=Paper=
{{Paper
|id=Vol-3333/paper3
|storemode=property
|title= Air Quality System in Smart City: Systematic Literature Review
|pdfUrl=https://ceur-ws.org/Vol-3333/Paper3.pdf
|volume=Vol-3333
|authors=Mouna Rhaiem,Mariam Chaabane,Ismael Bouassida Rodriguez
|dblpUrl=https://dblp.org/rec/conf/tacc/RhaiemCR22
}}
== Air Quality System in Smart City: Systematic Literature Review ==
https://ceur-ws.org/Vol-3333/Paper3.pdf
Air Quality System in Smart City: Systematic
Literature Review
Mouna Rhaiem1 , Mariam Chaabane1 and Ismail Bouassida Rodriguez1
1
ReDCAD, ENIS, University of Sfax, Tunisia
Abstract
Smart cities are becoming the go-to alternative when it comes to city planning or enhancement. Infras-
tructure, governance, security, transportation, economy, and healthcare are all now regulated by the
advanced technologies of this modern age following multiple patterns and parameters. According to
the United Nations Environment Program report [1], pollution is a global problem, and air pollution in
a city is the major environmental risk factor in our health. Smart cities, oriented service applications,
are becoming the go-to alternative when it comes to city planning or enhancement. Infrastructure,
governance, security, transportation, economy, and healthcare are all now regulated by the advanced
technologies of this modern age following multiple patterns and parameters. One of the main challenges
threatening the outcome of smart cities is pollution, further quickened by the non-ending emissions and
the acceleration of the global warming process. This highlights the importance of air quality in a smart
city. So, in this work we analyze some works from various countries that address the air quality (AQ)
in a smart city, the criteria used to evaluate the air quality in a smart city, and the categorization of air
quality based on those criteria. Novel aspects of this work are the purpose of the categorization of the
air quality in a smart city. This work is used to simplify the population the choice of the right place in
a smart city according to their needs, with air quality being the main criteria.
Keywords
Modeling, Air Quality, Smart city, System of system,
1. Introduction
the “Smart City” is a city that collects and uses data generated by its inhabitants and its
infrastructure, to improve the quality of life. It integrates services based on information and
communication technologies (ICT), which provide added value serving the city, via equipment
(such as sensors, actuators, etc.)[2]. These devices communicate with each other through a
network that optimizes the data transmission[3].
Thus, the “Smart City” offers urban services that make the city smarter and more economical.
The idea of the intelligence of a city is, therefore, to set up facilities in the city that use new
technologies in order to improve the quality, performance, and interactivity of urban services
while minimizing costs in money and time [4, 5].
One of the most important challenges in a smart city is the air quality system, So, this last
can detect all the dangers gazes in a smart city can facilitate for people to choose the best place
to live, and can encourage the government to make the best decision to decrease the source of
this gazes.
For decades, one of the most common ideas in literature is the precarious air quality in the
industrial zones and the healthy one in the green zones. However, in our day and time, green
places are no longer an exception to this rule, unfortunately. One of the fundamental elements
Tunisian Algerian Conference on Applied Computing (TACC 2022), December 13 - 14, Constantine, Algeria
Envelope-Open mouna.rh1111@gmail.com; mariam.chaabane@redcad.org; bouassida@redcad.org
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CEUR
Workshop
Proceedings
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ISSN 1613-0073 CEUR Workshop Proceedings (CEUR-WS.org)
of a healthy life is clean fresh air but there are many factors affecting its cleanness. Air pollution
is a major problem in many cities globally, that’s why we should know more about it and know
the criteria that are responsible for improving or deteriorating the air quality. On the other hand,
a very important evolution of cities is the emergence of "smart", especially smart technology, so
smart can offer the users use, control, and interaction, with using the Internet. Essentially, a
smart city is a city that provides services and solves city problems using advanced technology.
