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Analytics and Reporting

EAS Station includes a built-in analytics engine that tracks alert trends, detects anomalies in alert patterns, and aggregates system metrics over time. This data is accessible from the analytics dashboard and via REST API.

Accessing the Analytics Dashboard

Navigate to /analytics in the web interface (also linked from the main navigation as Analytics).

The dashboard displays:

  • Alert volume over time — hourly, daily, and weekly alert counts
  • Severity distribution — breakdown by Extreme / Severe / Moderate / Minor
  • Event type breakdown — which event codes (TOR, FFW, SVR, etc.) are most frequent
  • Geographic coverage — which FIPS codes appear most in received alerts
  • Anomaly indicators — alerts that fall outside normal patterns
  • Trend lines — moving averages showing whether alert activity is increasing or decreasing

Understanding Metric Categories

The analytics engine aggregates data into three types:

Category Description
alert_volume Count of alerts received per time period
alert_severity Distribution of alert severity levels
alert_events Frequency of specific EAS event codes

Metrics are rolled up at three periods: hourly, daily, and weekly.

Trend Analysis

The Trends section shows whether alert activity is statistically rising, falling, or stable over recent periods.

How to read trends:

  • Upward trend — Alert activity is above the historical baseline. This may indicate a developing weather pattern or a period of elevated hazards.
  • Downward trend — Activity is below baseline. May reflect seasonal quiet periods.
  • Stable — Activity is within normal range.

Trends are calculated using a linear regression over the selected time window (default: 7 days).

Anomaly Detection

The anomaly detector flags alert patterns that deviate significantly from historical norms. Anomalies appear in the Anomalies tab of the analytics dashboard.

Examples of flagged anomalies:

  • Sudden spike in alert volume (e.g., 5x the daily average)
  • An unusual event code appearing for the first time
  • Multiple alerts for the same FIPS code in a short window

Anomaly severity levels:

Level Description
Low Minor deviation, informational
Medium Notable departure from baseline
High Significant spike requiring attention
Critical Extreme outlier — likely a real emergency event

API Access to Analytics Data

All analytics data is available via the REST API. Authenticate with an API key (see API Key Management).

Get Metric Snapshots

GET /api/analytics/metrics

Query parameters:

Parameter Description Default
category Metric category (alert_volume, alert_severity, etc.) All
name Metric name All
period Aggregation period (hourly, daily, weekly) All
days Lookback window in days 7
limit Maximum results 100

Example:

curl -H "X-API-Key: <key>" \
  "https://your-eas-station.example.com/api/analytics/metrics?category=alert_volume&period=daily&days=30"

Get Trend Data

GET /api/analytics/trends

Returns trend direction and slope for each metric category over the selected window.

Get Detected Anomalies

GET /api/analytics/anomalies

Query parameters:

Parameter Description Default
days Lookback window 7
severity Filter by severity level All
limit Maximum results 50

Compliance and Export Reports

PDF Compliance Reports

Navigate to Compliance (/admin/compliance) to generate FCC-ready documentation:

  1. Select a date range using the date pickers.
  2. Click Export PDF to download a formatted compliance report including:
    • Alert receipt log with timestamps
    • Required Weekly Test (RWT) record
    • System health summary
    • Broadcast history

CSV Export

  1. Go to Alert History (/admin/alerts).
  2. Apply any filters (date range, severity, event type).
  3. Click Export CSV to download the filtered alert list.

Statistics Tab

The Statistics tab on the dashboard provides a quick summary:

  • Total alerts received (last 24 hours / 7 days / 30 days)
  • Alert severity breakdown as a bar chart
  • Top 10 event codes by frequency
  • Top 5 FIPS codes by alert count

Data Retention

Analytics metric snapshots are retained based on their aggregation period:

Period Default retention
Hourly 30 days
Daily 365 days
Weekly 5 years

Raw alert records in the cap_alerts table are retained indefinitely until manually cleaned. Use Admin → Maintenance → Cleanup to purge old records.

Integrating with External BI Tools

The REST API makes it straightforward to feed analytics data into external tools such as Grafana, Kibana, or Power BI.

Grafana example using the Simple JSON datasource plugin:

  1. Install the Infinity datasource plugin in Grafana.
  2. Add a new datasource of type Infinity.
  3. Set the base URL to https://your-eas-station.example.com.
  4. Add a custom header: X-API-Key = <your-key>.
  5. Create a panel using the /api/analytics/metrics endpoint with period=daily.

Troubleshooting

Dashboard shows "No data"

  • Analytics data is populated by background workers. If the system was just installed, allow at least 24 hours for trend data to accumulate.
  • Verify the poller service is running:
    sudo systemctl status eas-station-poller

API returns empty metrics array

  • Check the days parameter — default is 7. If the system has been running for less than 7 days, reduce this value.
  • Confirm that alerts are being received (Alert History should have entries).

Trends always show "stable" even during known events

  • Trend calculations require a baseline of at least 7 days of data. During the first week of operation, trends may not reflect short-term spikes accurately.
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This document is served from docs/guides/ANALYTICS_AND_REPORTING.md in the EAS Station installation.