Improve Analytics with operational insights and temporal pattern panels

This commit is contained in:
Smittix
2026-02-19 12:59:39 +00:00
parent cbe5faab3b
commit 02a94281c3
5 changed files with 579 additions and 82 deletions

View File

@@ -1,23 +1,25 @@
"""Analytics dashboard: cross-mode summary, activity sparklines, export, geofence CRUD."""
from __future__ import annotations
import csv
import io
import json
from flask import Blueprint, Response, jsonify, request
import app as app_module
from utils.analytics import (
"""Analytics dashboard: cross-mode summary, activity sparklines, export, geofence CRUD."""
from __future__ import annotations
import csv
import io
import json
from datetime import datetime, timezone
from flask import Blueprint, Response, jsonify, request
import app as app_module
from utils.analytics import (
get_activity_tracker,
get_cross_mode_summary,
get_emergency_squawks,
get_mode_health,
)
from utils.flight_correlator import get_flight_correlator
from utils.geofence import get_geofence_manager
from utils.temporal_patterns import get_pattern_detector
)
from utils.alerts import get_alert_manager
from utils.flight_correlator import get_flight_correlator
from utils.geofence import get_geofence_manager
from utils.temporal_patterns import get_pattern_detector
analytics_bp = Blueprint('analytics', __name__, url_prefix='/analytics')
@@ -66,13 +68,172 @@ def analytics_squawks():
})
@analytics_bp.route('/patterns')
def analytics_patterns():
"""Return detected temporal patterns."""
return jsonify({
'status': 'success',
'patterns': get_pattern_detector().get_all_patterns(),
})
@analytics_bp.route('/patterns')
def analytics_patterns():
"""Return detected temporal patterns."""
return jsonify({
'status': 'success',
'patterns': get_pattern_detector().get_all_patterns(),
})
@analytics_bp.route('/insights')
def analytics_insights():
"""Return actionable insight cards and top changes."""
counts = get_cross_mode_summary()
tracker = get_activity_tracker()
sparklines = tracker.get_all_sparklines()
squawks = get_emergency_squawks()
patterns = get_pattern_detector().get_all_patterns()
alerts = get_alert_manager().list_events(limit=120)
top_changes = _compute_mode_changes(sparklines)
busiest_mode, busiest_count = _get_busiest_mode(counts)
critical_1h = _count_recent_alerts(alerts, severities={'critical', 'high'}, max_age_seconds=3600)
recurring_emitters = sum(1 for p in patterns if float(p.get('confidence') or 0.0) >= 0.7)
cards = []
if top_changes:
lead = top_changes[0]
direction = 'up' if lead['delta'] >= 0 else 'down'
cards.append({
'id': 'fastest_change',
'title': 'Fastest Change',
'value': f"{lead['mode_label']} ({lead['signed_delta']})",
'label': 'last window vs prior',
'severity': 'high' if lead['delta'] > 0 else 'low',
'detail': f"Traffic is trending {direction} in {lead['mode_label']}.",
})
else:
cards.append({
'id': 'fastest_change',
'title': 'Fastest Change',
'value': 'Insufficient data',
'label': 'wait for activity history',
'severity': 'low',
'detail': 'Sparklines need more samples to score momentum.',
})
cards.append({
'id': 'busiest_mode',
'title': 'Busiest Mode',
'value': f"{busiest_mode} ({busiest_count})",
'label': 'current observed entities',
'severity': 'medium' if busiest_count > 0 else 'low',
'detail': 'Highest live entity count across monitoring modes.',
})
cards.append({
'id': 'critical_alerts',
'title': 'Critical Alerts (1h)',
'value': str(critical_1h),
'label': 'critical/high severities',
'severity': 'critical' if critical_1h > 0 else 'low',
'detail': 'Prioritize triage if this count is non-zero.',
})
cards.append({
'id': 'emergency_squawks',
'title': 'Emergency Squawks',
'value': str(len(squawks)),
'label': 'active ADS-B emergency codes',
'severity': 'critical' if squawks else 'low',
'detail': 'Immediate aviation anomalies currently visible.',
})
cards.append({
'id': 'recurring_emitters',
'title': 'Recurring Emitters',
'value': str(recurring_emitters),
'label': 'pattern confidence >= 0.70',
'severity': 'medium' if recurring_emitters > 0 else 'low',
'detail': 'Potentially stationary or periodic emitters detected.',
})
return jsonify({
'status': 'success',
'generated_at': datetime.now(timezone.utc).isoformat(),
'cards': cards,
'top_changes': top_changes[:5],
})
def _compute_mode_changes(sparklines: dict[str, list[int]]) -> list[dict]:
mode_labels = {
'adsb': 'ADS-B',
'ais': 'AIS',
'wifi': 'WiFi',
'bluetooth': 'Bluetooth',
'dsc': 'DSC',
'acars': 'ACARS',
'vdl2': 'VDL2',
'aprs': 'APRS',
'meshtastic': 'Meshtastic',
}
rows = []
for mode, samples in (sparklines or {}).items():
if not isinstance(samples, list) or len(samples) < 4:
continue
window = max(2, min(12, len(samples) // 2))
recent = samples[-window:]
previous = samples[-(window * 2):-window]
if not previous:
continue
recent_avg = sum(recent) / len(recent)
prev_avg = sum(previous) / len(previous)
delta = round(recent_avg - prev_avg, 1)
rows.append({
'mode': mode,
'mode_label': mode_labels.get(mode, mode.upper()),
'delta': delta,
'signed_delta': ('+' if delta >= 0 else '') + str(delta),
'recent_avg': round(recent_avg, 1),
'previous_avg': round(prev_avg, 1),
'direction': 'up' if delta > 0 else ('down' if delta < 0 else 'flat'),
})
rows.sort(key=lambda r: abs(r['delta']), reverse=True)
return rows
def _count_recent_alerts(alerts: list[dict], severities: set[str], max_age_seconds: int) -> int:
now = datetime.now(timezone.utc)
count = 0
for event in alerts:
sev = str(event.get('severity') or '').lower()
if sev not in severities:
continue
created_raw = event.get('created_at')
if not created_raw:
continue
try:
created = datetime.fromisoformat(str(created_raw).replace('Z', '+00:00'))
except ValueError:
continue
if created.tzinfo is None:
created = created.replace(tzinfo=timezone.utc)
age = (now - created).total_seconds()
if 0 <= age <= max_age_seconds:
count += 1
return count
def _get_busiest_mode(counts: dict[str, int]) -> tuple[str, int]:
mode_labels = {
'adsb': 'ADS-B',
'ais': 'AIS',
'wifi': 'WiFi',
'bluetooth': 'Bluetooth',
'dsc': 'DSC',
'acars': 'ACARS',
'vdl2': 'VDL2',
'aprs': 'APRS',
'meshtastic': 'Meshtastic',
}
filtered = {k: int(v or 0) for k, v in (counts or {}).items() if k in mode_labels}
if not filtered:
return ('None', 0)
mode = max(filtered, key=filtered.get)
return (mode_labels.get(mode, mode.upper()), filtered[mode])
@analytics_bp.route('/export/<mode>')

