Design and Development of Smart Wearable Technology Enhanced Learning for Specially Abled Students

Smart gadget use has made traditional one-way teaching techniques less likely to effectively support students with disabilities, which is a major concern for educators. In the light of these considerations, the current study represents an effort to create an intelligent, interactive educational system. As a result, we develop a smart watch wearable technology based on gestures to provide specially abled students enhanced learning services. In order to promote student interaction and attraction in the classroom, these wearable gadgets (smart watches) also precisely catch hand gestures of students with special needs and promptly respond to teachers. Additionally, using a variety of physical data from smart watches on students with disabilities, it is possible, using deep learning data analysis, to identify the key components of the learning process. Using cutting-edge deep learning models, we have discovered a visual voice and hand gesture recognition method in this work. This enables instantaneous alterations by teachers and suggests ways for students with disabilities to engage in multi-learning and imaginative thinking. It is specifically the smart interactive watch’s responsibility to track students’ physical activity and interaction outcomes in order to provide teachers with feedback. Furthermore, an illustrative system was used to exhibit the efficacy of the proposed method to have the ability to improve learning and teaching for both teachers and specially abled students.