机器学习在物联网中的作用:调查

K. S. Arikumar, K. Tamilarasi, S. Prathiba, M. M. Chalapathi, R. Moorthy, A. Deepak kumar
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引用次数: 0

摘要

最近各种通信技术的进步为传感器设备与互联网的连接铺平了道路。预计到2025年,联网设备数量最多可达到754.4亿台。这类设备的数量直接影响要传输的数据量。物联网(IoT)是通过现有互联网在这些设备之间提供连接的技术之一。此外,物联网产生的大数据具有时间依赖、地点依赖、数据质量多模态等特点。本文详细介绍了处理物联网设备生成的数据问题的各种机器学习技术。此外,还介绍了各种机器学习算法在物联网数据中的应用,以提取更高级别的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Machine Learning in IoT: A Survey
The recent advancements in various communication technologies have paved the way for sensor devices to connect with the internet. It can be expected that the quantity of internet-connected devices can reach a maximum of 75.44 billion by 2025. The quantities of such devices directly influence the amount of data to be transferred. The Internet of Things (IoT) is one of the technologies that provide connectivity among such devices through the existing internet. In addition to this, the IoT generates big data with the characteristics such as time-dependent, location-dependent, and multi-modal data quality. This paper presents a detailed survey about various machine learning techniques that treat the issues of the data generated by IoT devices. Further, the applications of various machine learning algorithms to the IoT data for extracting higher-level information have been presented.
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