View File

@@ -23,12 +23,112 @@
}
}
.analytics-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(140px, 1fr));
gap: var(--space-3, 12px);
margin-bottom: var(--space-4, 16px);
}
.analytics-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(140px, 1fr));
gap: var(--space-3, 12px);
margin-bottom: var(--space-4, 16px);
}
.analytics-insight-grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(210px, 1fr));
gap: var(--space-3, 12px);
}
.analytics-insight-card {
background: var(--bg-card, #151f2b);
border: 1px solid var(--border-color, #1e2d3d);
border-radius: var(--radius-md, 8px);
padding: 10px;
display: flex;
flex-direction: column;
gap: 4px;
}
.analytics-insight-card.low {
border-color: rgba(90, 106, 122, 0.5);
}
.analytics-insight-card.medium {
border-color: rgba(74, 163, 255, 0.45);
}
.analytics-insight-card.high {
border-color: rgba(214, 168, 94, 0.55);
}
.analytics-insight-card.critical {
border-color: rgba(226, 93, 93, 0.65);
}
.analytics-insight-card .insight-title {
font-size: 10px;
text-transform: uppercase;
letter-spacing: 0.04em;
color: var(--text-dim, #5a6a7a);
}
.analytics-insight-card .insight-value {
font-size: 16px;
font-weight: 700;
color: var(--text-primary, #e0e6ed);
line-height: 1.2;
}
.analytics-insight-card .insight-label {
font-size: 10px;
color: var(--text-secondary, #9aabba);
}
.analytics-insight-card .insight-detail {
font-size: 10px;
color: var(--text-dim, #5a6a7a);
}
.analytics-top-changes {
margin-top: 12px;
}
.analytics-change-row {
display: flex;
align-items: center;
gap: 10px;
padding: 7px 0;
border-bottom: 1px solid var(--border-color, #1e2d3d);
font-size: 10px;
}
.analytics-change-row:last-child {
border-bottom: none;
}
.analytics-change-row .mode {
min-width: 84px;
color: var(--text-primary, #e0e6ed);
font-weight: 600;
}
.analytics-change-row .delta {
min-width: 48px;
font-family: var(--font-mono, monospace);
}
.analytics-change-row .delta.up {
color: var(--accent-green, #38c180);
}
.analytics-change-row .delta.down {
color: var(--accent-red, #e25d5d);
}
.analytics-change-row .delta.flat {
color: var(--text-dim, #5a6a7a);
}
.analytics-change-row .avg {
color: var(--text-dim, #5a6a7a);
}
.analytics-card {
background: var(--bg-card, #151f2b);
@@ -180,11 +280,57 @@
max-width: 60px;
}
.analytics-correlation-pair .confidence-fill {
height: 100%;
background: var(--accent-green, #38c180);
border-radius: 2px;
}
.analytics-correlation-pair .confidence-fill {
height: 100%;
background: var(--accent-green, #38c180);
border-radius: 2px;
}
.analytics-pattern-item {
padding: 8px;
border-bottom: 1px solid var(--border-color, #1e2d3d);
display: flex;
flex-direction: column;
gap: 4px;
}
.analytics-pattern-item:last-child {
border-bottom: none;
}
.analytics-pattern-item .pattern-main {
display: flex;
justify-content: space-between;
align-items: center;
gap: 8px;
}
.analytics-pattern-item .pattern-mode {
font-size: 10px;
font-weight: 600;
color: var(--text-primary, #e0e6ed);
text-transform: uppercase;
letter-spacing: 0.04em;
}
.analytics-pattern-item .pattern-device {
font-size: 10px;
color: var(--text-dim, #5a6a7a);
font-family: var(--font-mono, monospace);
}
.analytics-pattern-item .pattern-meta {
display: flex;
gap: 10px;
font-size: 10px;
color: var(--text-dim, #5a6a7a);
flex-wrap: wrap;
}
.analytics-pattern-item .pattern-confidence {
color: var(--accent-green, #38c180);
font-weight: 600;
}
/* Geofence zone list */
.geofence-zone-item {

