Assessing smart city theories and models based on the utilization of big data in cities

In the wake of the rising city populations and rapid urbanization all over the world, cities are constantly evolving and striving to be smarter and more sustainable to serve their citizens. At the same time, they are experiencing challenges more complex than ever before, and have been looking for more efficient ways to solve these problems. Unfortunately, these challenges due to urbanization may likely be even worse in the future since it is almost impossible to re-build the existing cities. Therefore, there is a need for a modern conceptualization of smart technologies in order to create well-equipped smart cities to increase the urban livability. On the other hand, cities, including their whole infrastructure (e.g., utility systems such as power, water, gas and waste collection, and drainage systems) are continuously being instrumented with smart technologies at the aggregate level. While these smart technologies make human life easier, they also produce huge amounts of data whether through human interaction or not (i.e., buildings are equipped with smart automation and housing systems, and people have smart devices such as smart phones, smart watches and many others), and various techniques have been recently developed for privately and securely collecting, storing, analyzing, processing, integrating and visualizing these big data generated by both city systems and citizens in drastically increasing amounts. As such, smart cities and big data are very significant topics of the 21st century's modern world. Many past, ongoing and future smart city initiatives are introduced by governments and other agencies at the national and local level. These initiatives are shaping the world through huge investments in order to solve the problems associated by the increasing populations all over the world, especially in cities, to provide the efficient use of natural world resources, and finally to improve the quality of life in general. On the road to smarter cities, big data certainly have a significant role with regards to providing vital information on the city systems and its inhabitants, both physically and virtually. Therefore, one important question is as follows: Where does such data come from, and how can we efficiently utilize this data to achieve smarter cities? With this motivation, the main objective of this research is to aid in understanding the concept of smart cities utilizing a comprehensive assessment of big data technologies and methods. These technologies are evaluated regarding their current or potential use in smart cities, especially to inform the practitioners who are interested in developing smarter cities. As such, this thesis aims to give a general and deep understanding of the big data methods used to characterize and analyze smart cities while assessing the past and current smart city theories and models. This thesis focuses on how the efficient usage of urban data sets radically changed the way people live in cities in the 21st century with the help of information and communication technologies (ICT), and how big data can actually be utilized by city governments to improve urban planning and management processes in the context of smart cities. To achieve this goal, through the evaluation of the related literature and the assessment of data-driven applications of selected cities, several smart city principles will be presented in a novel scheme through "smart data management" and "smart people", which can successfully lead to "smart governance". To perform smart data management in cities, it is a must to instrument them with better data collection methodologies to ultimately develop better, different and smarter solutions to the problems faced by cities when compared to the past.