The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer’s disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central.

This article unveils MoSIoT (Modeling Scenarios of the Internet of Things), an innovative framework meticulously designed to simulate IoT systems, addressing the nuanced needs of individuals with hearing impairments. Grounded in the quality-of-life framework proposed by Verdugo et al., MoSIoT has been enriched and evolved to integrate and manage a spectrum of deafness technologies, thereby marking a significant enhancement in the overall quality of life for the affected individuals. The focal point of this work is the advocacy for accessibility and well-being through technology-driven and inclusive solutions. The presented case study provides a comprehensive insight into the transformative impact of MoSIoT, highlighting improvements in key quality of life dimensions such as “Interpersonal Relationships”, “Emotional Well-Being”, and “Personal Development”. These enhancements underscore the pivotal role of continuous innovation and inclusive design in the evolution of assistive technologies. The article delves into the intricacies of the system’s implementation, exploring its service-based architecture, which ensures modularity, scalability, and adaptability to diverse user needs and technological advancements. Furthermore, the potential for future research and development in this field is discussed, emphasizing the endless possibilities and avenues for enhancing assistive technology and promoting an inclusive and accessible future for individuals with disabilities.

The growing prevalence of Autism Spectrum Disorder (ASD) underscores the need for adaptive educational tools that promote inclusion. While a variety of digital resources are available, their fragmentation limits data unification and comprehensive longitudinal monitoring of student progress. This study introduces a personalized Learning Management System (LMS) called SpectrumSphere that incorporates Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), robotics, and Augmentative and Alternative Communication (AAC) to provide real-time, data-driven personalization, objective progress tracking, and enhanced collaboration between teachers and parents. This study has evaluated the intention of adoption of our LMS using an extended Technology Acceptance Model (TAM) with 30 special education teachers in different schools from the Valencian Community. Our findings show that perceived usefulness, perceived ease of use, and computer self-efficacy are the strongest predictors of teachers’ behavioral intention to adopt technology, while perceived external control operates indirectly by strengthening computer self-efficacy, highlighting that intuitive interfaces, robust institutional support and infrastructure, and comprehensive professional development are crucial to enable educators to harness SpectrumSphere’s adaptive recommendations.

The global prevalence of visual disabilities is increasing, significantly impacting the quality of life and social inclusion of those affected. Existing technologies, while helpful, continue to face challenges in terms of cost, accessibility, and real-time effectiveness. Individuals with visual impairments face significant barriers in their daily interactions with the environment, limiting their independence and social participation. The lack of adaptable and personalized solutions that address these specific needs remains a significant barrier. This study presents an extension of the Modeling Scenarios of the Internet of Things (MoSIoT) framework, a platform designed to improve the quality of life of people with disabilities by enhancing their interactions with IoT devices. The enhanced MoSIoT framework uses artificial intelligence and augmented reality technologies to significantly improve navigation and environmental interaction, enhancing the well-being of individuals with visual impairments. The proposed enhancements include advanced object detection, scene recognition, and augmented reality geolocation, all tailored to provide a richer and more autonomous user experience. A case study conducted as part of this research illustrates the practical application of these technologies in a real-world scenario, demonstrating how they can be used to support individuals with visual impairments in various everyday contexts. Practical tests conducted using tools such as YOLO for object recognition and Azure IoT for device integration have significantly improved user autonomy and quality of life. The results show that the enhanced framework can facilitate more effective environmental interaction and better social inclusion, highlighting its potential for implementation across different contexts and devices.