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4
big data analytiCs for
rEal-tiME City insights
Abstract
As explained in the beginning of this book, the overwhelming
leverage of miniaturization, digitization, distribution, consum-
erization, industrialization, and deeper connectivity technologies
has a number of trendsetting and transformational implications
for IT as well as for businesses across the globe. e principal
one among them is the enormous growth in data size and the
greater variability in data scope, structure, and speed. With a
growing array of data sources, the data being generated, cap-
tured, transmitted, stored, and analyzed are tremendously huge.
As data are turning out to be a strategic asset for any organiza-
tion to be decisive, distinctive, and disciplined in its operations,
offerings, and outputs, newer technologies, tips, and tools are
being unearthed to smartly stock and subject all incoming data
to a variety of deeper investigations to gain actionable insights
in time. Extracting and extrapolating knowledge out of data
heaps in time especially goes a long way in empowering every
kind of enterprise to be exceptionally efficient. e fast-evolving
domain of big data analytics (BDAs) is therefore being viewed
as a blessing in disguise by worldwide institutions, innovators,
and individuals aiming to be competitive and cognitive in their
deals, deeds, and decisions. Governments, cities, and citizens
are bound to be affected owing to the continuous growth of data
(data through business transactions and scientific experiments;
social and people data; system, sensor, actuator, and machine
data, etc.). Any organization that takes care of all the data being
produced within as well as outside is going to be highly right and
relevant toward its constituents, customers, clients, and consum-
ers. In this chapter, we illustrate how BDA plays an enormous
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INTELLIGENT CITIES
role in bringing in the expectant big transformations for city
infrastructures and ultimately in the quality of city residents’
lives.
4.1 Introduction
Leading market watchers, analysts, and researchers have clearly indi-
cated that the data being generated are doubling every two years [1,2].
According to one report, the total amount of data created every two
days is equivalent to that created between the dawn of time and 2003.
Several noteworthy developments are cited as the principal reason for
such a monumental growth of data. Data sources are simply multiply-
ing; edge technologies are empowering every object to be computa-
tional, communicative, sensitive, and responsive; all kinds of physical,
mechanical, and electrical systems are being functionally enabled
through a seamless integration with cyber applications and services
to be participative and contributory; every commonly found, cheap,
and casual article in our living and working environments are becom-
ing digitized artifacts signaling their valiant and salient entry into
the mainstream computing arena; clouds are being positioned as the
core and central platform for hosting databases, data warehouses, data
marts, and cubes; millions of websites (Web 1.0) and tens of social
sites (Web 2.0) are producing volumes of social, enlightening, enter-
taining, and people data; and so on.
Further, every noticeable event, transaction, interaction, request
and reply, and so on are being expectantly captured and saved in stor-
age appliances and arrays for real-time as well as posterior investiga-
tions. Ordinary objects are being digitized to be extraordinary in their
actions and reactions and these then are capable of being intercon-
nected with one another in the vicinity and with remote ones; thus the
foreseeable networks being formed out of these empowered elements
are going to be creatively autonomic, people-centric, dependable,
extensible, and efficient. In a nutshell, the realization of extremely
connected and service-enabled digital objects and machines in our
midst is the grand foundation for big data, which is multistructured;
massive in volume; and mesmerizing in variety, velocity, and value.
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BDA FOR REAL-TIME CITY INSIGHTS
As widely experienced, data are the fountainhead for information
and knowledge that can be wisely used for bigger and better things.
For the envisioned knowledge era, data are being carefully collected,
cleansed, classified, clustered, and conformed as a simplifying and
streamlining process toward their final destination. Big data storage
solutions are feverishly prevalent these days. e most respectable
activity on big data is to do synchronized and systematic analytics to
correctly and readily emit big insights. BDA frameworks primarily
comprising data processing and storage modules, toolsets, connec-
tors, drivers, and adaptors are made available by open-source as well
as commercial-grade solution vendors. Because of the extreme com-
plicity and complexity induced by multiplicity and heterogeneity of
big data, enabling BDA products, platforms, patterns, practices, and
processes are being derived and released by IT professionals to do big
data analysis easily and quickly.
