsensing system for road surface assessment.
Computers, Environment and Urban Systems.
URL of the Reference Authors Names and Emails
and Level of Journal (Q1, Q2, …Qn)
Keywords in this Reference
https://www-sciencedirect-
com.ezproxy.csu.edu.au/science/
article/pii/S0198971517301333
Xiao Li, Daniel W. Goldberg
Level of journal: Q1
Road surface roughness; Crowdsensing; Smartphone;
Transient events detection
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Purpose) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Techniques: Threshold technique
Tools: Cloud based data server
Applied Area: Road surface
assessment
Problem: Issues related to the road surface
influences infrastructure management.
Their repairing requires expensive
instruments.
Goal: Provide solution to the road related
issues by using latest sensor rich smart
phones because they are lower in cost and
their efficiency is higher.
Components of the research are:
 Utilize GPS systems of the smart phones.
 Use smart phones sensor to measure road
surface.
 Identify road situation using crowd sensed data.
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The Process (Mechanism) of this Work; Means How the Problem has Solved & Advantage & Disadvantage of Each Step in This Process
Process Steps Advantage Disadvantage (Limitation)
1 Extraction of road surface transient events
by applying threshold technique. Helps to detect current status of road
surface.
N/A
2 Collect and process data by utilizing GPS of
smart phones.
Beneficial or data management Time consuming process.
3 Calculate assessment indexes using number
of transient event.
Helps to understand X-axis acceleration. N/A
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Major Impact Factors in this Work
Dependent Variable Independent Variable
Road segments GPS system of different smart phones identifies road segments.
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Field tests Andro sensor performs field test/ing to optimize different levels of
road roughness.
Input and Output Feature of This Solution Contribution & The Value of This Work
Input Output
Sensor embedded
Smart phone as
input for a real time
road assessment. A
web based data
server used to
manage data.
All detailed
information
regarding the
surface o the roads
will be measured. A
low cost crowd
sensing system will
be introduced for
assessment of road
surfaces.
This solution has the GPS utility which is
important to keep real time tracking of the
infrastructure.
Crowd sensing makes provides a cost
efficient solution for road assessment.
This solution contributes to the development of
smart cities with taking advantages of the smart
phone sensors.
Mobile crowd sensing is important for decrease
the cost of expensive instruments used in road
surfacing.
1. what in the method could have been
better?
2. what in the author analyses were
missed?
3. was there a technique that could have been
used, or a question that could have been
asked, that the researchers did not use or
ask?
In this method, there could have been a
utility of navigation.
In this solution, author missed to includes a
road navigation system.
Is there a need of permission to collect data
from a citizen’s smart phone?
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How the GPS system perform live mapping of
road fields?
4. were the conclusion justified and
How?
Analyse This Work By Critical Thinking The Tools That Assessed this Work
The conclusion of the research is completely
justified because the mobile crowd sensing is
the most efficient method to cut road
surfacing instrument price. This solution has
the ability to keep record of all road
assessment according to their time and date.
This solution is beneficial for a cost effective
development of Smart cities. It is the best way
to make use of IoT (Internet of things).
A limited repeatability of threshold based
technique and the limited accuracy of smart
phones.
GPS system
Field testing
Z-axis accelerometer
Diagram/Flowchart
Figure 1: Internet of things (A system architecture)
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Reference in APA format Arkian, H. R., Diyanat, A., & Pourkhalili, A. (2017). MIST: Fog-based data analytics scheme with
cost-efficient resource provisioning for IoT crowdsensing applications. Journal of Network and
Computer Applications, vol. 82, pp. 152-165.
URL of the Reference Authors Names and Emails
and Level of Journal (Q1, Q2, …Qn)
Keywords in this Reference
https://www-sciencedirect-
com.ezproxy.csu.edu.au/science/
article/pii/S1084804517300188 Hamid Reza Arkiana, Abolfazl Diyanatb,
Atefe Pourkhalilia
Level of journal: Q1
Internet of things (IoT); Fog computing; Crowdsensing;
Resource allocation; Optimization
The Name of the Current Solution
(Technique/ Method/ Scheme/
Algorithm/ Model/ Tool/ Framework/
... etc )
The Goal (Purpose) of this Solution &
What is the Problem that need to be
solved
What are the components of it?
Techniques: Fog based mobile crowd
sensing
Tools: Cloud computing application
Applied Area: Resource provisioning
Problem: Computational issues due to
increasing demand o the real time
application. Power/battery, bandwidth and
storage related challenges which affect
service quality.
Goal: Provide a proper resource allocation
to decrease the response time for real time
applications using mobile crowd sensing.
Components of the research are:
 Cloud computing
 Fog computing
 Resource provisioning
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The Process (Mechanism) of this Work; Means How the Problem has Solved & Advantage & Disadvantage of Each Step in This Process
Process Steps Advantage Disadvantage (Limitation)
1 Initialize fog computing Improves the quality of service while
sharing data over internet.
N/A
2 Provision of resource Beneficial for a proper resource allocation
and to collect data.
Consume power.
3 Create a network model Helps to establish an IoT framework. N/A
Major Impact Factors in this Work
Dependent Variable Independent Variable
Fog nodes They range from the mobile phones sensors.
Resource provision Algorithms will be optimized for the provisioning of resources.
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Input and Output Feature of This Solution Contribution & The Value of This Work
Input Output
Cloud computing
will be give as input
to crease a Fog
computing
environment. Apply
optimization
strategies for
resource provision.
An IoT framework
will be established
with use of mobile
crowd sensing.
This solution has the feature to create a MCS
platform which provides real time
compatibility for fog based applications.
This framework contributes in making easy
computation by providing applications that can
be operated on real time.
It is important for the development of smart
cities by embedding MSC framework in IoT.
1. what in the method could have been
better?
2. what in the author analyses were
missed?
3. was there a technique that could have been
used, or a question that could have been
asked, that the researchers did not use or
ask?
Automatic fog node generator could have
been added to the given solution to decrease
efforts in MSC framework.
Author missed to analyze the influences while
improving quality of service (QoS).
Which method is better, Fog computing or
Cloud computing?
How real time applications contributes in IoT
establishment?
4. were the conclusion justified and
How?
Analyse This Work By Critical Thinking The Tools That Assessed this Work
The conclusion is justified as it involves the
best computing methods. The resource
Fog based data analytics has the ability to
collect a large amount of data using a network
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