View File

@@ -21,21 +21,25 @@ const Analytics = (function () {
}
}
function refresh() {
Promise.all([
fetch('/analytics/summary').then(r => r.json()).catch(() => null),
fetch('/analytics/activity').then(r => r.json()).catch(() => null),
fetch('/alerts/events?limit=20').then(r => r.json()).catch(() => null),
fetch('/correlation').then(r => r.json()).catch(() => null),
fetch('/analytics/geofences').then(r => r.json()).catch(() => null),
]).then(([summary, activity, alerts, correlations, geofences]) => {
if (summary) renderSummary(summary);
if (activity) renderSparklines(activity.sparklines || {});
if (alerts) renderAlerts(alerts.events || []);
if (correlations) renderCorrelations(correlations);
if (geofences) renderGeofences(geofences.zones || []);
});
}
function refresh() {
Promise.all([
fetch('/analytics/summary').then(r => r.json()).catch(() => null),
fetch('/analytics/activity').then(r => r.json()).catch(() => null),
fetch('/analytics/insights').then(r => r.json()).catch(() => null),
fetch('/analytics/patterns').then(r => r.json()).catch(() => null),
fetch('/alerts/events?limit=20').then(r => r.json()).catch(() => null),
fetch('/correlation').then(r => r.json()).catch(() => null),
fetch('/analytics/geofences').then(r => r.json()).catch(() => null),
]).then(([summary, activity, insights, patterns, alerts, correlations, geofences]) => {
if (summary) renderSummary(summary);
if (activity) renderSparklines(activity.sparklines || {});
if (insights) renderInsights(insights);
if (patterns) renderPatterns(patterns.patterns || []);
if (alerts) renderAlerts(alerts.events || []);
if (correlations) renderCorrelations(correlations);
if (geofences) renderGeofences(geofences.zones || []);
});
}
function renderSummary(data) {
const counts = data.counts || {};
@@ -85,14 +89,18 @@ const Analytics = (function () {
}
}
function renderSparklines(sparklines) {
const map = {
adsb: 'analyticsSparkAdsb',
ais: 'analyticsSparkAis',
wifi: 'analyticsSparkWifi',
bluetooth: 'analyticsSparkBt',
dsc: 'analyticsSparkDsc',
};
function renderSparklines(sparklines) {
const map = {
adsb: 'analyticsSparkAdsb',
ais: 'analyticsSparkAis',
wifi: 'analyticsSparkWifi',
bluetooth: 'analyticsSparkBt',
dsc: 'analyticsSparkDsc',
acars: 'analyticsSparkAcars',
vdl2: 'analyticsSparkVdl2',
aprs: 'analyticsSparkAprs',
meshtastic: 'analyticsSparkMesh',
};
for (const [mode, elId] of Object.entries(map)) {
const el = document.getElementById(elId);
@@ -109,9 +117,101 @@ const Analytics = (function () {
const points = data.map((v, i) =>
(i * step).toFixed(1) + ',' + (h - (v / max) * (h - 2)).toFixed(1)
).join(' ');
el.innerHTML = '<svg viewBox="0 0 ' + w + ' ' + h + '" preserveAspectRatio="none"><polyline points="' + points + '"/></svg>';
}
}
el.innerHTML = '<svg viewBox="0 0 ' + w + ' ' + h + '" preserveAspectRatio="none"><polyline points="' + points + '"/></svg>';
}
}
function renderInsights(data) {
const cards = data.cards || [];
const topChanges = data.top_changes || [];
const cardsEl = document.getElementById('analyticsInsights');
const changesEl = document.getElementById('analyticsTopChanges');
if (cardsEl) {
if (!cards.length) {
cardsEl.innerHTML = '<div class="analytics-empty">No insight data available</div>';
} else {
cardsEl.innerHTML = cards.map(c => {
const sev = _esc(c.severity || 'low');
const title = _esc(c.title || 'Insight');
const value = _esc(c.value || '--');
const label = _esc(c.label || '');
