Harnessing IoT Potential with Generative AI: Utilizations, Real-world Examples, and Boundaries |
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| © 2024 by IJCTT Journal | ||
| Volume-72 Issue-7 |
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| Year of Publication : 2024 | ||
| Authors : Tanvi Hungund, Shobhit Kukreti, Priyank Singh | ||
| DOI : 10.14445/22312803/IJCTT-V72I7P102 | ||
How to Cite?
Tanvi Hungund, Shobhit Kukreti, Priyank Singh, "Harnessing IoT Potential with Generative AI: Utilizations, Real-world Examples, and Boundaries," International Journal of Computer Trends and Technology, vol. 72, no. 7, pp. 12-16, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I7P102
Abstract
The emergence of the Generative Pre-Trained Transformer (GPT) language model, commonly known as ChatGPT, has spotlighted the continuously evolving realm of Generative AI (GAI). With the current strides in Graphics Processing Units (GPUs), training and deploying deep generative models has become more accessible. Concurrently, advancements in edge computing have facilitated leveraging GAI's potential across various applications in the Internet of Things (IoT). This paper delves into the possibilities of amalgamating GAI with IoT technology to forge innovative solutions addressing shortcomings in diverse IoT domains. Specifically, it explores how GAI can mitigate challenges stemming from inadequate and incomplete data in IoT systems by generating synthetic data for training other deep models. Furthermore, it examines GAI's role in tailoring content produced by IoT devices and other collaborative applications. It also scrutinizes real-world implementations of this synergy. Finally, the article concludes by outlining the current limitations of GAI technology for IoT applications and proposing avenues for future improvement.
Keywords
Generative Pre-Trained Transformer (GPT), Graphics Processing Units (GPUs), Internet of Things (IoT), Generative AI (GAI), Data Privacy and Security.
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