Real-Time Monitoring and AI-Based Control of Industrial Robots Using Cloud-Hosted Web Applications

Abstract

Intelligent control mechanisms find increasing ap- plication in the control of continuous production machines, such as industrial robotic arms, through data derived from real- time monitoring systems. These systems, made available on cloud-hosted web apps, can contribute significantly to increasing robot operation predictability and flexibility. Latency remains a limiting factor when physical control is performed remotely; this shortcoming is addressed here by a monitoring system that extracts real-time and historic robot status data, used by an artificial intelligence (AI) agent to continuously optimize the control parameters of an industrial robot operated on a local and dedicated manufacturing floor. The research comprises three principal components: a real-time robotic monitoring system, an AI-based robot control system, and a public-facing web app that visualizes robot information and conveys control commands to the robotic control system. High-frequency and low-latency WebSocket communication between the web app and both monitoring and control systems ensures near-seamless and real- time robotic operation control. Remote data visualization and control functionality can ultimately support predictive robot maintenance in Industry 4.0 production settings.