const detail = _esc(c.detail || '');
return '<div class="analytics-insight-card ' + sev + '">' +
'<div class="insight-title">' + title + '</div>' +
'<div class="insight-value">' + value + '</div>' +
'<div class="insight-label">' + label + '</div>' +
'<div class="insight-detail">' + detail + '</div>' +
'</div>';
}).join('');
}
}
if (changesEl) {
if (!topChanges.length) {
changesEl.innerHTML = '<div class="analytics-empty">No change signals yet</div>';
} else {
changesEl.innerHTML = topChanges.map(item => {
const mode = _esc(item.mode_label || item.mode || '');
const deltaRaw = Number(item.delta || 0);
const trendClass = deltaRaw > 0 ? 'up' : (deltaRaw < 0 ? 'down' : 'flat');
const delta = _esc(item.signed_delta || String(deltaRaw));
const recentAvg = _esc(item.recent_avg);
const prevAvg = _esc(item.previous_avg);
return '<div class="analytics-change-row">' +
'<span class="mode">' + mode + '</span>' +
'<span class="delta ' + trendClass + '">' + delta + '</span>' +
'<span class="avg">avg ' + recentAvg + ' vs ' + prevAvg + '</span>' +
'</div>';
}).join('');
}
}
}
function renderPatterns(patterns) {
const container = document.getElementById('analyticsPatternList');
if (!container) return;
if (!patterns || patterns.length === 0) {
container.innerHTML = '<div class="analytics-empty">No recurring patterns detected</div>';
return;
}
const modeLabels = {
adsb: 'ADS-B',
ais: 'AIS',
wifi: 'WiFi',
bluetooth: 'Bluetooth',
dsc: 'DSC',
acars: 'ACARS',
vdl2: 'VDL2',
aprs: 'APRS',
meshtastic: 'Meshtastic',
};
const sorted = patterns
.slice()
.sort((a, b) => (b.confidence || 0) - (a.confidence || 0))
.slice(0, 20);
container.innerHTML = sorted.map(p => {
const confidencePct = Math.round((Number(p.confidence || 0)) * 100);
const mode = modeLabels[p.mode] || (p.mode || '--').toUpperCase();
const period = _humanPeriod(Number(p.period_seconds || 0));
const occurrences = Number(p.occurrences || 0);
const deviceId = _shortId(p.device_id || '--');
return '<div class="analytics-pattern-item">' +
'<div class="pattern-main">' +
'<span class="pattern-mode">' + _esc(mode) + '</span>' +
'<span class="pattern-device">' + _esc(deviceId) + '</span>' +
'</div>' +
'<div class="pattern-meta">' +
'<span>Period: ' + _esc(period) + '</span>' +
'<span>Hits: ' + _esc(occurrences) + '</span>' +
'<span class="pattern-confidence">' + _esc(confidencePct) + '%</span>' +
'</div>' +
'</div>';
}).join('');
}
function renderAlerts(events) {
const container = document.getElementById('analyticsAlertFeed');
@@ -206,10 +306,25 @@ const Analytics = (function () {
if (el) el.textContent = val;
}
function _esc(s) {
if (typeof s !== 'string') s = String(s == null ? '' : s);
return s.replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;');
}
function _esc(s) {
if (typeof s !== 'string') s = String(s == null ? '' : s);
return s.replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;');
}
function _shortId(value) {
const text = String(value || '');
if (text.length <= 18) return text;
return text.slice(0, 8) + '...' + text.slice(-6);
}
function _humanPeriod(seconds) {
if (!isFinite(seconds) || seconds <= 0) return '--';
if (seconds < 60) return Math.round(seconds) + 's';
const mins = seconds / 60;
if (mins < 60) return mins.toFixed(mins < 10 ? 1 : 0) + 'm';
const hours = mins / 60;
return hours.toFixed(hours < 10 ? 1 : 0) + 'h';
}
return { init, destroy, refresh, addGeofence, deleteGeofence, exportData };
})();