The smart city features things like improving transportation and accessibility, ameliorating
social services, promoting sustainability, and giving a voice to its citizens. We will be focusing
in this paper on the categorization of air quality based on the criteria deduced from previous
studies, and the main concept that we need to focus on is the purpose of the categorization of
air quality as a service among the system of systems in a smart city.
2. Background
A systematic literature review is a core scientific activity that provides scientists to create a
summary of current evidence. According to Barbara A. Kitchenham et al [6] that the main
technologies underpinning (EBSE)1 is a rigorous procedure for searching research literature
called a systematic literature review (SLR). SLRs are secondary studies (i.e. studies that are
based on analyzing previous research) used to find, critically evaluate, and aggregate all relevant
research papers (referred to as primary studies) on a specific research question or research topic.
One of the principal tools used to support an evidence-based paradigm in other fields, ac-
cording to Budgen and Brereton [7]is the generation of systematic literature reviews, used to
aggregate the experiences gained from a range of different studies in order to answer a specific
research question.
3. Methods
3.1. Research questions
The review focuses on four research questions:
• How did the literature address the air quality in a smart city?
• What are the criteria used to evaluate the air quality in a smart city?
• How can we categorize the air quality in the smart city based on these criteria?
• What is the purpose of the categorization of the air quality in a smart city?
3.2. Search Process
The search process combines the key concepts of our search questions in order to retrieve
accurate results. The selected sources are shown in table 1:
It is an organized structure of keywords which are: “modeling” and “air quality” and “smart
city” and “system of systems”, used to search a database. Then, we added synonyms, variations,
1
Evidence-Based Software Engineering
Table 1
Literature sources
Source Type of source Search URL
IEEE Xplore Digital Library reviewed paper ieeexplore.ieee.org
ACM Digital library reviewed paper dl.acm.org
Springer reviewed paper springer.com
and related terms for each keyword. A Boolean operator (AND and OR) allows us to try different
combinations of search terms. The final search string is (modeling OR model OR design) AND
(air quality OR air-quality) AND (smart city OR smart cities) AND (system of systems OR
system-of-systems OR systems of systems OR systems-of-systems).
3.3. Inclusion and exclusion criteria
A set of exclusion/inclusion criteria was applied, after obtaining the search results from the
different sources:
3.3.1. Inclusion Criteria
• Publications that are related to the research questions
• Publications that match one of the search items
• Publications that are published after or on the 01.01.2010
• Publications that have the best practices examples
• Publications that are related to higher education institutions/universities
3.3.2. Exclusion Criteria
• Publications that do not match one of the search items
• Publications that do not have best practices examples
• Publications that are published before or on the 31.12.2009
• Publications, that are not related to higher education institutions/universities
• Publications that are not related to the research questions
3.4. Data collection
The different studies retrieved from the search process were stored in different libraries. The
data extracted from each study were:
• The publication year.
• Information about answers to the research questions.
4. Search Results
4.1. search results by resources
The search results are summarized in table 2 including each resource and the corresponding
number of papers.
Table 2
Search results by Resource
Resources Number of papers
Springer 74
IEEE Xplore Digital Library 135
ACM Digital library 389
Hyper Articles en Ligne (HAL) 4
Total 602
4.2. Filtered search results
The filtered search results are summarized in table 4 from 602 references. We could not find
one reference. We excluded 7 papers that were duplicated 521 were excluded by reading the
title and the abstract. We obtained 73 papers for introduction reading. we obtained 66 papers
for reading.
Table 3
Filtered search results
Irrelevant and duplicates 7
Incomplete and not related to RQ, excluded by reading the title and abstract 521
File not found 1
Total for Introduction reading 73
Not related to RQ, excluded by reading Introduction 7
Total for reading 66
4.3. Filtered search results by resources
After filtering irrelevant, duplicate, and incomplete papers, a total of 66 papers were selected
for the reviewing process. Table3 presents the filtered search results by resources.
