# Optional: Notify admin for review if adminReviewEnabled: sendToReviewQueue(sensorID, description)
#### 3.2.4 Multi-Modal Data Representation  
AccessiDashboard's user interface supports multiple modes of data representation to accommodate different user needs and preferences, all within the same platform.  
The main modes include:  
* Visual Chart Mode: The traditional dashboard view with charts, graphs, and minimal text. This mode is similar to conventional dashboards and is primarily intended for sighted users or those who prefer graphical representation. Each chart includes alt text and a caption, but the interface assumes the user can perceive the visual elements. This is the only mode that does not rely on AI generation.
* Bullet Trend List Mode: In this AI-generated textual mode, the latest sensor readings or summarized trends are presented as bullet points. For example, instead of a  
Figure 2: Pseudocode for OpenAI-based long description generation. This routine gathers sensor data, constructs a natural language prompt, calls the OpenAI API for interpretation, validates the output, and stores it for use in the accessible dashboard interface.  
graph showing the last 10 readings, the dashboard might display a list of items such as: \"Temperature: 22.4 \({}^{\circ}\)C--moderate level detected; Humidity: 48.1%--comfortable range; Air Quality Index: 94--moderate air quality.\" Each bullet provides a concise, plain-language summary of a parameter. This format is accessible for screen reader users and presents clearly separated data points in a linear sequence, enabling efficient comprehension.
* Data Grid Table Mode: Also AI-generated, this mode presents data in a tabular format similar to a spreadsheet. It may list the last N readings for each sensor in a table with columns like Timestamp, Temperature, Humidity, etc. This structured layout enables users to navigate cell by cell and compare values across time or across sensors. It leverages semantic HTML table markup, ensuring relationships between headers and data remain accessible and clear to assistive technologies.
* Detailed Analysis Mode: This mode provides a narrative, paragraph-based summary where the AI generates long-form textual descriptions of data trends and contextual insights. Instead of displaying raw values, the user receives a coherent and context-rich interpretation of the data--similar to an automated report or commentary powered by a large language model.  
All these modes are kept in sync with the underlying data. If a new sensor value arrives, the visual chart updates, the bullet list updates, the table updates, and even the narrative could be refreshed if needed. The user can switch between modes using a simple control in the UI (a dropdown or set of buttons to select the view type).  
Providing multiple modes addresses different cognitive styles [40] and situations. A blind user might primarily use the bullet or analysis modes, but a low-vision user might still glance at charts while also having the bullet list available for exact numbers. A sighted user might generally use the visual mode but occasionally read the detailed analysis for insights that might not be immediately obvious from the raw graph.  
By designing these modes within one system, we also ensure that adding a new sensor or data source automatically makes that data available in all formats. There is no separate maintenance for an \"accessible version\" versus the \"regular version\"--they are one unified system, just different views. This is a key aspect of inclusive design: one platform that adapts to the user, rather than parallel platforms.