Big Data and Technology Evolution in the IoT Industry

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Elona Marku, Maryia Zaitsava, Manuel Castriotta, M. Guardo, M. Loi
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引用次数: 0

Abstract

The present study aims to better understand how and to what extent the different dimensions of Big Data can offer insights on technology evolution. By using a patent analytics perspective, in this paper, we introduce a novel approach based on co-words analysis using the abstracts of 170,279 European patents in the Internet of Things (IoT) field published from 2011 to 2019. In so doing, we map and visualize an industry’s technology structure, development, and trends, as well as disentangle the IoT technology conceptual structure, highlighting its core and boundary concepts. This is the first study that applies a decomposition framework to clarify the determinants of IoT inventions, showing relevant changes in the focus of IoT technology overtime. By shedding light on the evolutionary dynamics of the field, this research offers a valuable contribution to the technology innovation literature.
物联网产业中的大数据与技术演进
本研究旨在更好地理解大数据的不同维度如何以及在多大程度上为技术发展提供见解。本文从专利分析的角度,利用2011 - 2019年欧洲物联网(IoT)领域发表的170,279项专利摘要,提出了一种基于共词分析的新方法。在此过程中,我们绘制和可视化了一个行业的技术结构、发展和趋势,并理清了物联网技术的概念结构,突出了其核心和边界概念。这是第一个应用分解框架来澄清物联网发明的决定因素的研究,显示了物联网技术重点随着时间的推移而发生的相关变化。通过揭示该领域的进化动态,本研究为技术创新文献提供了宝贵的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
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