{"title":"Empowering IoT with Generative AI: Applications, Case Studies, and Limitations","authors":"Siva Sai, Mizaan Kanadia, Vinay Chamola","doi":"10.1109/IOTM.001.2300246","DOIUrl":null,"url":null,"abstract":"The rise of the Generative Pre-Trained Transformer(GPT) language model, more commonly used as ChatGPT has brought a spotlight on the ever-developing field of Generative AI (GAI).} With current advancements in graphics processing units (GPUs), it has become easier to train and use deep generative models. Similarly, the developments in edge computing have made it possible for us to make the most of GAI's potential for numerous use cases in IoT. In this article, we explore the prospects of combining GAI with Internet of Things (IoT) technology to create innovative solutions for several areas where these devices fall short. Specifically, we dive into how GAI can help address the challenges posed by data insufficiency and incompleteness in IoT systems, by generating synthetic data that can be used to train other deep models. We also discuss how GAI can be used to personalize content generated by IoT devices along with other applications of the synergy. Additionally, we also delve into the real-world scenarios where the technology shall be implemented. We conclude with the limitations of GAI technology for IoT applications which can be worked upon in the future.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"31 5","pages":"38-43"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Internet of Things Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IOTM.001.2300246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The rise of the Generative Pre-Trained Transformer(GPT) language model, more commonly used as ChatGPT has brought a spotlight on the ever-developing field of Generative AI (GAI).} With current advancements in graphics processing units (GPUs), it has become easier to train and use deep generative models. Similarly, the developments in edge computing have made it possible for us to make the most of GAI's potential for numerous use cases in IoT. In this article, we explore the prospects of combining GAI with Internet of Things (IoT) technology to create innovative solutions for several areas where these devices fall short. Specifically, we dive into how GAI can help address the challenges posed by data insufficiency and incompleteness in IoT systems, by generating synthetic data that can be used to train other deep models. We also discuss how GAI can be used to personalize content generated by IoT devices along with other applications of the synergy. Additionally, we also delve into the real-world scenarios where the technology shall be implemented. We conclude with the limitations of GAI technology for IoT applications which can be worked upon in the future.
生成式预训练变换器(GPT)语言模型的兴起(更常用的名称是 ChatGPT)使不断发展的生成式人工智能(GAI)领域成为焦点。随着图形处理器(GPU)的不断进步,训练和使用深度生成模型变得更加容易。同样,边缘计算的发展也让我们有可能在物联网的众多用例中充分利用 GAI 的潜力。在本文中,我们将探讨将 GAI 与物联网(IoT)技术相结合的前景,以便为这些设备所欠缺的几个领域创建创新解决方案。具体来说,我们将深入探讨 GAI 如何通过生成可用于训练其他深度模型的合成数据,帮助解决物联网系统中数据不足和不完整所带来的挑战。我们还讨论了 GAI 如何用于个性化物联网设备生成的内容,以及协同效应的其他应用。此外,我们还深入探讨了该技术在现实世界中的应用场景。最后,我们总结了 GAI 技术在物联网应用中的局限性,这些局限性可以在未来加以改进。