A systematic literature review on vision-based human event recognition in smart classrooms: identifying significant events and their applications

The field of vision-based human event recognition in smart environments has emerged as a thriving and successful discipline, with extensive efforts in research and development driving notable progress. This progress has not only yielded valuable insights but also practical applications across various domains. Within this context, human actions, activities, interactions, and behaviors are all considered as events of interest in smart environments. However, when focusing on smart classrooms, a lack of unified consensus on the definition of "human event" poses a significant challenge for educators, researchers, and developers. This lack of agreement hinders their ability to precisely identify and classify specific situations that are relevant to the educational context. To address this challenge, the aim of this paper is to conduct a systematic literature review of significant events, with a particular emphasis on their applications in assistive technology. The review encompasses a comprehensive analysis of 227 published documents spanning from 2012 to 2022. It delves into key algorithms, methodologies, and applications of vision-based event recognition in smart environments. As a primary outcome, the review identifies the most significant events, categorizing them according to single-person behavior, multiple-person interactions, or object-person interactions, examining their practical applications within the educational context. The paper concludes with a discussion on the relevance and practicality of vision-based human event recognition in smart classrooms, especially in the post-COVID era.