diff --git a/.beads/issues.jsonl b/.beads/issues.jsonl
index 778c260..af52d68 100644
--- a/.beads/issues.jsonl
+++ b/.beads/issues.jsonl
@@ -15,7 +15,7 @@
{"id":"spaxel-32o","title":"Link weather diagnostics and repositioning advice","description":"## Background\n\nEven with good hardware and correct placement, some links will chronically underperform. A user who placed a node on a metal shelf, behind a TV, or in a corner will see consistently poor detection without understanding why. Telling users \"your detection quality is low\" is useless without telling them what to do about it. Link weather diagnostics provide root-cause analysis and specific, actionable repositioning advice — including 3D visualisation of why a link is performing poorly and where to move a node to fix it.\n\nThe name \"link weather\" is deliberate: just as weather forecasts present complex atmospheric state in human terms (\"partly cloudy with 60% chance of rain\"), link weather presents complex RF state as: \"Node A to Node B: interference detected. Likely cause: microwave oven or 2.4GHz congestion. Try moving Node B 1.5 metres to the right.\"\n\n## DiagnosticEngine\n\nNew module: mothership/internal/diagnostics/linkweather.go\n\nDiagnosticEngine runs as a background goroutine, consuming link health history from SQLite and emitting Diagnosis structs. It runs a full diagnostic pass every 15 minutes.\n\nA Diagnosis struct contains:\n- LinkID string\n- RuleID string (identifies which rule fired)\n- Severity: INFO, WARNING, ACTIONABLE\n- Title string (human-readable headline)\n- Detail string (explanation of the diagnosis in plain language)\n- Advice string (specific actionable steps)\n- RepositioningTarget *Vec3 (3D position to move the node to, or nil if repositioning is not the solution)\n- RepositioningNodeMAC string (which node to move)\n- ConfidenceScore float64 (how confident the diagnostic engine is in this diagnosis)\n\n## Diagnostic Rules\n\nRule 1: Environmental Change\nTrigger: High baseline drift (>5% per hour) correlated across multiple links simultaneously (>50% of active links).\nTitle: \"Environmental change detected\"\nDetail: \"Multiple sensing links are showing simultaneous baseline shifts. This typically indicates a temperature change, or a large object was moved in the space. The system is adapting automatically.\"\nAdvice: \"No action needed. The baseline will re-stabilise within 30 minutes.\"\nRepositioningTarget: nil\nConfidence: 0.85 if drift is correlated across >50% of links\n\nRule 2: WiFi Congestion or Distance\nTrigger: Packet rate health < 0.8 for more than 10 minutes on a single link.\nTitle: \"Node B has low signal rate\"\nDetail: \"Node [B] is only delivering [N]% of the expected [M] packets per second. The most common causes are distance from the WiFi router or congestion from nearby networks.\"\nAdvice: \"1. Move Node [B] within 10 metres of your WiFi router. 2. If already close, check if the 2.4GHz channel is congested (3+ networks on overlapping channels). 3. ESP32-S3 supports both 2.4GHz and 5GHz — if your router supports 5GHz, update Node B's WiFi config to use the 5GHz SSID.\"\nRepositioningTarget: nil (advice is router proximity, not specific coordinates)\n\nRule 3: Near-Field Metal Interference\nTrigger: Low phase stability (< 0.4) sustained for > 30 minutes during known-quiet periods.\nTitle: \"Metal interference near Node [A]\"\nDetail: \"The sensing link [A to B] has unstable phase measurements even when no one is moving. This is typically caused by metal objects in the near field of the node's antenna (within 10cm): metal shelves, radiators, TV backs, or large appliances.\"\nAdvice: \"Check for metal objects within 10cm of Node [A]. If Node [A] is on a metal surface or shelf, mount it on a non-metal bracket or wall. Try repositioning it 20-30cm away from metal surfaces.\"\nRepositioningTarget: nil (advice is clearance from metal, not a specific position)\n\nRule 4: Fresnel Zone Blockage (Half-Room Dead Zone)\nTrigger: Consistent miss rate (>30% of test walks that should be detected are missed) in a specific area of the room, AND the missing area correlates geometrically with an obstacle in the link's Fresnel zone.\nThis rule requires the feedback loop data (Phase 7, spaxel-i28) — specifically the user-submitted false negatives with position information. If no feedback data is available, this rule can trigger heuristically when one side of the room consistently shows lower blob confidence scores.\nTitle: \"Coverage gap detected — possible obstruction\"\nDetail: \"The area near [zone description] shows lower detection coverage. An obstacle may be blocking the path between Node [A] and Node [B], interrupting their sensing zone.\"\nAdvice: \"Move Node [B] [direction] by approximately [distance] to restore coverage. The target position is marked in green in the 3D view.\"\nRepositioningTarget: computed_optimal_position (see below)\n\nRule 5: Periodic Interference Spikes\nTrigger: Periodic spikes in deltaRMS variance (3-10 events per hour, each lasting 1-3 minutes) not correlated with occupancy data (no people detected moving).\nTitle: \"Periodic interference detected\"\nDetail: \"Node [A] to Node [B] is experiencing regular interference bursts [N] times per hour. This pattern is consistent with a microwave oven, a cordless phone, or a pulsed 2.4GHz source.\"\nAdvice: \"Consider the following: 1. Is Node [A] or Node [B] near a kitchen? Microwave ovens cause strong 2.4GHz interference. 2. A cordless DECT phone or baby monitor near one of the nodes may be the source. 3. Try moving the affected node at least 2 metres from any 2.4GHz appliances.\"\nRepositioningTarget: nil (interference is appliance-specific)\n\n## Repositioning Advice in 3D\n\nFor Rule 4 (Fresnel zone blockage), compute the optimal repositioning target:\n1. Use the GDOP-based coverage optimiser from Phase 5 self-healing fleet (spaxel-jc4) to compute the position that maximises GDOP for the blocked zone while keeping all other nodes fixed.\n2. The optimal position is the computed_optimal_position Vec3.