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Smart city article details

Title	A Bibliometric Analysis Of Anomaly Detection For Iot-Enabled Smart Cities
ID_Doc	418
Authors	Chugh N.
Year	2022
Published	Lecture Notes in Electrical Engineering, 915
DOI	http://dx.doi.org/10.1007/978-981-19-2828-4_29
Abstract	Anomaly detection for IoT-enabled smart cities is a significant field in the functioning of smart cities. To better characterize and understand anomaly detection for IoT-enabled smart cities literature studies, there is a requirement for widespread bibliometric analysis in this area. The aim of this work is to characterize the research literature over the last ten years (2011 to 2020) using citation and thematic analysis which is an automated process. To achieve the said objective, a bibliometric study is conducted on Web of Science (WoS) data comprising 375 research papers. The thematic analysis depicts the most studied topic distributions. It has been observed that significant areas are security, privacy, machine learning, and fault detection, respectively, associated with current research subject. The results of the study reveal that publications per year have grown swiftly in the last five years and on average 67 papers are published per year. The largest share of papers has been contributed by Asia followed by Europe and then North America in this field. Through this paper, researchers can get an overview of the studied field and contribute to the progression of this domain. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Author Keywords	Anomaly detection; IoT; Outlier detection; Smart cities

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