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Smart Cities: Mass Data Collection and Processing

Kauppinen, Amanda (2021)

 
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Kauppinen, Amanda
2021
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
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Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi:amk-202104074354
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The purpose of this thesis was to explore modern Smart City implementations and how they manage big data in terms of both storage and the process by which it is analysed. The thesis takes a closer look into what is required for a city to be considered Smart, and how modern cities are on the forefront of handling this transition. The main goal of this research was to provide detailed insight on the how large amounts of data are to be collected and stored in a Smart City setting. Additionally, the study includes a deeper evaluation of the analytical process in terms of both the requirements for success and various techniques by which the analysis is conducted. Furthermore, it incorporates the benefits and also the risks associated with city-wide implementation of Smart technologies. The thesis concludes with the future of Smart Cities and challenges they may face moving forward.

The research behind this thesis was conducted using varying journals, articles and e-books written within the past decade. These sources were comprised of topics such as Smart technologies, government-issued development plans, and case studies on modern Smart City implementations and piloting programs.

Based on this study, it can be concluded that there are both incredible benefits and substantial risks to the usage of big data analysis in Smart Cities. Smart City technologies have the ability to account for remarkable advancements in society. Ideally, they can accomplish a more connected, sustainable society, thus greatly improving the quality of life of inhabitants. However, the findings also indicate that it will be absolutely necessary moving forward that serious considerations are made in regard to cybersecurity and protection of both individual and government data.
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