# Optional: Notify admin for review if adminReviewEnabled: sendToReviewQueue(sensorID, description)
## 5 Discussion  
Following the implementation of AccessiDashboard, we reflected on its effectiveness, the value of AI-generated descriptions, and the practical implications of deploying an inclusive IoT dashboard at scale. Our contribution advances the state of the art by introducing a dedicated, accessibility-first platform--AccessiDashboard--purpose-built to support real-time, inclusive IoT data exploration. In contrast to existing solutions such as Azimuth, which generates rule-based textual summaries from static dashboard specifications, and Grafana, which requires manual effort to meet even basic accessibility standards, AccessiDashboard integrates accessibility as a core design principle rather than a supplemental feature. It dynamically connects each live sensor feed to a Large Language Model (LLM), producing WCAG-compliant, context-aware textual narratives that evolve with the data in real time. Crucially, a human-in-the-loop validation mechanism enables administrators to review and refine AI-generated outputs, ensuring both reliability and editorial oversight. This architecture--combining automation with ethical safeguards--streamlines inclusive design workflows and reduces the maintenance burden typically associated with accessibility. The result is a scalable and sustainable dashboarding solution that delivers timely, rich insights to blind or visually impaired users, fully aligned with the experience provided to sighted users. While AccessiDashboard leverages AI to enhance the accessibility of environmental and device data, especially for users with visual impairments, we acknowledge the \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline \multirow{2}{*}{**Feature**} & \multicolumn{2}{c}{**AccessiDashboard**} & \multirow{2}{*}{**Azimuth (Accessible Dashboard Prototype)**} & \multirow{2}{*}{**Grafana (General Dashboard Platform)**} \\  & **(AI-Enhanced IoT Dashboard)** & & \\ \hline \multirow{8}{*}{
\begin{tabular}{c} **Human-in-the-Loop** \\ **Validation** \\ **(for** \\ **Accessibility**)** \\ \end{tabular} } & **Yes.** AccessiDashboard includes a human oversight mechanism for its AI-generated content. Administrators can review the long descriptions produced by the AI and adjust or approve them before they reach end-users. This \"human-in-the-loop\" approach ensures that any errors or awkward phrasing from the AI can be corrected, and it provides accountability—important since the narratives are automatically generated. & **No** (fully automated). Azimuth’s model is to generate accessible dashboards automatically from a specification. There is not a dedicated step for human validation of the generated textual descriptions. The descriptions are generated by deterministic templates and logic, and a “review” step was not built into the pipeline. If changes are needed, it would require modifying the code or template rather than a simple admin oversight, nor any specialized review interface for accessibility. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._potential risks associated with automated outputs. In particular, AI-generated textual summaries--though designed to be informative and screen-reader friendly--may introduce bias, overgeneralizations, or contextual inaccuracies that could have consequences in high-stakes environments. To address these concerns, the platform includes several built-in safeguards. First, all AI-generated interpretations are accompanied by explicit disclaimers that inform users of the automated nature of the content. For instance, a visual and screen-reader-accessible prompt states: _\"The detailed environmental analyses below are based on real IoT sensor inputs. The text descriptions were automatically generated by AI to enhance clarity and accessibility. These interpretations are meant to assist human understanding, but they may not capture all scientific nuances and should not replace expert judgment.\"_ This ensures transparency and helps users interpret AI-enhanced content as assistive rather than definitive.