<![CDATA[This systematic literature review explores the application of Artificial Intelligence of Things (AIoT) in Assistive Technology designed to support individuals with disabilities. Out of an initial 267 articles, 38 studies were selected based on inclusion criteria and quality assessment. The review identifies the dominant machine learning models used in AIoT-based assistive technology solutions. Most research focuses on visual impairments, revealing a significant gap in addressing cognitive, psychological, and degenerative disabilities. Various IoT devices such as wearables, sensors, exoskeletons, and smart wheelchairs are employed to provide adaptive, real-time, and personalized assistance. Key methodological limitations include reliance on simulated data, small sample sizes, and lack of field validation. Technical challenges such as device interoperability and accessibility also hinder implementation. These findings highlight the need for more inclusive research involving direct participation of end-users to develop effective, accessible, and scalable AIoT-based assistive technologies that enhance the quality of life for people with disabilities.]]>
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