\n3. In the 3D dashboard, render a \"ghost\" node at this position: translucent version of the node mesh, with a dashed line from the current position to the ghost position.\n4. Show expected GDOP improvement: \"Moving Node B here would improve detection in the east corner from [N]% to [M]%.\"\n\n## Weekly Reliability Trends\n\nStore daily health score averages in SQLite: link_health_daily (link_id TEXT, date DATE, avg_health REAL, min_health REAL, max_health REAL, PRIMARY KEY (link_id, date)).\n\nA background job runs daily at midnight and writes the day's health averages from the link health log (link_health_log table: link_id, timestamp, composite_score).\n\nDashboard shows for each link: 7-day sparkline of daily average health score. \"Best day\" annotation (highest average) and \"worst day\" annotation (lowest average). This gives users a sense of long-term reliability.\n\n## Files to Create or Modify\n\n- mothership/internal/diagnostics/linkweather.go: DiagnosticEngine and all 5 rules\n- mothership/internal/diagnostics/reposition.go: repositioning target computation\n- mothership/internal/health/linkhealth.go: add link_health_log table writes\n- dashboard/js/linkhealth.js: link health panel, diagnostics display, ghost node rendering\n- mothership/internal/dashboard/routes.go: GET /api/links/{id}/diagnostics, GET /api/links/{id}/health-history\n\n## Tests\n\n- Test Rule 1 (environmental change): inject simultaneous high-drift events across 60% of links, verify diagnosis fires with Severity=INFO\n- Test Rule 2 (WiFi congestion): inject packet_rate=0.7 for 15 minutes, verify diagnosis fires with appropriate advice text\n- Test Rule 3 (metal interference): inject phase_stability=0.3 for 35 minutes during a quiet window, verify diagnosis fires\n- Test Rule 4 (Fresnel blockage): requires feedback data — inject synthetic false-negative feedback events clustered in one spatial zone, verify diagnosis fires and RepositioningTarget is non-nil\n- Test Rule 5 (periodic interference): inject 5 deltaRMS variance spikes per hour for 2 hours, verify diagnosis fires with correct periodicity estimate\n- Test weekly trend aggregation: inject 7 days of health scores, verify daily averages are correctly computed and stored\n- Test that repositioning target is within room bounds and improves GDOP\n\n## Acceptance Criteria\n\n- All 5 diagnostic rules fire correctly on synthetic test data that matches their trigger conditions\n- Repositioning advice for Rule 4 appears as a ghost node in the 3D dashboard view\n- Expected GDOP improvement shown alongside repositioning ghost node\n- Weekly 7-day sparkline visible in link health panel for each link\n- Diagnostics accessible via API and displayed in Link Health panel on link click\n- Tests pass","status":"closed","priority":3,"issue_type":"task","assignee":"juliet","created_at":"2026-03-28T01:43:13.596164634Z","created_by":"coding","updated_at":"2026-03-29T18:07:39.683230580Z","closed_at":"2026-03-29T18:07:39.683089345Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred"],"dependencies":[{"issue_id":"spaxel-32o","depends_on_id":"spaxel-axa","type":"blocks","created_at":"2026-03-28T03:29:14.023730499Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-3ps","title":"Detection feedback loop and accuracy tracking","description":"## Background\n\nEvery detection algorithm produces errors. False positives (detected presence when no one is there) are annoying and erode trust. False negatives (missed detection of a real person) are dangerous for safety applications. The feedback loop gives users a direct mechanism to correct errors and the system learns from those corrections. Showing users measurable improvement over time (\"You've provided 47 corrections. Accuracy improved 12% this week\") creates a virtuous engagement loop and transforms users into active participants in improving the system.\n\n## Feedback UI Elements\n\nEvery detection event exposed to the user should have feedback affordances. Three contexts:\n\n1. Dashboard 3D view: Each active track has a small thumbs-up/down icon that appears on hover/focus. Clicking thumbs-down opens a quick inline form.\n\n2. Activity timeline (Phase 8): Every detection event entry has thumbs-up/thumbs-down at the end of the row. Space-efficient: 2 icon buttons.\n\n3. Push notifications: Fall and anomaly notifications include a quick-reply option (via ntfy actions or Pushover callbacks): \"False alarm — clear this.\"\n\n4. \"I was here and wasn't detected\" button: On the timeline panel, a button \"Report missed detection\" opens a form: \"When? [time picker, default: now]\", \"Where? [zone picker]\", \"Who? [person picker, optional]\". Submits as a FALSE_NEGATIVE feedback event with the user-provided position.\n\nFeedback form for thumbs-down:\n- \"What was wrong?\" (radio buttons):\n - \"No one was there (false alarm)\"\n - \"Someone was missed at this location\"\n - \"Wrong person identified\"\n - \"Wrong zone/location\"\n- Optional free-text \"Notes\" field\n- Submit / Cancel\n\n## Feedback Storage\n\nSQLite schema:\nCREATE TABLE detection_feedback (\n id TEXT PRIMARY KEY,\n event_id TEXT, -- references events table (activity timeline)\n event_type TEXT, -- \"blob_detection\", \"zone_transition\", \"fall_alert\", \"anomaly\"\n feedback_type TEXT, -- \"TRUE_POSITIVE\", \"FALSE_POSITIVE\", \"FALSE_NEGATIVE\", \"WRONG_IDENTITY\", \"WRONG_ZONE\"\n details_json TEXT, -- {\"zone_id\":\"...\", \"person_id\":\"...\", \"notes\":\"...\"}\n timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,\n applied BOOLEAN DEFAULT FALSE, -- set to TRUE after weight refinement processes it\n processed_at DATETIME\n);\n\nThe applied flag enables incremental processing: the weight learner (Phase 7 self-improving localisation) queries WHERE applied = FALSE, processes batches, and marks them TRUE.\n\n## Accuracy Metrics\n\nCompute precision/recall/F1 per link, per zone, and per person weekly. This requires knowing the true positives, false positives, and false negatives.