Large and mega cities are beset with scores of problems in housing,
infrastructures, safety and security, transport, energy, communica-
tion, water, the quality of life, and so on. e receding and reces-
sionary economy puts more stress and strictures on our declining and
deteriorating cities. At the same time, cities also open up fresh possi-
bilities and opportunities for thinkers and practitioners to contemplate
and activate different things differently. People need to change their
structure and behavior significantly to fit cogently with the distinctly
identified ideals of the smarter world, a next-generation idea or vision
being proclaimed and pursued vigorously and rigorously by leading
IT infrastructure and product companies these days. is incredible
notion of a smarter world is being presented as the next logical move
by worldwide technology creators and service providers to be relevant
in their long and arduous journey. ere are several key drivers and
decisive trends for the surging popularity of this game-changing con-
cept. A series of enabling developments and advancements in realiza-
tion technologies are being unfolded to simplify and streamline the
hitherto unknown path toward the desired and marvelous transfor-
mation. e BDA discipline is on a fast track and its contributions are
leveraged to design and develop smarter cities. is chapter describes
how BDA will contribute immeasurably and flawlessly toward the
faster realization and sustenance of next-generation cities.
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INTELLIGENT CITIES
4.2 Data Analytics and Intelligent Cities
Our cities are becoming more complex these days and hence inte-
grated, insightful, and intelligent IT systems need to be in place to
anticipatively monitor and manage the intricacies and intimacies
of the world’s cities. Today IT is penetrating all kinds of industry
verticals. For example, modern airlines are activated and automated
through a host of IT systems. Similarly, as the complications and con-
vulsions of today’s cities are on the rise, the smart leverage of all the
superb advancements of IT has to be elegantly ensured [3].
• Realization of intelligent operations will originate from
the boundary-less and ubiquitous access to and flow of data
across multiple sources. ere are tools to collect, correlate,
and corroborate data accurately, analyze it rapidly, and see the
resulting information visually anytime, anywhere to enable
informed decision making and to make agencies more nim-
ble, transparent, and adaptive.
• All of the polystructured data being gleaned are not value-
adding. ere are repetitive and redundant data. City-specific
data systems must understand the difference between signif-
icant and nonsignificant data in their specific contexts and
hence data management platforms, practices, processes, and
patterns are mandatory to attain the desired success.
• Master data management (MDM), city performance man-
agement (CPM), and BDA platforms; data virtualization and
visualization tools; and predictive and prescriptive analytics
capabilities can layer on top to deliver intelligent operations.
us it is clear that IT, especially data analytics, along with a flex-
ible and future-directed strategy, will play a very critical role in shap-
ing up our sliding and sagging cities.
4.2.1 e Prominent Sources of Big Data
As discussed earlier, big data represents huge volumes of data in
petabytes, exabytes, and zettabytes for the near future. As we move
around the globe, we leave a trail of data behind us. Business-to-
consumer (B2C) and consumer-to-consumer (C2C) e-commerce sys-
tems and B2B e-business transactions, online ticketing and payments,
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BDA FOR REAL-TIME CITY INSIGHTS
Web 1.0 (Simple Web), Web 2.0 (Social Web), Web 3.0 (Semantic
Web), Web 4.0 (Smart Web), still and dynamic images, and so on are
the prominent and dominant sources of data. Sensors and actuators
are deployed abundantly in specific environments for security and for
enabling the occupants and owners of the environments to be smart.
In short, every kind of integration, interaction, orchestration, col-
laboration, automation, and operation produces streams of decision-
enabling data to be plucked and put into transactional and then into
analytical data stores. As the world and every tangible item in it are
connected purposefully, the data-generation sources and resources are
bound to grow ceaselessly, resulting in heaps and hordes of data.
4.2.2 Describing the Big Data World
We have discussed the fundamental and copious changes happening
in the IT and business domains. e growth of service enablement of
applications, platforms, infrastructures (servers, storages, and network
solutions) and even everyday devices besides the varying yet versatile
connectivity methods has laid down strong and simulating founda-
tions for big interactions, transactions, automations, and insights. e
tremendous rise in data collection along with all the complications
has instinctively captivated both business and IT leaders and lumi-
naries to act accordingly and adeptly to take care of this impending
huge and data-driven opportunity for governments, corporations, and
organizations. is is the beginning of the much-discussed and dis-
coursed big data computing discipline.
is paradigm is becoming formalized with deeper and decisive
collaboration among product vendors, service organizations, inde-
pendent software vendors, system integrators, and research organiza-
tions. Having understood the strategic significance, all the different
stakeholders have come together in complete unison to create and
sustain simplifying and streamlining techniques, platforms, and infra-
structures; integrated processes; best practices; design patterns; and
key metrics to make this new discipline pervasive and persuasive.
Today the acceptance and activation levels of big data computing are
consistently on the climb. However, it is bound to raise a number of
critical challenges but at the same time, if taken seriously it will be
highly impactful and insightful for business organizations to traverse
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