Next-Generation Edge Computing: Leveraging Ai-Driven Iot For Autonomous, Real-Time Decision Making And Cyber security

Therein lies a reason for the fast growth of edge computing: the proliferation of IoT devices, which sets the stage for autonomous, real-time decision-making in various applications. This paper explores the convergence of artificial intelligence with edge computing architectures to enhance IoT systems and, consequently, achieve faster and efficient processing at the network edge. Here, we introduce a new architecture that leverages AI-powered algorithms to process and analyze data in real-time to allow for instant, automatic responses in critical situations. This work, meanwhile, addresses the growing risk of cybersecurity in this decentralized environment by embedding strong security protocols, specially designed for edge networks. We demonstrate through experiments that, with our system, there will be a significant improvement in the accuracy of decisions with enhanced system resilience against cyber threats. The results show that this new architecture in edge computing holds great potential for the massive industry turning around fast, secure data processing and operations, involving the next frontier of autonomous systems.

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Publication Details

Journal
Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
Published
2024-08-16
DOI
https://doi.org/10.60087/jaigs.v5i1.204
Citations
7
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
2.44
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article

Next-Generation Edge Computing: Leveraging Ai-Driven Iot For Autonomous, Real-Time Decision Making And Cyber security

Christianah Gbaja
7 citations
Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
IoT and Edge/Fog Computing
2.44
article

Next-Generation Edge Computing: Leveraging Ai-Driven Iot For Autonomous, Real-Time Decision Making And Cyber security

Christianah Gbaja
article en
7 citations

Abstract

Therein lies a reason for the fast growth of edge computing: the proliferation of IoT devices, which sets the stage for autonomous, real-time decision-making in various applications. This paper explores the convergence of artificial intelligence with edge computing architectures to enhance IoT systems and, consequently, achieve faster and efficient processing at the network edge. Here, we introduce a new architecture that leverages AI-powered algorithms to process and analyze data in real-time to allow for instant, automatic responses in critical situations. This work, meanwhile, addresses the growing risk of cybersecurity in this decentralized environment by embedding strong security protocols, specially designed for edge networks. We demonstrate through experiments that, with our system, there will be a significant improvement in the accuracy of decisions with enhanced system resilience against cyber threats. The results show that this new architecture in edge computing holds great potential for the massive industry turning around fast, secure data processing and operations, involving the next frontier of autonomous systems.

Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023Vol. 5(1)
Film Independent (US)
Openalex Percentile: Top 10%
IoT and Edge/Fog Computing
2.44
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