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Abstract
Smart-cities are an emerging paradigm containing heterogeneous network infrastructure, ubiquitous sensing devices, big-data processing and intelligent control systems. Their primary aim is to improve the quality of life of the citizens by providing intelligent services in a wide variety of aspects like transportation, healthcare, entertainment, environment, and energy. In order to provide such services, the role of big-data and its analysis is extremely important as it enables to obtain valuable insights into the large data generated by the smart-cities. In this article, we investigate the state-of-art research efforts directed towards big-data analytics in a smart-city context. Specifically, first we present a big-data centric taxonomy for the smart-cities to bring forth a generic overview of the importance of big-data paradigm in a smart-city environment. This is followed by the presentation of a top-level snapshot of the commonly used big-data analytical platforms. Due to the heterogeneity of data being collected by the smart-cities, often with conflicting processing requirements, suitable analytical techniques depending upon the data type are also suggested. In addition to this, a generic four-tier big-data framework comprising of the sensing hub, storage hub, processing hub and application hub is also proposed that can be applied in any smart-city context. This is complemented by providing the common big-data applications in a smart-city and presentation of ten selected case studies of smart-cities across the globe. Finally, the open challenges are highlighted in order to give future research directions.
Highlights
Smart-cities are an emerging paradigm made possible by the amalgamation of a number of new technologies, like the Internet of Things (IoT), real-time systems, and big-data
The following are the contributions of this work: a) First, we present the characteristics of big-data in a smart-city environment and devise a suitable taxonomy for the same. b) Second, we present a concise overview of the major big-data analytical platforms for smart-cities. c) Third, a possible four-tier system framework for big-data in the context of smart-cities is presented. d) Fourth, we discuss the most popular applications of big-data in a smart-city environment and present ten use-cases of actual smart-city initiatives across the globe. e) Last, we unearth several big-data related open research challenges to give future directions
BIG-DATA APPLICATIONS IN SMART-CITIES we present some of the common use cases of big-data analytics in a smart-city context
Summary
Smart-cities are an emerging paradigm made possible by the amalgamation of a number of new technologies, like the Internet of Things (IoT), real-time systems, and big-data. A massive volume of data from various sensors and other sources are generated by smart-cities, which must be collected, managed, and analyzed to get useful insights and provide the required functionalities. In this respect, big-data analytics play an important role by providing powerful data mining. 2. BIG-DATA CHARECTERISTICS IN A SMART-CITY AND TAXONOMY The smart-cities generate data in a continuous manner from different applications like healthcare, energy-management, traffic-management, environment monitoring, etc, which results in a massive volume. Data Analytics A wide variety of machine-learning algorithms are used to extract knowledgeable information from the big-data generated by smart-cities for making predictions, identifying trends, discovering hidden information or making decisions [23].
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