AI-Driven Ergonomic Assessment and Optimization of Classrooms and Offices at Public Sector University

Abstract

With more AI in classrooms and workplaces, public universities now have new ways to deal with ergonomic issues. It analyses 65 studies focused on using AI to review and boost ergonomics in both learning and working environments. The purpose was to understand whether using AI such as machine learning, computer vision and neural networks, can improve physical, mental and environmental ergonomics for everyone in the school. Analysis found that most of the main outcome areas had moderate to good effect sizes: pain was reduced (Hedges’ g = 0.58), productivity was raised (g = 0.47), being in the classroom was more engaging (g = 0.51) and environmental quality was increased (g = 0.63). Significant differences were found in the data (p < 0.01) and the amount of heterogeneity remained low to moderate (between 30% and 42%) among different institutional and geographical groups, proving that AI works similarly everywhere. AI tools were able to promptly highlight ergonomic tips, handle environment-related work processes and adapt to new learning requirements at work. Although the results were in favor of bone marrow transplantation, it was apparent that many studies didn’t use controls for participant blinding and concealing the patient’s group allocation which made the research less reliable. It was found that using AI for ergonomics in public sector universities is a practical and important way to boost comfort, mental abilities and make workplaces better. Compatible models demonstrate that implementing AI in schools and education support systems is very beneficial. More studies should be carried out to learn about long-term gains, ethical issues and cost-saving effects to make sure smart ergonomic systems are sustainable and applied equally in all academic and administrative university offices.