# Optional: Notify admin for review if adminReviewEnabled: sendToReviewQueue(sensorID, description)
## 4 Implementation Details
\begin{tabular}{c} **Partial**. Grafana expects at \\ real-time visualization of metrics \\ (widely used for live IoT data \\ dashboards [53]), but accessible \\ real-time feedback is limited [54]. \\ Screen readers do not \\ automatically announce new data \\ points on a chart. Grafana has \\ plans to improve this, but as of \\ now, any real-time accessible \\ output (like a textual update) \\ would require \\ manual configuration. \\ \end{tabular}  \\ \hline
**AI-Enhanced** & \begin{tabular}{c} **Yes**.-LLM-generated \\ descriptions. A core feature of \\ AccessiDashboard is its use of AI \\ to produce rich textual \\ descriptions of data in real time. \\ Each incoming sensor feed is \\ connected to a Large Language \\ Model, which generates \\ **Users** \\ \end{tabular}  & \ \begin{tabular}{c} **No** (auto-generated text, but not \\ AI/LLM). Azimuth provides \\ automatically generated textual \\ descriptions of dashboards, but it \\ does not employ machine learning or \\ LLMs for this. Instead, it uses \\ rule-based templates and data \\ analysis to create descriptions. These \\ complementary descriptions are \\ generated algorithmically (using the \\ provided data JSON), so while they \\ offer useful insights (like “Category X \\ has the highest value Y”), they lack \\ the more nuanced narrative that an \\ AI might provide. \\ \end{tabular}  & \begin{tabular}{c} **No**. Grafana does not include any \\ AI-driven description capability. \\ It provides no native feature to \\ summarizes for charts. Any \\ descriptive text for a panel must \\ be written and added manually \\ by the dashboard creator. \\ Essentially, visually impaired \\ users only get whatever labels or \\ captions a human \\ provided—Grafana itself does not \\ produce explanatory narratives \\ about the data. \\ \end{tabular}  \\ \hline
**WCAG** & \begin{tabular}{c} **High**—Built to meet WCAG 2.1 \\ AA. Accessibility is a \\ foundational design goal for \\ AccessiDashboard. It uses \\ semantic HTML5, proper ARIA \\ roles, and keyboard navigation. \\ Headings are in logical order, \\ regions/landmarks are properly \\ labeled, every interactive element \\ is keyboard-accessible, and color \\ contrast is checked automatically. \\ In short, it aims to exceed WCAG \\ 2.1 AA guidelines, not just \\ minimally comply. \\ \end{tabular}  & \ \begin{tabular}{c} **High** (best-practice adherence). \\ While the Azimuth paper does not \\ explicitly claim a WCAG \\ conformance level, the system was \\ designed with accessibility guidelines \\ in mind. The dashboard generated by \\ accessibility is another known \\ age--some controls or panels \\ cannot be fully used via keyboard \\ alone, though work is underway \\ to fix these (adding \\ skip-to-content links, fixing focus \\ traps, etc.). \\ \end{tabular}  & \begin{tabular}{c} **Moderate** (partial compliance). \\ Grafana is partially conformant \\ with WCAG 2.1 Level AA as of \\ 2023 [54]. This means some parts \\ of Grafana meet the guidelines, \\ but others do not. Keyboard \\ accessibility is another known \\ gap—some controls or panels \\ cannot be fully used via keyboard \\ alone, though work is underway \\ to fix these (adding \\ skip-to-content links, fixing focus \\ traps, etc.). \\ \end{tabular}  \\ \hline
**Valtimodal** & \begin{tabular}{c} **Yes**—rich multimodal output. \\ AccessiDashboard presents data \\ through multiple synchronized \\ modalities. Alongside the usual \\ visual charts/graphs, it provides \\ text-first alternatives: structured \\ data tables, bullet-list summaries \\ of sensor readings, and narrative \\ descriptions generated by AI. \\ This multimodal design means \\ sighted users and visually \\ impaired users have parallel \\ access to the information—charts \\ for those who can see them, and \\ text/tables/narratives for those \\ using screen readers. \\ \end{tabular}  & \