ABSTRACT: roots in the so-called Healthy Cities program. In


The idea
of Smart Cities (SCs) has its roots in the so-called Healthy Cities program. In
the framework of SCs, the air quality is one of the fundamental factors that
should be constantly monitored because of its effects on health and, more
generally, on citizens’ Quality of Life (QoL). In fact, WHO launched the Global
Platform on Air Quality and Health, calling for a collaborative effort in order
to develop, implement and monitor air pollution abatement strategies. The
monitored data will be uploaded to the web page to collect the information from
anywhere and easy for everyone to know about environment pollution.   From a technical point of view, we can
conclude that the use of sensor nodes can be quite effective in monitoring the
air quality in cities, increasing the monitoring area with limited costs,
w.r.t. to the use of only fixed nodes, at the cost of a tolerable measurement
error due to mobility and other factors, such as the height at which the mobile
sensor is used.

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Key words –  Healthy cities , monitor air quality ,
environment pollution , fixed sensor nodes, webpage



Smart Cities Mission is mainly an urban renewal
development initiated by the country’s government for the better growth of its
innumerable cities by making it citizen friendly and sustainable. This mission
envisions in area development plan and based on Smart Cities challenge the
selected cities are upgraded and benefitted from this mission. Each city will
possess a corporate company CEO to facilitate this mission. This mission was
recently launched in India in the year 2015 in which a total of ?98,000 crores (US$15 billion)
has been approved by the Indian Cabinet for the development of nearly 100 smart
cities nationwide. The entire urban ecosystem is built by four pillars namely
comprehensive development, physical, social and economical infrastructure.  This can be considered as a long term goal for
the benefit of citizens who can work for the development of their city by
adding the layers of “smartness”. The first objective for building an efficient
smart city is to develop a cost effective, distributed sensor network which
consist of both fixed and mobile sensor nodes in order to measure several
environmental parameters. The environment monitored data collected from sensor
nodes can be thereby shared to the citizens through their personal mobile
devices or by loading the contents in a web page. This vital information is
made available to the city governors as well as local authorities. The obtained
data will be related to the parameters like air quality, thermal index, traffic
density index, humidity, dew point, water level for flood detection, different
gas content in air like nitrogen, carbon dioxide, hydrocarbons etc. The overall
working is depicted by the following architectural diagram for the
environmental monitoring in smart cities.

The mobile application will receive the required
information by means of the cloud server and thus acts as an alertness for the
environment officials so that they can fix the problems which causes a
prolonged danger or an obstacle to the residing citizens. This is implemented
by the technology called “Internet of things” in which several devices will be
connected together and information can be manipulated and distributed accordingly.
The main advantage of this architecture is the low cost of the components
involved, provide a user friendly programming environment and also useful for
data analysis purpose to study about the environment.




centric computing and communication in smart cities:

This paper 1
Franca Delmastro et al. mainly explains about the mobile technologies which
keeps the people connected by means of special participatory sensing nodes and
mobile sensor network (MSN). A mobile application called CAMEO has been built
on social aware middleware platform able to integrate features of smart citizen
in sharing useful contents related to quality of life. CAMEO overcomes the
limitation of single person centric paradigm.

safe cities- A mobile and social network approach:

In this paper 2 Jaime Ballesteros et al. focusses
upon manmade disasters and growing population problems. It envisions upon the
real time public safety .It includes an android application namely iSafe to
form a geo-social network. It ensures both privacy and performance so as to
prevent crime events happening in city.

for smart cities:

In this paper 8 Andrea Zanella et al. presents the
“Padora Smart City” project which deals with several constraints like
structural health, waste management, air quality noise monitoring, traffic
congestion, smart parking etc by means of bluetooth, Wifi, Ethernet networks.
It gives out a relevant example of IOT paradigm short range communication
technology Radio Frequency Identification (RFID) and Near Field Communication (NFC).

data driven robustness algorithm for IOT in smart cities:

