Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Review

Abstract

According to the World Health Organization, about 15% of the world’s population has some form of disability. Assistive Technology, in this context, contributes directly to the overcoming of difficulties encountered by people with disabilities in their daily lives, allowing them to receive education and become part of the labor market and society in a worthy manner. Assistive Technology has made great advances in its integration with Artificial Intelligence of Things (AIoT) devices. AIoT processes and analyzes the large amount of data generated by Internet of Things (IoT) devices and applies Artificial Intelligence models, specifically, machine learning, to discover patterns for generating insights and assisting in decision making. Based on a systematic literature review, this article aims to identify the machine-learning models used across different research on Artificial Intelligence of Things applied to Assistive Technology. The survey of the topics approached in this article also highlights the context of such research, their application, the IoT devices used, and gaps and opportunities for further development. The survey results show that 50% of the analyzed research address visual impairment, and, for this reason, most of the topics cover issues related to computational vision. Portable devices, wearables, and smartphones constitute the majority of IoT devices. Deep neural networks represent 81% of the machine-learning models applied in the reviewed research.

Implementation of AI-Based Assistive Technologies for Learners with Physical Disabilities in Areas of Innovation and Special Schools: A Practical Design Thinking Approach

“…Advancements of technologies in the area of disabilities has evolved over time from the use of Assistive communication, mobility and visual technologies; to the integration of Artificial Intelligence of Things (AIoT) devices that employee the power of artificial intelligence and machine learning in the enhancement of the ATs (de Freitas et al, 2022). The AIoTs consume data gathered over the internet and algorithms utilized in monitoring the persons with disability by creating solutions that extend the usability of their physical frame into a virtual environment that augments the reality of the user in interacting with Assistive Technologies (Kirongo et al, 2019).…”

“…When applied to Assistive Technologies (AT), Artificial Intelligence (AI) enables PWDs through solutions designed for mobility and navigation, applied to persons living with physical and visual challenges. Medical aspects of PWDs is critical, and the application of eMedicine, telemedicine, mobile medicine so-lutions inculcated with AI has enabled health monitoring of PWDs (de Freitas et al, 2022) facing terminal and critical illnesses through the digitization and automation of the detection, monitoring, diagnosis, and prescription of the medical conditions while ensuring the monitoring of those PWDs with ing ailments including the sending of messages to remind them specific times for taking their medication. AI has been applied to solve challenges related to cognitive, visual, and communication systems that employ robotics, AI and ML techniques for ease of longevity of life among sick and elderly PWDs.…”