Raveenthiran, GSivarajah, KKugathasan, VChandrasiri, SMohamed Riyal, A. ARajendran, K2024-11-082024-11-082024-07-25G. Raveenthiran, K. Sivarajah, A. A. Mohamed Riyal, V. Kugathasan, S. Chandrasiri and K. Rajendran, "Revolutionalize Your Learning Experience with EQU ACCESS," 2024 International Conference on Electrical, Computer and Energy Technologies (ICECET, Sydney, Australia, 2024, pp. 1-6, doi: 10.1109/ICECET61485.2024.10698521.979-8-3503-9591-4https://rda.sliit.lk/handle/123456789/3826This paper introduces a novel approach aimed at enhancing online education by placing a central focus on students' emotional well-being and improving their learning experiences. The approach integrates four key machine learning technologies: behavioral expression analysis, a personalized chatbot for emotional support, voice stress detection, and visual content description. Through empirical findings, the study illustrates the effectiveness of these methods in bolstering students' emotional well-being and academic performance. By providing a roadmap for the advancement of online education and emotional support, this research holds promise for delivering substantial benefits to learners worldwide. The study showcases notable advancements in online education, reporting a 30% rise in perceived emotional support and a 25% increase in overall satisfaction. The personalized emotional support chatbot achieved an 85% accuracy in addressing students' emotional needs, while voice stress detection boasted a 90% accuracy in identifying anxiety. Additionally, visual content description led to a 20% improvement in comprehension. These findings highlight the approach's potential to elevate both emotional well-being and academic performance in online learners.enVisualizationElectric potentialAccuracyEducationAnxiety disordersMachine learningChatbotsArticle10.1109/ICECET61485.2024.10698521