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Home / Archives / Volume-6 / Issue-3 / Article-8

Volume - 6 | Issue - 3 | september 2024

AI-Driven Edge Computing for Risk Prediction in IIoT Environments Open Access
N. Bhalaji   107
Pages: 283-292
Cite this article
Bhalaji, N.. "AI-Driven Edge Computing for Risk Prediction in IIoT Environments." Journal of IoT in Social, Mobile, Analytics, and Cloud 6, no. 3 (2024): 283-292
Published
18 October, 2024
Abstract

This research presents an industrial risk prediction model for multimodal data based on edge computing, aiming at real-time and efficient industrial site risk prediction. Most AI-driven applications require high-end servers to perform complicated AI tasks, resulting in significant energy consumption in IIoT contexts. This study will discuss intelligent edge computing, an emerging technology that may cut energy usage while processing AI tasks, and how to construct green AI technology for IIoT applications. The study also analyses AI technology, and existing technologies to determine the optimal way for generating risk prediction in the IIOT environment.

Keywords

Industrial Risk Prediction High-End Servers IoT IIoT Edge Computing AI Technology

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