IoT-Enabled Assistive Learning for Differently-Abled Students

Ensuring inclusive education for differently-abled students remains a persistent challenge in today’s digital learning ecosystem. While Artificial Intelligence (AI) enhances personalization and adaptive learning, accessibility gaps continue to limit participation for learners with disabilities. This research explores the convergence of the Internet of Things (IoT) and AI to build an inclusive, low-cost, and multimodal assistive framework integrated with the LearnSphere platform. The proposed ESP32-based module provides tactile feedback, LED visual cues, voice navigation, and text-to-speech capabilities to enable seamless interaction with e-learning content. The layered system architecture—spanning IoT device, application, and cloud intelligence layers—facilitates real-time feedback, adaptive learning, and accessibility customization. Preliminary evaluations emphasize improvements in autonomy, usability, and engagement among differently-abled learners. This study demonstrates that IoT–AI integration can transform e-learning into a more inclusive, interactive, and equitable environment.