In this paper 17 Tie Qiu et al. deals with
information like node’s geographic, neighbor kit, sensing data extracted by bid
data server .The authors have proposed an approach by enacting multi-population
genetic algorithm(MPGA).It mainly optimizes the robustness of topology against
malicious  attacks .

architecture model for smart cities using cognitive Internet of Things (CIoT):

In this paper 18 Manoj Kumar Patra et al. deals
with the combination of cognitive science and internet of things. It helps in
dealing with massive amount of unstructured data. CIOT focusses on
heterogeneous and interconnected devices along with centralized server. Various
sensors includes (Accelerometer Sensor) MEMS, CMOS (Image Sensor),actuator etc.


This paper 20 Mario Weber et al. illustrates the
two case studies on smart parking and air quality monitoring .The basis
technology for the urban development is Information and Communication
Technology (ICT) enabling interaction and collaboration among citizen. The
services are implemented according to general data protection regulation (GDPR)
and directive (11, 12).

based smart cities – Recent advances and challenges:

This paper Yasir Mehmood 19 et al. presents an
overview of major open platforms for smart cities which categorises network
types, existing communication protocols, crucial requirements. Wide range
technology such as GSM, GPRS, LTE, cellular IOT, zigbee, Wifi, WiMax, IEEE
802.11p, etc. Open platform includes FIWARE, CONTIKI, OCEAN,OM2M6 ,Smart

building monitoring from structure to indoor environment:

This paper J. V?elák 9 et al. deals with
environmental monitoring in infrastructures by integrating information gathered
from buildings management system (BMS). It not only monitors temperature and humidity
but concentration values of CO2 and other volatile organic compounds  by using UCEEB sensor being emitted so as to
prevent health problems .IOT upgrades this system by means of low cost, low
power sensor. Communication technology like LoRa, Sigfox, LTE-M and sensors
like FBG (Fiber Brag Grating).

data aggregation using compressed sensing with side information:

In this paper Evangelos Zimos 10 et al. a
mechanism is being introduced called aggregation for large scale air pollution monitoring
by means of IOT devices. Aggregation techniques for WSN such as Differential
Pulse Code Modulation (DPCM) and alternative strategy like Distributed Source
Coding (DSC) have been used. The algorithm used here is data recovery which
combines Principal Component Analysis (PCA) with CS for grid network. The
proposed systems provide move robustness and efficiency compared to classical

smart cities using IOT – An empirical study

This paper Gaurav Sarin 11 et al. consists of
study of IOT and to identify preferences of consumer based on smart cities
solutions. It differentiates the concept of internet and IOT which mentions
connectivity not only possible in hardware devices but also in variety of
sensors. For this study primary tools like IBMSPSS and MS excel used to analyse
data .Other parameters like information security correlation, IOT revenue model
correlation, hardware cost and reliability, device and sensor interoperability
and independent variables like energy, traffic, healthcare air quality noise,
management values are analysed appropriately.



and Personalising Smart city services using Machine Learning,IOT and big data:

This paper Jeannette Chin 12 et al. explores
various technologies like MC (Machine Learning) and Artificial Intelligence
(AI) to leverage IOT and Big data to study about smart cities. Well known
algorithm like Bayes network, Naïve Bayesian, J48, Nearest neighbor correlate
weather data especially rainfall and temperature. The data is mainly analysed
on WEKA platform which is a powerful machine learning tool. All four
classification provide accurate and consistent results.

time smart traffic management system for smart cities by using IOT and bigdata:

This paper Patan Rizwan 13 et al. provides a clear
information about deploying traffic indicates and a low cost real time traffic
system. IOT is being used to retrieve the data at a faster rate and sent for
big data analysis. A user friendly App serves purpose by providing traffic
updates, status of read, vehicle strength, traffic jam issues etc. Techniques
like RFID, GPS are used for vehicle tracking. Primary algorithm used here is
VSN (Vector Distance Routing Algorithm) to provide reliable communication.  





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