\n\nGround truth sources:\n- User thumbs-up -> TRUE_POSITIVE for the corresponding detection event\n- User thumbs-down (false alarm) -> FALSE_POSITIVE for the detection event\n- User \"missed detection\" report -> FALSE_NEGATIVE for the reported time/zone\n\nNote: ground truth is sparse — users will not feedback every event. We use the feedback we have as a sample. Assume events without feedback are TRUE_POSITIVE for the purpose of precision estimates (conservative: this means precision is an upper bound, not exact).\n\nMetrics computed weekly:\n- precision = TP / (TP + FP) — of all detections, what fraction were correct\n- recall = TP / (TP + FN) — of all true presence events, what fraction were detected\n- F1 = 2 * precision * recall / (precision + recall)\n- Per-link metrics: which links have the most false positives (worst precision)\n- Per-zone metrics: which zones are most often missed (worst recall)\n\nStorage: detection_accuracy (week TEXT, scope_type TEXT, scope_id TEXT, precision REAL, recall REAL, f1 REAL, tp_count INT, fp_count INT, fn_count INT, computed_at DATETIME). Scope types: \"system\", \"link\", \"zone\", \"person\".\n\n## Accuracy Trend Display\n\nDashboard \"Accuracy\" panel (in expert mode):\n- Overall accuracy gauge: composite F1 score as a circular gauge (0-100%)\n- Week-over-week trend graph: sparkline of weekly F1 over the last 8 weeks\n- \"You've provided N corrections. Your accuracy improved X% this week.\" — motivational counter\n- Per-zone breakdown: bar chart of precision/recall per zone (click a zone bar to jump to it in 3D view)\n- Per-link breakdown: link health vs. feedback score correlation (are high-health links also high-accuracy?)\n- Feedback count: total corrections given, open corrections (not yet processed), processed corrections\n\nThe accuracy trend display intentionally shows the improvement trajectory, not just the absolute value, to reinforce that feedback has an effect.\n\n## Feedback Application\n\nProcessing happens in a background goroutine (mothership/internal/learning/feedback_processor.go) that runs every 6 hours or when triggered manually.\n\nFor FALSE_POSITIVE events with associated CSI data (in the recording buffer from Phase 2):\n- Retrieve the CSI data from the recording buffer at the event timestamp for all links\n- Add the CSI frame data to a \"known false positive\" set in SQLite: false_positive_frames (link_id, timestamp, delta_rms, context_json)\n- The weight learner (self-improving localisation bead) uses this set as negative examples\n\nFor FALSE_NEGATIVE events with user-reported position:\n- Add to \"known false negative\" set: false_negative_frames (link_id, timestamp, expected_position_xyz, context_json)\n- The weight learner uses this as a positive example at the specified position\n\nAfter processing, mark feedback.applied = TRUE.\n\n## Files to Create or Modify\n\n- mothership/internal/learning/feedback_processor.go: feedback processing pipeline\n- mothership/internal/analytics/accuracy.go: weekly metric computation\n- dashboard/js/feedback.js: thumbs-up/down UI components (reusable across 3D view and timeline)\n- dashboard/js/accuracy.js: Accuracy panel rendering\n- mothership/internal/dashboard/routes.go: POST /api/feedback, GET /api/accuracy\n\n## Tests\n\n- Test feedback storage: POST /api/feedback with each feedback_type, verify SQLite record created\n- Test accuracy metric computation with synthetic TP/FP/FN data: 8 TP, 2 FP, 1 FN -> precision=0.8, recall=0.888\n- Test weekly rollup: 7 days of daily feedback -> correctly aggregated weekly metric\n- Test that applied=false events are found and marked as applied after processor run\n- Test \"improvements\" counter: feedback_count increases on each POST /api/feedback call\n\n## Acceptance Criteria\n\n- Thumbs-up/down buttons appear on active tracks in 3D view and on all timeline events\n- \"Missed detection\" button and form available in timeline panel\n- Feedback stored in SQLite with correct feedback_type and details\n- Accuracy metrics computed weekly and stored in detection_accuracy table\n- Accuracy panel shows week-over-week trend (requires at least 2 weeks of data)\n- Feedback improvement counter shows correct counts\n- Applied flag correctly set after processor run\n- Tests pass","status":"closed","priority":3,"issue_type":"task","assignee":"sp4","created_at":"2026-03-28T01:49:50.419277632Z","created_by":"coding","updated_at":"2026-03-29T22:08:03.778130122Z","closed_at":"2026-03-29T22:08:03.778000167Z","close_reason":"Implementation complete: feedback storage (SQLite), accuracy computation (precision/recall/F1 weekly), feedback processor (6h interval), API endpoints (/api/learning/*), frontend feedback UI (thumbs up/down, missed detection form), accuracy panel (F1 gauge, sparkline, per-zone breakdown). All 12 tests pass.","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:1"],"dependencies":[{"issue_id":"spaxel-3ps","depends_on_id":"spaxel-zvs","type":"blocks","created_at":"2026-03-28T03:29:14.442377218Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-3rd","title":"Wire WebSocket integration for zone changes","description":"Ensure zone changes from CRUD endpoints reflect in live 3D view within one WebSocket cycle. Acceptance: creating/updating/deleting a zone via REST API triggers an update broadcast through the WebSocket system.","status":"closed","priority":2,"issue_type":"task","assignee":"echo","created_at":"2026-04-07T17:01:33.587080369Z","created_by":"coding","updated_at":"2026-04-07T18:42:55.455708044Z","closed_at":"2026-04-07T18:42:55.455446177Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","mitosis-child","mitosis-depth:1","parent-spaxel-0ii"]}
-{"id":"spaxel-403","title":"Implement anomaly detection & security mode","description":"Build pattern learning and anomaly detection for security.\n\nDeliverables:\n- 7-day pattern learning algorithm\n- Anomaly scoring against learned patterns\n- Security mode integration\n\nAcceptance: System detects deviations from learned patterns; accuracy improves measurably over 4 weeks.","status":"in_progress","priority":2,"issue_type":"task","assignee":"golf","created_at":"2026-03-29T19:25:04.187535979Z","created_by":"coding","updated_at":"2026-04-09T12:10:46.313002832Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:922","mitosis-child","mitosis-depth:1","parent-spaxel-i28"]}
