The concept of “Big Data” has drawn a considerable attention from researchers in information sciences, policy and decision makers in governments and enterprises such a new scientific paradigm is emerging as Data Intensive Scientific Discovery (DISD). The speed of growing excessive data causes great troubles to a wide range of fields and sectors from economic and business to public administration, from national security to scientific researches in many areas as it makes potential values and brilliant opportunities. Therefore, decision makers have a strong tendency to manage this growth, in particular from the viewpoint of data capture, data storage, data analysis and data visualization. This presentation aims to review deeply the current literature and classify tools, techniques and technologies using to handle the data deluge. After that, it have focused on reviewing and discussing insights and applications of big data benefits in smart cities such as traffic data centers, information transportation systems, citizen demands and etc.

1. Fahimeh TabatabaeiFahimeh Tabatabaei
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13. Pike Research defines a smart city as
“the integration of technology into a
strategic approach to sustainability,
citizen well-being, and economic
development.” Viable smart city
models thus should to be “multi-
dimensional, encompassing different
aspects of smartness and stressing the
importance of integration and
interaction across multiple domains”
(Vilajonsa et al, 2013).
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3-Approaches Characteristics
The top-down
Smart City
Optimization through the Technology;
Emphasis on having a control room;
Focusing on providing an ICT-based integrated architecture to overview urban
activities as well as the tools to automatically interact with infrastructures;
Processes implications consists of the calculations, visualizations and
predictions based on the gathered metrics;
involvement of powerful private
companies;
The bottom-up
Smart City
Focusing on the people ‘‘using’’ the city;
Relying on large and small businesses or start-ups that aim to arouse
innovation in a certain urban sector;
Dismissing any form of top-down urbanization (Specially with the
involvement of powerful private companies);
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The Smart City
as a local
innovation
platform
Looking at positive aspects of both views of top-down and bottom-top;
Collaborative perspective to smart cities (Smart cities as a collaborative
meeting place);
Using the potential of all involved stakeholders;
Considering to the Government as the intermediary, the enabler of interaction
of multiple actors;
Smart Cities should capture creative and collaborative innovation through directly
interactions between public bodies, private sectors and citizens in:
 Dealing with the next data flood, digital footprint and data trails (coming from use of
linked open data, big data, IoT, sensor data etc.);
 Identifying and tackling new relational complexities between actors;
 Facing grand societal challenges in a local context (e.g. mobility, security, local and
participatory governance etc.);
 Offering new and engaging experiences to citizens (Walravens, 2014).
Fahimeh Tabatabaei

16.  Developing IT infrastructures.
 Ramping up technologies and services that require large upfront investments.
 This might produce a new tertiary sector exploiting data generated in the existing
infrastructures, which will be used to offer new services to cities, utilities, and
citizens.
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Recent emergence of Cloud computing promises solutions to ICT challenges in Smart
cities by facilitating Big data storage and delivering the capacity to process, visualize
and analyze city data. Such an infrastructure level solution can also facilitate the
decision makers in meetings by providing an integrated information processing
infrastructure for variety of smart cities a applications to support decision making and
urban governance.
Fahimeh Tabatabaei

17. Big data concept has been used by US authorities to keep a track on terrorists. Monitoring and
capturing everything a person does on internet, feeds from surveillance cameras, border sensors,
capturing telephone and mobile communications, monitoring chat applications to keep a check on
suspected persons. USA project ADVISE (Analysis, Dissemination, Visualization, Insight and
Semantic Enhancement and PRISM are two such examples of use of Big Data for surveillance.
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The telecommunications infrastructure is the basis for data generation, exchange data, flow data
and their transport that provide intelligence to the city.
Open data coming from PA contains typically statistic information about the city (such as data on
the population, accidents, flooding, votes, administrations, energy consumption, presences on
museums, etc.), location of point of interests, POIs, on the territory (including, museums, tourism
attractions, restaurants, shops, hotels, etc.), major GOV services, ambient data, weather status
and forecast, changes in traffic rules for maintenance interventions, etc.
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