Digital Equity and Embedded AI: Ensuring Accessibility in Smart City Infrastructure
Keywords:
Digital Equity, Embedded AI, Smart City Infrastructure, Algorithmic Bias, Accessibility Design, Universal Design, Participatory DesignAbstract
An array of embedded AI systems becoming widespread in the urban infrastructure puts society at a critical point of juncture with a promise of significantly enhancing the quality of life of all citizens and, at the same time, promoting the worsening of the current inequalities. This detailed review of how algorithm-based implementation of embedded AI use in traffic management, community safety, and utility systems will inevitably introduce or exacerbate social divisions by being biased or not truly algorithmic, by being digital and not designed to be user-friendly. The article provides actionable frameworks that the embedded system architecture can apply to provide equitable benefits of smart cities, based on experiences of successful implementation in digitally inclusive cities. Among the important findings, it can be stated that strategic platform architecture choices, general design principles, and community-oriented development procedures play a crucial role in developing actually smart urban systems that act as bridges to an opportunity instead of barriers to involvement. The article addresses some crucial issues, such as the fact that there is a problem of algorithmic bias in the field of facial recognition and pedestrian detection and the need to design a multi-sensory interface that would accommodate a wide range of abilities. The article also highlights the fact that digital equity is not an additional feature of smart city development but a mandatory condition of sustainable urban change and indicates that inclusive embedded AI platforms offer high technical quality and equitable deliverables.
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