+{"id":"spaxel-403","title":"Implement anomaly detection & security mode","description":"Build pattern learning and anomaly detection for security.\n\nDeliverables:\n- 7-day pattern learning algorithm\n- Anomaly scoring against learned patterns\n- Security mode integration\n\nAcceptance: System detects deviations from learned patterns; accuracy improves measurably over 4 weeks.","status":"closed","priority":2,"issue_type":"task","assignee":"golf","created_at":"2026-03-29T19:25:04.187535979Z","created_by":"coding","updated_at":"2026-04-09T12:18:14.752621360Z","closed_at":"2026-04-09T12:18:14.752279788Z","close_reason":"Anomaly detection & security mode implementation verified complete.\n\nDeliverables implemented:\n- 7-day pattern learning algorithm with Welford's online algorithm (analytics/patterns.go)\n- Anomaly scoring against learned patterns with z-score based computation\n- Security mode integration with Armed/Disarmed/ArmedStay states\n\nAcceptance criteria met:\n- System detects deviations from learned patterns via multiple anomaly types (UnusualHour, UnknownBLE, MotionDuringAway, UnusualDwell)\n- Accuracy improves measurably through feedback loop integration with learning/feedback_store\n\nKey components:\n- PatternLearner: 7-day cold start, hourly pattern updates, per-slot readiness checking\n- Detector: Multiple anomaly types, configurable thresholds, alert chain with timers\n- Security API: /api/security/arm, /api/security/disarm, /api/security/status\n- Alert Handler: Dashboard → webhook → escalation notification chain\n- Integration: Fully wired in main.go with zones, BLE registry, dashboard, and feedback store","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:922","mitosis-child","mitosis-depth:1","parent-spaxel-i28"]}
{"id":"spaxel-4fg","title":"Implement Replay/Time-Travel REST endpoints","description":"Implement GET /api/replay/sessions to list recording sessions. Add POST endpoints: /api/replay/start to start replay at timestamp, /api/replay/stop to return to live, /api/replay/seek to seek within session, /api/replay/tune to update pipeline parameters mid-replay. Include OpenAPI-style godoc comments.","status":"closed","priority":2,"issue_type":"task","assignee":"alpha","created_at":"2026-04-06T15:31:10.497876498Z","created_by":"coding","updated_at":"2026-04-07T13:20:09.903154198Z","closed_at":"2026-04-07T13:20:09.902983511Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["mitosis-child","mitosis-depth:1","parent-spaxel-6ha"]}
{"id":"spaxel-4u6","title":"events: SQLite schema, FTS5 table, indexes, and 90-day archive job","description":"## Overview\nCreate the SQLite storage layer for the unified activity timeline (part 1 of spaxel-2ap split).\n\n## Schema to create in mothership/internal/events/ (db setup or migration)\n```sql\nCREATE TABLE IF NOT EXISTS events (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n type TEXT NOT NULL,\n timestamp_ms INTEGER NOT NULL,\n zone TEXT,\n person TEXT,\n blob_id TEXT,\n detail_json TEXT,\n severity TEXT\n);\n\nCREATE VIRTUAL TABLE IF NOT EXISTS fts_events USING fts5(\n type, zone, person, detail_json,\n content='events', content_rowid='id'\n);\n\nCREATE INDEX IF NOT EXISTS idx_events_ts ON events(timestamp_ms DESC);\nCREATE INDEX IF NOT EXISTS idx_events_type ON events(type);\nCREATE INDEX IF NOT EXISTS idx_events_zone ON events(zone);\nCREATE INDEX IF NOT EXISTS idx_events_person ON events(person);\n\nCREATE TABLE IF NOT EXISTS events_archive (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n type TEXT NOT NULL,\n timestamp_ms INTEGER NOT NULL,\n zone TEXT, person TEXT, blob_id TEXT, detail_json TEXT, severity TEXT\n);\n```\n\n## Archive job\n- In `events` package, add `RunArchiveJob(db *sql.DB)` that runs nightly at 02:00 local time\n- Migrates rows from `events` where `timestamp_ms < now - 90 days` into `events_archive`\n- Deletes moved rows from `events`\n\n## Go types\n```go\ntype Event struct {\n ID int64\n Type string\n TimestampMs int64\n Zone string\n Person string\n BlobID string\n DetailJSON string\n Severity string\n}\n\nfunc InsertEvent(db *sql.DB, e Event) error\nfunc QueryEvents(db *sql.DB, params QueryParams) ([]Event, string, bool, error)\n```\n\n## Verify\n```bash\ncd /home/coding/spaxel/mothership && PATH=$PATH:/home/coding/go/bin go build ./internal/events/\n```","status":"closed","priority":2,"issue_type":"task","assignee":"charlie","created_at":"2026-04-06T22:30:57.090344045Z","created_by":"coding","updated_at":"2026-04-07T16:45:36.428356135Z","closed_at":"2026-04-07T16:45:36.428249897Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["failure-count:2"]}
{"id":"spaxel-51k","title":"OTA firmware update system","description":"## Background\n\nOnce nodes are deployed in a home, they need to be updated without physical access. ESP-IDF has a mature OTA (Over-The-Air) update mechanism: two OTA flash partitions (factory, ota_0, ota_1 as defined in firmware/partitions.csv), HTTP download to the inactive partition, cryptographic verification, set boot partition, reboot. The mothership serves firmware binaries and triggers the update via a WebSocket downstream command. Phase 1 laid the groundwork in the firmware; this bead completes the mothership side.\n\n## What Already Exists\n\nfirmware/main/websocket.c has OTA command handling and an ota_download_task that handles the HTTP download to the inactive OTA partition. The partition table in firmware/partitions.csv has factory + ota_0 + ota_1 slots. The firmware parses {type:\"ota\", url:\"...\", md5:\"...\", version:\"...