Table 4
Filtered search results by resources
Resources Number of papers
Springer 2
IEEE Xplore Digital Library 44
ACM Digital library 20
Hyper Articles en Ligne (HAL) 0
5. Finding
The review process of the different selected papers was done by how this researcher answering
for the four research questions defined previously.
5.1. Air quality in a smart city as addressed by the literature
Air pollution is a vital health problem in a city. According to the World Health Organization
(WHO)2 , ambient outdoor air pollution was estimated to cause 4.2 million premature deaths in
2016, which are mainly due to the exposure to small particulate matter PM2.53 etc.
Urban air pollution is a major problem in many cities globally. According to Min et al [8]
among air pollutants, Particulate Matter (PM) is of major concern since it can penetrate into
the respiratory system of people. In particular, PM 2.5 and PM 10 consist of particulates with a
diameter smaller than 2.5 and 10 micrometers respectively.
Most of the papers take air quality as the main segment in their research, and they agree that
there are many places on our planet that are considered unsafe. The more we know about the
subject, the greater we can improve it. Therefore, it is crucial to further study the air quality
variables in order to classify cities according to the degree of safety and well-being of citizens.
5.2. The criteria used to evaluate the air quality in a smart city
Many cities have built air quality systems monitoring stations to inform people about urban air
quality.
According to Suciu et al [9] air quality systems integrate various air quality sensors (VOCs4 , air
temperature, and relative humidity.
In initial implementation according to [10][11], [16], each sensor board has five environmental
2
https://www.who.int/fr
3
Particulate matter 2.5 (PM2.5), refers to tiny particles or droplets in the air that are two and one-half microns
or less in width
4
Volatile Organic Compound: a type of compound (a chemical that combines two or more elements) containing
carbon that changes easily into a gas and that can be harmful to people’s health or to the environment
sensors including air pressure, such as CO25 , NO26 , CO7 , O2, formaldehyde, and UVI8 , RSPM9 ,
SO210 , SPM11 , TVOC12 , illuminance , photochemical oxides, the weather condition (i.e. air
pressure, humidity, cloud condition, wind, rain), metahne, isobutene, ethanol, hydrogen, NO313 ,
N2O5, HNO3, HONO, PNA14 , H2O215 , ALD2Acetaldehyde, PANPeroxyacetylnitrat, PACDPer-
oxyacetic acid, FACDFormic acid, AACDAcetic Acid,CRES Cresol, MGLY Methylglyoxal, ISOP,
ISPD Products of isoprene rxns, SULF H2SO4 Sulfuric acid, UMHP Methanediol, TERP, NH3
(gases34), monsoon, other basic chemical substances, Hydrocarbon (CxHx), gas density, soil
moisture, and MQ5 Gas, CO3, chlorofluorocarbons, methane, sulfur dioxide, and CFC. PSO4,
PNH4, PNO3, POA, PEC, SOAA, SOAB, FPRM, CPRM.
Based on those studies, many criteria evaluating the air quality can be acquired, and with these
criteria, we can design a thorough categorization of smart cities using air quality systems as the
main parameter.
5.3. Categorization of the air quality in a smart city based on the previously
mentioned criteria
Du et al [12] propose different classifications of categories including one of them suggesting
five categories(good, moderate, unhealthy, very unhealthy, hazardous).
The work of Mehta et al [13] offers five categories as we can see in all of the air quality systems
(good, satisfactory, moderate, poor, very poor, and severe), or (very low, low, moderate, high,
very high).
Further, Do et al [14] propose three categories with this description (good, moderate, poor) or
this description Max concentration, Min concentration, and Mean concentration. As well, Gore
et al [11] takes colors and values as a categorization, with values:[0..50], [51..100], [101..150],
[151..200], [201..300] and [301..500] with colors: green, yellow, orange, red, purple, and maroon.
