Object Recognition with Machine Learning: Case Study of Demand-Responsive Service

Digital accessibility in the era of artificial intelligence—Bibliometric analysis and systematic review

“…Watters et al (2020) integrated an Alexa smart speaker and custom Alexa Skill for natural language interaction, a Talking LabQuest with AI for data collection and analysis, and a Raspberry Pi for coordination, effectively combining AI techniques with components to create a virtual AI lab assistant for enhanced laboratory assistance. In a study by Lin et al (2019), machine learning and deep learning techniques, particularly neural networks, were harnessed for image recognition using YOLOv3, a real-time image recognition model, for object recognition and notification. In addition, chatbot technology was implemented using the LINE platform, demonstrating the integration of AI methodologies in both image recognition and chatbot development.…”

“…Additionally, Hezam et al ( 2023) utilized a hybrid multi-criteria decision-making method to prioritize digital technologies for enhancing transportation accessibility for people with disabilities, addressing barriers, and selecting technologies through an uncertain decision-making framework. Furthermore, Lu et al (2020) aimed to aid people with disabilities in operating tractors, ensuring safe operation when consciousness and limb movements are inconsistent, whereas Lin et al (2019) focused on providing wheelchair-accessible bus rides for people with disabilities. The INSENSION Platform for Personalized Assistance of Non-symbolic Interaction for individuals with profound intellectual and multiple disabilities (PIMD), developed by Kosiedowski et al (2020), supports independence by recognizing non-symbolic behaviors and collecting contextual information through video, audio, and sensor data.…”