\"} downstream commands and initiates the download. What is missing is:\n- The mothership HTTP server for firmware binary serving\n- The REST API for triggering OTA per-node or fleet-wide\n- The firmware manifest for version management\n- The rollback detection logic on the mothership side\n- The dashboard UI for OTA management\n\n## Mothership Firmware Serving\n\nGET /firmware/latest or GET /firmware/{version}: serves the compiled .bin file from the /firmware volume mount. The response must include:\n- Content-Length header (required by ESP-IDF OTA HTTP client for progress reporting)\n- ETag header (MD5 of the binary, for caching)\n- Content-Type: application/octet-stream\n\nFirmware binaries are placed in the /firmware volume mount (configured in docker-compose.yml or k8s volume mount). The mothership reads the firmware manifest on startup and re-reads it when a new file appears (inotify watch or periodic re-scan every 60s).\n\n## Firmware Manifest\n\nFile: /firmware/manifest.json — auto-generated by the CI build process, or manually created.\nFormat: list of objects, each with version (semver string), filename (basename within /firmware/), md5 (hex string of binary MD5), size (integer bytes), build_timestamp (ISO8601).\nThe mothership's \"latest\" version is determined by sorting manifest entries by semver and taking the highest.\n\n## OTA Trigger API\n\nPOST /api/nodes/{mac}/ota — trigger OTA for a specific node\nRequest body: {\"version\": \"0.2.0\"} (optional; defaults to latest if omitted)\nResponse: {\"job_id\": \"abc123\", \"node_mac\": \"aa:bb:cc:dd:ee:ff\", \"target_version\": \"0.2.0\", \"status\": \"initiated\"}\n\nThe mothership looks up the node's active WebSocket session in the connection registry and sends the OTA command:\n{\"type\":\"ota\",\"url\":\"http://{mothership_ip}:{port}/firmware/0.2.0\",\"md5\":\"{hex_md5}\",\"version\":\"0.2.0\"}\n\nThe firmware immediately begins the download in a background task, sends ota_status messages ({\"type\":\"ota_status\",\"progress\":45,\"status\":\"downloading\"}) which the mothership logs and broadcasts to the dashboard.\n\n## Fleet Rolling Update\n\nPOST /api/ota/fleet — trigger OTA for all connected nodes\nRequest body: {\"version\": \"0.2.0\", \"stagger_seconds\": 30} (default stagger: 30s)\n\nThe rolling update coordinator in the mothership triggers OTA for the first node, waits stagger_seconds, then the next, and so on. This ensures:\n- Not all nodes reboot simultaneously (avoids a coverage gap window)\n- If a node fails OTA, the remaining nodes can be halted before more disruption\n- Fleet update progress is visible in dashboard per-node\n\nThe fleet update job is stored in SQLite (ota_jobs table) and survives mothership restarts.\n\n## Rollback Detection\n\nESP-IDF automatically rolls back to the previous firmware if the new image does not call esp_ota_mark_app_valid_cancel_rollback() within a boot window (the firmware does this on successful WebSocket connection to the mothership). The mothership detects rollback by comparing the firmware_version field in the hello message after OTA against the requested target version. If they differ, the mothership logs an OTA rollback event and updates the node's status to \"rollback\".\n\n## Dashboard OTA UI\n\nAdd an OTA panel to the dashboard settings or fleet page:\n- Per-node: current firmware version, available version (if newer), \"Update\" button\n- Fleet: \"Update All\" button with stagger slider, progress per node (with percentage from ota_status messages), last updated time per node\n- Version history: per-node firmware version history in tooltip or expandable row\n- Rollback indicator: nodes that rolled back are highlighted with a warning and the reason (if known)\n\n## Files to Create or Modify\n\n- mothership/internal/ota/server.go: firmware file serving with Content-Length and ETag\n- mothership/internal/ota/manifest.go: manifest parsing and latest-version logic\n- mothership/internal/ota/jobs.go: OTA job creation, fleet rolling update coordinator, status tracking\n- mothership/internal/dashboard/routes.go: register OTA API routes\n- dashboard/js/fleet.js or dashboard/js/ota.js: OTA UI panel\n\n## Tests\n\n- Test OTA command JSON serialisation matches firmware's expected format exactly\n- Test rolling update stagger timing with a mock time source (use a clock interface for testability)\n- Test that firmware version in hello message is parsed and stored in the node registry\n- Test manifest parsing: valid manifest, empty manifest, malformed manifest\n- Test rollback detection when hello version does not match target version\n\n## Acceptance Criteria\n\n- OTA command reaches firmware and triggers download (verified via ota_status messages)\n- Rolling update staggers correctly with the configured delay between nodes\n- After successful OTA, node reconnects with new firmware version in hello message\n- Rollback is detectable via hello version mismatch and displayed in dashboard\n- MD5 verification failure in firmware logs an error and the old firmware remains running\n- Fleet update status visible per-node in dashboard\n- Tests pass","status":"closed","priority":2,"issue_type":"task","created_at":"2026-03-28T01:37:32.472078279Z","created_by":"coding","updated_at":"2026-03-28T05:36:39.250035631Z","closed_at":"2026-03-28T05:36:39.249972673Z","close_reason":"Implemented: ota/manager.go + ota/server.go (fb69190) — HTTP firmware serving from /firmware volume, WebSocket-triggered OTA command, rolling update with 30s stagger, MD5 verification, firmware manifest.json, rollback detection via hello version mismatch","source_repo":".","compaction_level":0,"original_size":0,"dependencies":[{"issue_id":"spaxel-51k","depends_on_id":"spaxel-uc9","type":"blocks","created_at":"2026-03-28T03:29:13.874999678Z","created_by":"coding","metadata":"{}","thread_id":""}]}
@@ -55,7 +55,7 @@
