## PRD: Screen Blanking Event Analytics

This PRD defines the requirements for analyzing screen blanking events logged by AIVA, focusing on deriving insights into user behavior and system performance.

### GPM-050: Aggregate Screen Blanking Counts by Day
**Goal:** To provide a daily count of screen blanking events.
**Acceptance Criteria:**
- A new table or view exists containing daily screen blanking event counts.
- The table/view includes columns for date and total blanking events.
- Data is aggregated correctly based on the logged screen blanking events.
**Files:** `analytics/models/screen_blanking_counts.sql`
**Spawns:** Screen Blanking Duration Analysis

### GPM-051: Analyze Screen Blanking Reasons
**Goal:** To understand the distribution of reasons for screen blanking.
**Acceptance Criteria:**
- A report or dashboard displays the frequency of each recorded screen blanking reason (user interaction, video playback, inactivity timeout, etc.).
- The report is filterable by date range.
- The report clearly visualizes the proportion of each reason.
**Files:** `analytics/reports/screen_blanking_reasons.py`
**Spawns:** Correlate Screen Blanking Reasons with User Activity

### GPM-052: Calculate Average Screen Blanking Frequency per User
**Goal:** To determine the average number of screen blanking events per user per day.
**Acceptance Criteria:**
- A new metric is calculated representing the average screen blanking frequency per user per day.
- The metric is accessible via an API endpoint.
- The calculation correctly accounts for users with varying levels of activity.
**Files:** `analytics/api/screen_blanking_metrics.py`
**Spawns:** Identify Users with Unusual Screen Blanking Behavior

### GPM-053: Create a Dashboard for Screen Blanking Event Monitoring
**Goal:** To provide a centralized view of screen blanking event data.
**Acceptance Criteria:**
- A dashboard displays key metrics related to screen blanking events, including daily counts, reason distribution, and average user frequency.
- The dashboard is interactive, allowing users to drill down into specific data points.
- The dashboard is visually appealing and easy to understand.
**Files:** `ui/dashboards/screen_blanking_dashboard.jsx`
**Spawns:** Alerting on Anomalous Screen Blanking Patterns

### GPM-054: Implement Data Retention Policy for Screen Blanking Logs
**Goal:** To manage the storage costs associated with screen blanking event logs.
**Acceptance Criteria:**
- An automated process is implemented to delete screen blanking logs older than a specified period (e.g., 90 days).
- The data retention policy is configurable.
- The data deletion process is efficient and does not impact system performance.
**Files:** `data_pipeline/screen_blanking_data_retention.py`
**Spawns:** Archiving Historical Screen Blanking Data

### GPM-055: Identify Time of Day Trends for Screen Blanking Events
**Goal:** To determine if there are specific times of day when screen blanking events are more frequent.
**Acceptance Criteria:**
- A visualization (e.g., a heatmap) displays the frequency of screen blanking events by time of day.
- The visualization is filterable by day of the week.
- The visualization clearly shows peak times for screen blanking events.
**Files:** `analytics/visualizations/screen_blanking_time_trends.py`
**Spawns:** Predict Screen Blanking Events Based on Time and User Activity

### GPM-056: Correlate Screen Blanking with System Resource Usage
**Goal:** To investigate whether screen blanking is correlated with high or low system resource usage (CPU, memory, etc.).
**Acceptance Criteria:**
- A report or analysis compares screen blanking event frequency with system resource usage metrics.
- The report identifies any statistically significant correlations.
- The report includes visualizations to illustrate the relationships between screen blanking and resource usage.
**Files:** `analytics/correlation/screen_blanking_resource_usage.py`
**Spawns:** Optimize System Performance Based on Screen Blanking Patterns
