Big data in smart-cities: Current research and challenges

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, environment, and energy. In order to provide such services, the role of big-data is important. In this article, we investigate the state-of-art research efforts directed towards big-data analytics in a smart-city context. First, we present a big-data centric taxonomy for the smart-cities to bring forth a generic overview of the big-data paradigm in a smart-city environment. Second, we present 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 suggested. Additionally, a generic four-tier big-data framework comprising of the sensing hub, storage hub, processing hub and application hub is presented that can be applied in any smart-city context. This is complemented by providing the common big-data applications and presentation of ten selected case studies of smart-cities across the globe. Finally, open challenges are highlighted in order to give future research directions.