Machine learning techniques in Internet of Things

Siqi Bai, Xinyue Cui
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Abstract

The Internet of Things (IoT) and Machine Learning (ML) are two very hot technologies these days. IoT requires a lot of data processing, and ML is a useful means of processing data. Therefore, the combination of IoT and ML has become a very promising research direction. This paper is a investigation of the combination of IoT and ML. It first introduces the development history of IoT and ML, then introduces some achievements that have emerged in the field of ML and IoT combination. After that, the paper refers some ML technologies which will play important roles in IoT. In this process, this paper also proposes a scheme to improve the accuracy of YOLO algorithm by identifying picture groups. Finally, the paper discusses the existing problems and future development directions of the combination of IoT and ML and provides some references and suggestions for scholars who study the combination of ML and IoT technology.
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物联网中的机器学习技术
物联网(IoT)和机器学习(ML)是目前非常热门的两项技术。物联网需要大量的数据处理,而机器学习是处理数据的有用手段。因此,物联网与机器学习的结合已经成为一个非常有前途的研究方向。本文是对物联网和机器学习结合的研究,首先介绍了物联网和机器学习的发展历史,然后介绍了在物联网和机器学习结合领域已经出现的一些成果。然后,本文介绍了一些将在物联网中发挥重要作用的机器学习技术。在此过程中,本文还提出了一种通过识别图片组来提高YOLO算法准确率的方案。最后讨论了IoT与ML结合存在的问题和未来的发展方向,为研究ML与IoT技术结合的学者提供了一些参考和建议。
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