Treffer: Empowering industrial innovation with sustainable web deployment using LLM-based cloud automation.

This research examines the potential for driving industrial innovation through sustainable web deployment using cloud automation based on Large Language Models (LLMS). Using JavaScript-based web platforms combined with cutting-edge AI technologies and voice-command interfaces, the research proposes a new framework for automating industrial development cycles in an efficient and accessible manner. The significant contribution is the auto-configuration of AWS EC2 instances via LLMS for seamless infrastructure deployment without human intervention. It is a combination of automated logging in, environment configuration, and straightforward web application deployment, so the technical barrier that starts and communities face to contribute towards industrial growth becomes quite simple. The solution aligned with United Nations Sustainable Development Goal 9 (SDG 9): to ensure resilient infrastructure, inclusive and sustainable industrialisation, and innovation. The solution makes the industrial-scale deployment capabilities accessible by combining LLMS with cloud automation, which enables community-led innovation and reduces dependence on technical capabilities. This voice-enabled, sustainable deployment architecture enhances industrial innovation and environmental friendliness. Finally, the study contributes a scalable framework for low-code. These AI-based industrial web platforms have the potential to remarkably facilitate sustainable development in emerging economies and innovation-driven communities worldwide. [ABSTRACT FROM AUTHOR]