View File

@@ -2,10 +2,10 @@
<div id="analyticsMode" class="mode-content">
{# Analytics Dashboard Sidebar Panel #}
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Summary</span>
<span class="collapse-icon">&#9660;</span>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Summary</span>
<span class="collapse-icon">&#9660;</span>
</h3>
<div class="section-content">
<div class="analytics-grid" id="analyticsSummaryCards">
@@ -55,13 +55,31 @@
<div class="card-sparkline" id="analyticsSparkMesh"></div>
</div>
</div>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Mode Health</span>
<span class="collapse-icon">&#9660;</span>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Operational Insights</span>
<span class="collapse-icon">&#9660;</span>
</h3>
<div class="section-content">
<div class="analytics-insight-grid" id="analyticsInsights">
<div class="analytics-empty">Insights loading...</div>
</div>
<div class="analytics-top-changes">
<div class="analytics-section-header">Top Changes</div>
<div id="analyticsTopChanges">
<div class="analytics-empty">No change signals yet</div>
</div>
</div>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Mode Health</span>
<span class="collapse-icon">&#9660;</span>
</h3>
<div class="section-content">
<div class="analytics-health" id="analyticsHealth"></div>
@@ -77,13 +95,25 @@
<div class="squawk-emergency" id="analyticsSquawkPanel">
<div class="squawk-title">Active Emergency Codes</div>
<div id="analyticsSquawkList"></div>
</div>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Recent Alerts</span>
</div>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Temporal Patterns</span>
<span class="collapse-icon">&#9660;</span>
</h3>
<div class="section-content">
<div id="analyticsPatternList">
<div class="analytics-empty">No recurring patterns detected</div>
</div>
</div>
</div>
<div class="section">
<h3 class="section-header collapsible" onclick="toggleSection(this)">
<span>Recent Alerts</span>
<span class="collapse-icon">&#9660;</span>
</h3>
<div class="section-content">

View File

@@ -6,16 +6,42 @@ from typing import Any
from utils.alerts import get_alert_manager
from utils.recording import get_recording_manager
from utils.temporal_patterns import get_pattern_detector
IGNORE_TYPES = {'keepalive', 'ping'}
DEVICE_ID_FIELDS = (
'device_id',
'id',
'mac',
'mac_address',
'address',
'bssid',
'station_mac',
'client_mac',
'icao',
'callsign',
'mmsi',
'uuid',
'hash',
)
def process_event(mode: str, event: dict | Any, event_type: str | None = None) -> None:
if event_type in IGNORE_TYPES:
return
if not isinstance(event, dict):
return
device_id = _extract_device_id(event)
if device_id:
try:
get_pattern_detector().record_event(device_id=device_id, mode=mode)
except Exception:
# Pattern tracking should not break ingest pipeline
pass
try:
get_recording_manager().record_event(mode, event, event_type)
except Exception:
@@ -27,3 +53,22 @@ def process_event(mode: str, event: dict | Any, event_type: str | None = None) -
except Exception:
# Alert failures should never break streaming
pass
def _extract_device_id(event: dict) -> str | None:
for field in DEVICE_ID_FIELDS:
value = event.get(field)
if value is None:
continue
text = str(value).strip()
if text:
return text
nested_candidates = ('target', 'device', 'source', 'aircraft', 'vessel')
for key in nested_candidates:
nested = event.get(key)
if isinstance(nested, dict):
nested_id = _extract_device_id(nested)
if nested_id:
return nested_id
return None