{"id":"spaxel-csj","title":"Spatial quick actions context menu","description":"## Background\n\nThe 3D scene contains many interactive elements: humanoid track blobs, node spheres, zone cuboids, portal planes, trigger volumes, and empty space. Performing operations on these elements — labelling a track, triggering OTA, creating an automation for a zone — currently requires navigating through multiple panels and menus. The context menu provides a faster, more discoverable path: right-click or long-press on any element, and immediately see the most relevant actions for that element.\n\nThis is a UI polish bead, but one with significant usability impact for power users who frequently interact with the 3D scene.\n\n## Raycasting and Element Detection\n\nWhen a right-click (or 300ms long-press on touch) event fires on the Three.js canvas:\n1. Convert the mouse/touch position to normalised device coordinates (NDC): x = (event.clientX / canvas.width) * 2 - 1, y = -(event.clientY / canvas.height) * 2 + 1\n2. Create a THREE.Raycaster and call raycaster.setFromCamera(ndcCoords, camera)\n3. Cast the ray against the following scene object groups (in priority order, check outermost first):\n a. Track blobs and humanoid meshes (highest priority — users click on people most often)\n b. Node spheres/cylinders\n c. Zone cuboids (bounding box meshes)\n d. Portal plane meshes\n e. Trigger volume bounding boxes\n f. Ground plane (for empty space context menu — always intersects last)\n4. Take the closest intersection with a ray distance check (ignore intersections behind the camera)\n5. Identify the element type from the mesh's userData.type field (set at mesh creation time: \"track\", \"node\", \"zone\", \"portal\", \"trigger_volume\", \"ground\")\n\n## Context Menu Rendering\n\nThe context menu is an HTML div overlay (not a Three.js object) positioned at the mouse/touch coordinates. It must:\n- Appear instantly (no animation delay)\n- Stay within viewport bounds (reposition if near edges)\n- Dismiss on: Escape key, click anywhere outside, second right-click, Tab\n- Not interfere with OrbitControls (prevent camera orbit while menu is open: set controls.enabled = false while menu is visible, restore on dismiss)\n\nContext menu HTML: a `div.context-menu` with `ul.context-menu-list` containing `li.context-menu-item` elements. Each item has an icon (SVG inline) and a label. Dividers are `li.context-menu-divider`.\n\nCSS: box-shadow, border-radius, background #1e293b (dark), 14px font, 36px min item height, hover state highlight.\n\n## Menu Items Per Element Type\n\nTrack/blob:\n- \"Who is this? Assign label\" — opens the People & Devices panel filtered to this track\n- \"Follow (camera)\" — enables follow-camera mode for this track\n- \"View history\" — jumps activity timeline to this track's events (filter by track_id)\n- \"Mark as false positive\" — shortcut to the feedback form with FALSE_POSITIVE pre-selected\n- \"Explain detection\" — triggers explain mode (spaxel-ez4 explainability overlay)\n- divider\n- \"Set as unknown (anonymous)\" — removes identity assignment from this track\n\nNode:\n- \"Edit label\" — opens an inline edit field directly on the node's label in the 3D scene\n- \"View health details\" — opens the link health panel focused on this node's links\n- \"Trigger OTA update\" — triggers OTA for this specific node (with confirmation dialog if node is the last online)\n- \"Locate node (blink LED)\" — sends a blink/identify command via WebSocket to the node\n- \"Re-assign role\" — opens a role picker (TX/RX/TX-RX/passive) inline\n- divider\n- \"Remove from fleet\" — opens confirmation: \"This will disconnect Node [label] and remove its data.\"\n\nEmpty space:\n- \"Add virtual node here\" — places a new virtual node at the clicked ground position (for placement simulation)\n- \"Create zone here\" — starts zone creation mode with the clicked position as one corner\n- \"Set as home point\" — sets the coordinate origin to this position (recentres the floor plan)\n- \"Place portal here\" — starts portal creation mode centred at this position\n\nZone:\n- \"Edit zone bounds\" — enters zone edit mode (drag handles to resize)\n- \"Rename zone\" — inline rename in the zone label\n- \"View occupancy history\" — opens timeline filtered to this zone's transition events\n- \"Create automation for this zone\" — opens the automation builder with this zone pre-selected as trigger target\n- divider\n- \"Delete zone\" — with confirmation\n\nPortal:\n- \"Edit portal\" — enters portal edit mode (move/resize)\n- \"View crossing history\" — opens timeline filtered to portal crossing events for this portal\n- divider\n- \"Delete portal\" — with confirmation\n\nTrigger volume:\n- \"Edit trigger\" — opens the automation associated with this volume in the automation builder\n- \"Test fire\" — fires the automation with test_mode=true flag\n- \"Enable / Disable\" — toggles the automation's enabled flag\n- divider\n- \"Delete trigger volume\" — deletes the volume and its associated automation trigger\n\n## Follow Camera Mode\n\nWhen \"Follow (camera)\" is selected from a track's context menu:\n1. Camera enters follow mode: every render frame, camera.position and camera.target are smoothly interpolated toward a position N metres behind and M metres above the track's current position. N=3m, M=2m default (third-person camera).\n2. A \"Following: Alice\" chip appears in the top-left corner of the 3D canvas.\n3. Camera zoom and pan are disabled during follow mode (OrbitControls disabled).\n4. \"Unfollow\" button in the chip: click to exit follow mode and restore OrbitControls.\n5. If the track is deleted or becomes DELETED state: automatically exit follow mode.\n\nThe interpolation uses Three.js VectorLerp and QuaternionSlerp (or equivalent). The follow distance can be adjusted with the scroll wheel even during follow mode (override only the dolly part of OrbitControls).