Identifying core IoT technologies using ARM and FCM: A comprehensive data-driven method

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information Pub Date : 2024-07-17 DOI:10.1016/j.wpi.2024.102295

Jalil Heidary Dahooie , Iman nouri , Mehdi Mohammadi , Haydar Yalcin , Tugrul Daim

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引用次数: 0

Abstract

The internet of things (IoT) technology has garnered significant attention in recent years due to its wide-ranging applications. IoT, with its high connectivity capabilities, integrates various industrial, domestic, and agricultural devices into a smart and remotely controllable software and hardware platform. The field of IoT technology is expansive and encompasses a multitude of sub-technologies. Identifying core technologies in this domain is crucial for guiding research and development efforts by companies. Given the interrelation of these core technologies and their combination with recent decision-making approaches, network-based strategies have recently received special attention. The developed methods are based on static conditions and the assumption of stability, while in emerging technologies like IoT, the pace of changes over time is high. This leads to changes in the importance of technologies under various scenarios.

In this study, in order to analyze the extracted patent data, association rule mining (ARM) algorithms were applied to identify the relationships between technologies and social network analysis was used to analyze the relationships between technologies and estimate their initial weights. Finally, fuzzy cognitive map (FCM) were used to estimate the final weights of technologies and rank them. The fcm approach allows for simultaneous modeling of both static and dynamic states of the system and, on the other hand, by calculating under various scenarios, suggests a core technology that is sustainable.

The research results show that digital information transmission technologies, digital or electrical data processing, and wireless communication networks are the most important sub-technologies of Internet of things.

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利用 ARM 和 FCM 识别核心物联网技术：一种全面的数据驱动方法

近年来，物联网（IoT）技术因其广泛的应用而备受关注。物联网以其高度的连接能力，将各种工业、家用和农业设备集成到一个可远程控制的智能软硬件平台中。物联网技术领域非常广泛，包含多种子技术。确定该领域的核心技术对于指导企业的研发工作至关重要。鉴于这些核心技术之间的相互关系以及它们与最新决策方法的结合，基于网络的战略最近受到了特别关注。已开发的方法基于静态条件和稳定性假设，而在物联网等新兴技术中，随着时间的推移，变化的速度非常快。在本研究中，为了分析提取的专利数据，应用了关联规则挖掘（ARM）算法来识别技术之间的关系，并使用社会网络分析来分析技术之间的关系并估计其初始权重。最后，使用模糊认知图（FCM）估算技术的最终权重并进行排序。研究结果表明，数字信息传输技术、数字或电子数据处理以及无线通信网络是物联网最重要的子技术。

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

World Patent Information INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

3.50

自引率

18.50%

发文量

期刊介绍： The aim of World Patent Information is to provide a worldwide forum for the exchange of information between people working professionally in the field of Industrial Property information and documentation and to promote the widest possible use of the associated literature. Regular features include: papers concerned with all aspects of Industrial Property information and documentation; new regulations pertinent to Industrial Property information and documentation; short reports on relevant meetings and conferences; bibliographies, together with book and literature reviews.