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each public infrastructure is of the autonomous and decentralized type,
or in other words, is composed of separate and independent clusters,
each of which is connected to the other clusters. is allows for the
coordination of electric power and transportation management systems,
or between the electric power management systems of different regions.
For instance, advanced management is possible based on monitoring
the balance between power supply and demand to direct electric auto-
mobiles to charge stations with available power, and it is also possible to
make accommodations for electric power between regions.
Having understood the emerging needs, several corporations have
one or more generic as well as specific IT products for freshly starting
intelligent city tasks and for enhancing existing cities to be smart.
1.9 e Context-Aware Framework for Smart City Applications
ere are sensing, perception, vision, knowledge extrapolation, and
actuation technologies flourishing to create and sustain context-
aware environments within a city. People are about getting all kinds
of information, commercial transactions, knowledge and physical
services based on their situation (location, time, etc.) and their vari-
ous needs (mental, physical, social, etc.). Cyber applications, cloud-
based services, user devices, communication gateways and device
middleware, digitalized and interconnected objects, and so on are
collectively contributing to the swift implementation and delivery of
cognitive context-aware services to users. e framework (Figure 1.5)
for context-aware computing possesses five main modules.
1.9.1 Data Collection and Cleansing
is is a prime component for carefully collecting data from dis-
tributed and difference sources. With the continued growth of data
generators and extractors (sensors and actuators, smartphones, social
sites, enterprise as well as cloud data centers, devices and instruments
from research labs, machines from manufacturing plants and floors,
etc.), multiformatted and faceted data are being gathered these days.
Further, data gleaned need to be subjected to a series of tasks such as
transforming and polishing to make them compatible with the tar-
get data storage environment. With the emergence of new kinds of
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ENVISIONING INTELLIGENT CITIES
database management systems (Structured Query Language [SQL],
NewSQL, and NoSQL), the choice of data management is very criti-
cal for the framework. Data connectors, drivers, adapters, and inte-
grators have been made available by product vendors to simplify this
arduous task. Data virtualization is a new term in the industry that is
gaining momentum for data collection and synchronization in highly
distributed and disparate environments.
1.9.2 Data Storage
Once data are refined they are duly stored in an easy-to-access and
use storage infrastructure such as a database, data cube and mart, or
data warehouse. is enables users to query the data warehouse to
retrieve the correct and relevant information to plan ahead and pro-
ceed with clarity and confidence. It is a kind of batch processing and
pull mechanism. Slicing, dicing, report generation, and other kinds of
macro- as well as microlevel operations can be accomplished on data
stored to squeeze out usable information.
1.9.3 Data Interpretation
On the other hand, as data pour into different places, context-sensitive
information needs to be retrieved and dispatched to the people concerned
Data dissemination
Data
warehouse
Data
selection
Data acquisition
Data store
User
queries
Data
interpretation
Interface
Interfac
e
Data
integration
Inquiry
pool
Figure 1.5 The reference architecture for the context-aware framework.
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through a variety of devices, displays, and so on; centralized monitoring;
measurement and control systems; any appropriate actuation systems,
and so on. at is, a competent real-time data interpretation mecha-
nism has to be in place for extracting situation details quickly to act
on them. Knowledge discovery is a crucial cog in context-aware com-
puting. ere is a need to have special knowledge bases, policies/rules
repository, and other viable solutions to facilitate accurate interpretation
of incoming data to extract timely insights. us knowledge engineering
and enhancement are achieved through multiple tasks such as data inte-
gration, aggregation, classification, clustering, composition, processing,
analyzing, mining, and so on done individually and collectively.
1.9.4 Cloud-Based
e context-aware framework has a module to enable cloud connec-
tivity. ese days, sensors and devices in our everyday environments
are connected not only with one another in the vicinity but also with
remotely hosted applications, services, and data in cloud environ-
ments. With a device integration standard such as Open Service
Gateway initiative (OSGi), devices in our physical places are being
empowered by dynamically downloading all kinds of enabling ser-
vices and installing and configuring them to be highly relevant for the
widely discoursed and discussed digital living. us cloud integration
is indispensable for future context-aware solutions. ese days, differ-
ent sorts of data are being generated outside our living environments
and they are of high value for people if leveraged smartly. For exam-
ple, there are unprecedented advancements in the forms of social net-
working sites, knowledge communities, smarter cars with in-vehicle
infotainment systems, financial industries pumping trillions of bytes
every day, and so on. e projected data growth is simply phenomenal.
1.9.5 Data Dissemination
Knowledge engineered needs to be packaged and shared among users
in a preferred and presentable format. Reports, maps, charts, and
graphs are the main mechanisms for sharing knowledge. Data visual-
ization is a popular topic bombarded with a bevy of techniques, tools,
and tips facilitating the dissemination of knowledge to people in time.
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ENVISIONING INTELLIGENT CITIES
Context-awareness is an important criterion for city services.
With the proliferation of sensors in city environments, data capture,
interpretation, and knowledge dissemination aspects are essential for
crafting people-friendly services.
1.10 Conclusion
e goals of smart cities are the ubiquitous availability and simpli-
fied access of various urban resources, infrastructures, facilities, and
services. Further, cities ought to be self-sustaining ecological environ-
ments and prime service providers for residents, enterprising endeav-
ors and adventures, institutions, and visitors. Cities need to be deeply
connected, functionally integrated, technologically automated, and
equipped to use their precious resources and infrastructures optimally
to visualize and deliver hitherto unforeseen services. Finally, smart
cities will be thriving, scintillating, and increasingly attractive hubs
with at the same time substantially reduced living costs and mini-
mization of the climate footprint. Smart city initiatives are clearly
mission driven and aptly enabled by mashups of many proven and
promising technologies. e key use cases for intelligent cities include
• Smart traffic for reducing congestion on city roads
• Smart healthcare for enabling appropriate access to health-
care data for early disease detection and prevention, informed
diagnosis and medication prescription, compassionate care,
and so on
• Smart safety and security to improve public and property
safety by reducing crime incidents and providing faster
responses for both man-made and natural disasters
• Smart service delivery by streamlining, tailoring, and person-
alizing scores of social, physical, and information services for
residents
• Smart energy for environmental sustainability
• Smart banking for synchronized and simplified cash transactions
• Smart businesses to be sufficiently anticipative of consumers’
needs and come out with people-centric offerings
e list is actually growing with the fluent arrival and acceptance of
pioneering technologies; multipurpose yet handy devices; indispensable,
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disposable, disappearing, and diminutive sensors and actuators; sustain-
able and resilient infrastructures; city-specific and converged IT plat-
forms; outside-in thinking in product design; and co-creation of city
services, data analytics and knowledge engineering systems, and so on.
References
1. TCS Innovation Labs (2013). Intelligent Cities: A City Process
Management Approach (white paper).
2. Alcatel-Lucent (2012). Getting Smart about Smart Cities: Understanding
the Market Opportunity in the Cities of Tomorrow.
3. IBM (2012). IBM Intelligent Operations Center for Smarter Cities
Administration Guide (Redbook).
4. Oracle (2013). How Smart Are Your City’s Services? Oracle’s City
Platform Solution (white paper).
5. ales Smart City Platform, https://www.thalesgroup.com/en.
6. Hitachi Smart City Platform, http://www.hitachi.com/.
7. Information Technology (IT) Portal, http://www.peterindia.net.
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