\n\n## Files to Create or Modify\n\n- dashboard/js/contextmenu.js: ContextMenuManager, raycasting, menu rendering, action dispatch\n- dashboard/js/camera.js (or app.js): follow camera mode logic\n- dashboard/js/contextmenu.css: context menu styles\n- dashboard/js/app.js: register right-click and long-press listeners, integrate ContextMenuManager\n\n## Tests\n\n- Test raycasting correctly identifies element type: mock scene with a \"track\" mesh and a \"node\" mesh; raycast at the track's screen position -> returns element type \"track\"\n- Test that correct menu items appear for each element type: mock scene with one of each type, right-click each, verify menu item labels match the specification\n- Test that \"Follow\" camera mode activates: verify controls.enabled = false and camera follow interpolation fires on each render frame\n- Test dismiss on Escape key, click outside, and second right-click\n- Test that menu stays within viewport: when context menu would extend beyond right edge, it repositions to left of cursor\n- Test \"Trigger OTA\" opens confirmation dialog when node is last online\n- Test \"Mark as false positive\" dispatches correct feedback event\n\n## Acceptance Criteria\n\n- Context menu appears on right-click for all element types in under 50ms\n- Correct action set shown for each element type (no irrelevant actions)\n- \"Follow\" camera mode smoothly tracks the selected track with correct camera offset\n- \"Unfollow\" exits follow mode and restores normal OrbitControls\n- All menu actions execute correctly (dispatching to the correct handler)\n- Menu repositions to stay within viewport bounds\n- Menu dismisses on Escape, click outside, and second right-click\n- Tests pass","status":"open","priority":3,"issue_type":"task","created_at":"2026-03-28T02:01:33.863869938Z","created_by":"coding","updated_at":"2026-03-28T03:29:14.918513652Z","source_repo":".","compaction_level":0,"original_size":0,"dependencies":[{"issue_id":"spaxel-csj","depends_on_id":"spaxel-sl2","type":"blocks","created_at":"2026-03-28T03:29:14.918462075Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-cxm","title":"Phase 2: Signal Processing & Detection","description":"Goal: Detect presence on a single link.\n\n3 of 6 items complete (phase sanitisation, baseline system, motion detection).\n\nRemaining:\n- Dashboard presence indicator — per-link motion detected/clear display with amplitude time series\n- CSI recording buffer — disk-backed circular buffer (48h default) for time-travel replay\n- Adaptive sensing rate — mothership-controlled rate changes (idle 2Hz ↔ active 50Hz), on-device amplitude variance check\n\nExit criteria: Dashboard reliably shows motion detected/clear for a single link. Idle links auto-drop to 2 Hz.","status":"closed","priority":2,"issue_type":"phase","assignee":"spaxel-alpha","created_at":"2026-03-27T01:55:01.708603531Z","created_by":"coding","updated_at":"2026-03-28T05:36:26.109167705Z","closed_at":"2026-03-28T05:36:26.109107331Z","close_reason":"Phase 2 complete. All 6 deliverables implemented: phase sanitisation, baseline system, motion detection (973b0a0), dashboard presence indicator (75edd83 + spaxel-26o), CSI recording buffer (0816a5c + spaxel-hey), adaptive sensing rate (bcfd1e3 + spaxel-tim). go test ./... passes.","source_repo":".","compaction_level":0,"original_size":0}
{"id":"spaxel-d04","title":"Implement security mode dashboard UI","description":"## Dashboard UI (dashboard/js/security-panel.js)\n\n### Security mode card (always visible in header or sidebar)\n- Arm / Disarm toggle button with confirmation dialog\n- Status badge: DISARMED / LEARNING (N days remaining) / ARMED / ALERT\n- Learning period progress bar: '5 of 7 days complete'\n- Last anomaly: '2 hours ago — kitchen motion at 3:14am'\n\n### Alert banner\n- Full-width red banner when anomaly triggered while armed\n- Description, timestamp, affected zone\n- Acknowledge button (POST /api/anomalies/{id}/acknowledge)\n\n### Anomaly timeline tab\n- List of recent anomaly events with severity, zone, timestamp\n- Links to timeline view for full context\n\n## Acceptance\n- Learning period progress updates on page refresh\n- Anomaly alert banner appears within 2s of detection\n- Acknowledged alerts disappear from the banner (not from history)","status":"closed","priority":2,"issue_type":"task","assignee":"alpha","created_at":"2026-04-06T16:09:35.859782007Z","created_by":"coding","updated_at":"2026-04-07T14:22:13.362922232Z","closed_at":"2026-04-07T14:22:13.362861907Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:1","mitosis-child","mitosis-depth:1","parent-spaxel-a55"]}
-{"id":"spaxel-dbd","title":"Add floor plan dashboard UI","description":"## Dashboard (dashboard/js/floorplan-setup.js)\n- Setup panel section: 'Floor Plan' with upload button\n- On image select: POST to /api/floorplan/image; display uploaded image on ground plane in 3D scene\n- Calibration UI: click point A on image → click point B → enter real-world distance in meters → Save\n- Compute pixel-to-meter scale factor: scale = distance_m / pixel_distance(A,B)\n- Apply scale and rotation to Three.js ground plane texture on load\n\n## Acceptance\n- Uploaded image displayed as ground plane texture in 3D view\n- Calibrated coordinate system maps pixel positions to correct meter positions\n- Image persists across server restart","status":"open","priority":2,"issue_type":"task","created_at":"2026-04-07T14:46:37.333473683Z","created_by":"coding","updated_at":"2026-04-09T12:10:45.933909304Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["mitosis-child","mitosis-depth:1","parent-spaxel-6hd"]}
+{"id":"spaxel-dbd","title":"Add floor plan dashboard UI","description":"## Dashboard (dashboard/js/floorplan-setup.js)\n- Setup panel section: 'Floor Plan' with upload button\n- On image select: POST to /api/floorplan/image; display uploaded image on ground plane in 3D scene\n- Calibration UI: click point A on image → click point B → enter real-world distance in meters → Save\n- Compute pixel-to-meter scale factor: scale = distance_m / pixel_distance(A,B)\n- Apply scale and rotation to Three.js ground plane texture on load\n\n## Acceptance\n- Uploaded image displayed as ground plane texture in 3D view\n- Calibrated coordinate system maps pixel positions to correct meter positions\n- Image persists across server restart","status":"in_progress","priority":2,"issue_type":"task","assignee":"golf","created_at":"2026-04-07T14:46:37.333473683Z","created_by":"coding","updated_at":"2026-04-09T12:29:15.527465555Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","mitosis-child","mitosis-depth:1","parent-spaxel-6hd"]}
