Empowering Accessibility: IoT-Driven Smart Buildings for Elderly and Disabled Individuals

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Abstract

This study aims to examine the attitudes of elderly and disabled individuals in Saudi Arabia toward Internet of Things (IoT)-enabled smart home technologies, with specific attention to the influence of demographic variables. The research employed a descriptive survey design, utilizing an online questionnaire distributed to a stratified random sample of 249 participants. Stratification ensured balanced representation across gender, age, educational attainment, employment status, and economic background. Statistical analyses, including Scheffé’s post hoc test, revealed generally positive attitudes toward IoT adoption, primarily driven by perceived benefits related to enhanced quality of life, personal safety, and autonomy. Significant differences were identified across several demographic variables: married individuals, employed participants, those with higher education, higher-income groups, and individuals aged 30 to 45 all reported more favorable attitudes. Similarly, individuals with disabilities expressed stronger acceptance compared to their elderly counterparts. In contrast, gender differences were not statistically significant. These findings highlight the need for targeted, inclusive strategies that promote the adoption of IoT technologies across diverse social groups. The study contributes to a deeper understanding of how demographic characteristics shape technology acceptance and underscores the urgency of designing accessible, user-centered smart home systems. Recommendations emphasize public awareness initiatives, affordability measures, and inclusive design practices contributing to digital equity and aligning with the broader objectives of Saudi Vision 2030 for sustainable urban development.

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APA

Alshboul, Z., Hamadneh, B. M., Alqarni, T. M., Aljunaeidia, B. Z., & Khadum, M. (2025). Empowering Accessibility: IoT-Driven Smart Buildings for Elderly and Disabled Individuals. International Journal of Advanced Computer Science and Applications, 16(7), 1027–1034. https://doi.org/10.14569/IJACSA.2025.0160797

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