Developing a Context Aware System for Energy Management in Urban Areas

Ferrández-Pastor, Francisco-Javier; Gómez-Trillo, Sergio; García‐Chamizo, Juan Manuel; Valdivieso-Sarabia, Rafael J.

doi:10.1007/978-3-319-48799-1_37

Cited by 1 publication

(1 citation statement)

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“…The third most growth topic was energy efficiency with 154 documents, and China and Italy as leading countries with 18 and 17 publications, respectively. Energy efficiency as an application for IoT is related in this data set with the following topics: smart buildings [128][129][130], energy harvesting [131][132][133], and RFID [134,135]. Social networks (or Social media) is another application for IoT, with 117 documents, and Italy as the leading country with 23 publications.…”

Section: Applicationsmentioning

confidence: 99%

Internet of Things: A Scientometric Review

et al. 2017

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Abstract:Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, which generate a large number of samples, creating a big data challenge. This IoT paradigm has gained traction in recent years, yielding extensive research from an increasing variety of perspectives, including scientific reviews. These reviews cover surveys related to IoT vision, enabling technologies, applications, key features, co-word and cluster analysis, and future directions. Nevertheless, we lack an IoT scientometrics review that uses scientific databases to perform a quantitative analysis. This paper develops a scientometric review about IoT over a data set of 19,035 documents published over a period of 15 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) in two main scientific databases (Clarivate Web of Science and Scopus). A Python script called ScientoPy was developed to perform quantitative analysis of this data set. This provides insight into research trends by investigating a lead author's country affiliation, most published authors, top research applications, communication protocols, software processing, hardware, operating systems, and trending topics. Furthermore, we evaluate the top trending IoT topics and the popular hardware and software platforms that are used to research these trends.

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