Scientific review on the internet of things research

Abstract

After the concept of Internet of Things (IoT) was introduced, numerous studies have been employed during the past two decades. However, because each study has its own individual goals, it is necessary to overview summarize the current status of IoT by investigating knowledge structure from a comprehensive perspective. It is meaningful to overview IoT in terms of 1) improving research efficiency, 2) identifying research opportunities, and 3) establishing research direction. For those reasons, several previous studies have been conducted. However, the internal and external validity due to citation and confirmation biases are threatened because most of them adopt a narrative review as a methodology. Although their insights are meaningful, dynamic changes in technological development are hardly reflected since they stand on a static approach. To overcome those limitations, this dissertation employed keywords and Latent Dirichlet Allocation (LDA) topic modelling analysis by retrieving more than 15,000 bibliographic data from Scopus database. Because keywords are selective terms to represent the main idea and concept concisely, this dissertation utilized them to investigate IoT research trend and emerging keywords. However, keywords analysis has inherent limitations of that same keywords used in different articles do not indicate they have identical semantic meanings. In addition, a set of keywords in an article cannot fully reflect author’s original intentions. In order to remedy this problem, a LDA topic modelling analysis was employed because texts information in abstracts is tolerant to possible misinterpretation in a keyword analysis. Consequently, this study discovered hot topics among 50 topics. A common conclusion from both studies is that trust, smart home, cloud, big data, and authentication might be prospective research topics for IoT. In addition, technological convergence in IoT research rather than divergence is required to achieve the original goal of IoT because current IoT components are not connected sufficiently while existing divergence indicate weak technical dependency. Interestingly, big data is one of the emerging topics, but its linkages toward other topics are quite weak. Policy makers, researchers, and practitioners can refer to conclusions from this study to establish research directions and to invest resources in IoT efficiently. Various theoretical and practical implications are discussed.