Leveraging big data in smart cities: A systematic review

Abstract

Recently, the notion of a smart city, which includes smart well‐being, smart transit, and smart society, has attracted much attention due to its impact on people's quality of living. Data in smart cities are characterized by variety, velocity, volume, value, and veracity that are the well‐known characteristics of big data. The fast pace expanding of IoT devices and sensors in smart cities generates a huge volume of data that can help decision‐makers and managers in city management. The aim of this article is to wholly and systematically review big data handling approaches in smart cities, in which we analyze research efforts published between 2013 and February 2021, where these techniques are categorized based on their algorithms and architectures. Further, the main ideas, evaluation techniques, tools, evaluation metrics, algorithm types, advantages, and disadvantages are explored. Additionally, essential evaluation factors are introduced in which scalability and availability by 16%, time by 15% and accuracy by 11% are more in focus, and finally, some of the challenges, open issues, and future trends that are valuable for further research are suggested in big data handling approaches in smart cities.

Research trends in the application of big data in smart cities—A literature review

“…First, a comprehensive search of two databases, the WoS Core Collection and the IEEE Xplore database, was conducted. To identify relevant articles, we drew on the search criteria set out by Karimi et al (2021): TS=(('big data' AND 'smart' AND ('cities' OR 'city')).…”

“…The definitions of smart cities were summarized by Hajek et al (2022), who concluded that the smart city relies on ICT capability that improves resource efficiency, facilitates transportation, affects people, increases living standards, and promotes prosperity and sustainability. The rise of smart cities is an outstanding illustration of the diffusion and utilization of big data analytics (Karimi et al, 2021).…”

“…Big data practitioners receive a rigorous approach for smart city big data management. Karimi et al (2021) created an algorithm-architecture taxonomy. Meta-heuristic algorithms were the most popular.…”

“…Al Nuaimi et al (2015) elaborated on the benefits and opportunities of big data for smart cities, specifying the enabling requirements to capture the benefits of big data and the challenges involved. Most recently, Karimi et al (2021) systematically reviewed algorithm-and architecturebased approaches to the use of big data in smart cities.…”

Fuel Consumption Monitoring through COPERT Model—A Case Study for Urban Sustainability

“…In a study for quantification of instantaneous drive cycle and parameters in high spatio-temporal data, a novel approach was enabled by the authors in [23] which provided the basis for a microscopic emissions model. In an article by [24], where efforts were made using a novel algorithm and architecture to handle big data in smart cities. In a study by [25], several taxis data were decimated to find out why a taxi driver declines to serve taxi customers in Bangkok using an approach that is data driven for taxi probe data and their collection, analysis was carried out for several months.…”