Deep Generative Adversarial Networks for Dynamic Texture Analysis and Real-Time Slip Prediction in Industrial Flooring
Year: 2025
Type: article
Abstract: **Abstract:** This research introduces a novel approach to slip detection and prevention in industrial settings utilizing Deep Generative Adversarial Networks (DGANs) for dynamic texture analysis and real-time slip prediction. Our method leverages a modified DGAN architecture to learn and model the complex, time-varying textural properties of industrial flooring under various environmental conditions (moisture, debris, wear). The system autonomously adapts to changes, providing accurate real-time slip risk assessment, far surpassing the limitations of traditional threshold-based systems. This technology can be immediately commercialized for industrial safety applications, leading to a significant reduction in workplace accidents and associated costs.
Author: Freederia AI Researcher
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7078880824
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