The work of Aiello [15] is based on a simple circular marker: the marker is filled with a value
ranging from a minimum value (blue) to the maximum value(red), where blue stands as 0 PM10
pollution and red stands as 30 PM10 pollutions, the maker based on both colors and values.
Ivanov et al used a scale from 0 (very low) to 100 (very high)[16], the scale was based on category
and values at the same time.
The categorization of air quality was addressed by multiple papers on which various groups were
suggested based on. These classifications are accessible and comprehensible for the majority of
the citizens, making it an efficient way to appreciate the state of a smart city.
5
gaz carbon dioxide
6
nitrogen dioxide gas
7
Carbon monoxide
8
Ultra Violet Index
9
Respirable suspended particulate matter
10
Sulfur dioxide
11
Suspended Particulate Matter
12
Total Volatile Organic compounds
13
Nitrogen oxide pollution
14
Peroxynitric acid
15
Hydrogen peroxide
5.4. Purpose of the categorization of the air quality in smart city
For smart cities, there is a need to monitor environmental conditions[17] to identify pollution
sources and mitigate them. Thus, a network of low-cost air quality monitoring sensor nodes
can be deployed to monitor air quality and weather parameters. Thus, through the detection of
pollution sources, the city can take corrective action and improve its environmental health. By
installing disaster detection systems, such as flood and precipitation monitoring solutions in
your environment, citizens can be alerted in advance of a catastrophic event. A holistic view
can be obtained, allowing authorities to make data-driven infrastructure planning and policy
decisions.
All papers preview the air quality both indoors and outdoors in a normal city and smart city
and talk about the criteria that contribute to the classification of the air quality.
The researches address the purpose of the categorization of the air quality in the smart city to
provide timely information to both government and the public. This data can be used to make
better decisions, whether it’s about planning for transportation or knowing the most optimal
route to walk to work.
6. Discussion
Studies have shown multiple criteria used to evaluate the air quality system in a smart city such
as dangerous gases, particulate matter, humidity, temperature, etc. An adequate categorization
of air quality based on these criteria was detailed, for example: (good, moderate, poor),(good,
moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, hazardous), in order to
determine the purpose of this categorization especially before building the smart city.
However, we acknowledge that there are considerable discussions on the purpose of the catego-
rization of air quality in a smart city. It was limited to assessing the hazard levels or the degree
of comfort, without including details about both subjects. As a matter of fact, an analysis of the
age, medical record, and profession of the citizens should be taken into consideration to ensure
an adapted air quality system for their needs. In addition, the areas with the highest air quality
index should include more green areas and more restrictions on gas emissions.
7. Threats to Validity
We identified two main threats to the validity of this SLR, when we talk about the time period,
we used studies that are published in 2010 and after, so there are some studies in 2010, and we
know after a decade, many indications change after a long period of time.
Further, in this SLR we used some studies consisting of a small number of papers and we know
that the number of papers in a study affects greatly the results.
8. Conclusion
In conclusion, indoor and outdoor air pollution is known to cause plenty of health problems,
that’s why we must take into consideration the importance of research assessing air quality
systems in a smart city.
The installation of an air quality monitoring system controls the presence of pollutants, resulting
in better environmental conditions for humans. It also has an impact on our health and reduces
the risk of health problems by maintaining a moderate or as-needed environment.
This paper focuses on the air quality in a smart city, precisely on the criteria used to evaluate
the air quality in a smart city and the categorization of the air quality system in a smart city
based on the aforementioned criteria.
Future investigations are necessary to validate the suggestions that can be drawn from this
study, specifically to describe clearly and in a detailed manner the purpose of the categorization
of air quality systems in a smart city, and most importantly before the construction of the smart
city.
Acknowledgment
This work was partially supported by the LABEX-TA project MeFoGL:
"Méthodes Formelles pour le Génie Logiciel"
Glossary
AQ Air Quality. 1
EBSE Evidence-Based Software Engineering. 2
ICT Information and Communication Technologies. 1
SLR Systematic Literature Review. 2
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