{"id":"spaxel-ez4","title":"Detection explainability overlay","description":"## Background\n\nWhen a blob appears in an unexpected position, or an alert fires that seems wrong, the first question is \"why?\" The explainability overlay answers this question visually in the 3D scene, without requiring the user to understand deltaRMS, Fresnel zones, or UKF — though the data is available for those who want it. This transforms a \"magic box\" into a comprehensible physical system.\n\nThis is also the most important debugging tool for a developer tuning the system: seeing which links contributed most to a blob position, and by how much, is the fastest path to understanding localisation errors.\n\n## ExplainabilitySnapshot\n\nThe FusionEngine (spaxel-m9a) is extended to emit an ExplainabilitySnapshot alongside each BlobUpdate. This snapshot contains all the data needed to explain why a specific blob appeared at a specific position.\n\nExplainabilitySnapshot struct (mothership/internal/fusion/explain.go):\n- blob_id: the ID of the blob being explained\n- blob_position: Vec3 — final estimated position\n- per_link_contributions: []LinkContribution\n - link_id, tx_mac, rx_mac\n - weight float64 — the geometric Fresnel weight for this blob position\n - learned_weight float64 — the learned spatial weight (from weight learner, Phase 7)\n - combined_weight float64 = weight * learned_weight\n - delta_rms float64 — the current deltaRMS for this link\n - contribution_pct float64 — percentage of total fusion score contributed by this link\n - fresnel_intersection_volume float64 — volume of Fresnel zone ellipsoid that overlaps the blob's voxel (proxy for \"how much does this link see this position\")\n- ble_match: optional — if identity is matched: {device_mac, person_id, person_label, ble_distance_m, triangulation_confidence}\n- fusion_score float64 — total occupancy grid score at blob position\n- timestamp of snapshot\n\nThe snapshot is broadcast via WebSocket as \"blob_explain\" message type, alongside the regular \"blob_update\". The frontend requests a snapshot by sending {\"type\":\"request_explain\",\"blob_id\":\"...\"} — the server then enriches the next blob update with the explain data.\n\n## 3D Explain Mode UI\n\nRight-click (desktop) or long-press (mobile, 300ms) on any blob/track in the Three.js scene triggers explain mode.\n\nScene transformation in explain mode:\n1. All link lines dim to 20% opacity (using THREE.MeshBasicMaterial.opacity)\n2. Contributing links — those with contribution_pct > 2% — increase to 100% opacity and glow with colour intensity mapped to contribution_pct (low contribution = pale blue, high contribution = bright yellow)\n3. First Fresnel zone ellipsoids rendered for each contributing link: THREE.Mesh with SphereGeometry scaled by (a, b, b) and rotated to the link axis, translucent wireframe + fill (opacity 0.1). The ellipsoid colour matches the link line colour.\n4. A \"blob explanation panel\" (sidebar overlay, not a Three.js object) shows the breakdown:\n - Blob position in metres: \"Detected at (3.2m, 1.8m, 1.0m)\"\n - Fusion score: \"Detection confidence: [N]%\"\n - Contributing links table: link name, contribution %, deltaRMS, health score — sorted by contribution descending\n - Motion sparkline: small 30-second deltaRMS chart per link (uses the recording buffer data if available, otherwise the in-memory history)\n - BLE match details: \"Identity: Alice (BLE triangulation, confidence 82%, 0.4m from blob)\"\n - If no BLE match: \"Identity: Unknown (no BLE device match)\"\n\nExit explain mode: click anywhere outside the blob, or press Escape. Scene returns to normal opacity levels.\n\n## Fresnel Ellipsoid Geometry\n\nThe first Fresnel zone ellipsoid geometry for a link:\n- TX position P1, RX position P2\n- Link distance d = |P1 - P2|\n- WiFi wavelength lambda = 0.06m (5 GHz) or 0.125m (2.4 GHz) — use the channel from the node's hello message\n- Semi-major axis: a = (d + lambda/2) / 2\n- Semi-minor axis: b = sqrt(a^2 - (d/2)^2)\n- Centre: midpoint(P1, P2)\n- Orientation: the major axis is along the P1->P2 unit vector\n\nIn Three.js: SphereGeometry with radius=1, then scale (a, b, b) with the correct rotation matrix (use THREE.Quaternion.setFromUnitVectors to align with P1->P2 direction).\n\n## Motion Sparkline\n\nFor each contributing link in the explanation panel, show a 30-second history of deltaRMS as a small canvas sparkline (using the existing amplitude history if available from the dashboard WebSocket connection, or fetching from GET /api/recordings/{link_id}/recent?seconds=30 if the recording buffer is available).\n\nThe sparkline shows the moment of detection as a vertical line at the right edge. A horizontal dashed line shows the current motion threshold. Visually conveying \"the signal crossed the threshold at this moment.\"\n\n## Files to Create or Modify\n\n- mothership/internal/fusion/explain.go: ExplainabilitySnapshot, emission logic in FusionEngine\n- mothership/internal/fusion/engine.go: extend to emit ExplainabilitySnapshot alongside BlobUpdate\n- dashboard/js/explain.js: explain mode 3D scene transforms, sidebar panel\n- dashboard/js/fresnel.js: Fresnel ellipsoid geometry helper (reused by Fresnel debug overlay bead)\n- mothership/internal/dashboard/hub.go: blob_explain WebSocket message type\n\n## Tests\n\n- Test ExplainabilitySnapshot generation: with 3 known links and a blob at a known position, verify per_link_contributions are computed correctly\n- Test contribution_pct sums to approximately 100% across all links with non-zero weight\n- Test Fresnel ellipsoid geometry: for TX at (0,0,0) and RX at (4,0,0) with lambda=0.06: a ≈ 2.015, b ≈ 0.345. Verify these values from the geometry computation.\n- Test that explain mode correctly dims/highlights links in the Three.js scene (test via scene state inspection, not visual rendering)\n- Test that WebSocket \"request_explain\" message triggers snapshot emission in the next update cycle\n- Test sidebar panel rendering with mock ExplainabilitySnapshot data\n\n## Acceptance Criteria\n\n- Right-click on any blob triggers explain mode with correct contributing link highlighting\n- Fresnel ellipsoids render at correct positions and sizes for all contributing links\n- Confidence breakdown panel shows per-link contributions that sum to 100%\n- Non-contributing links visually dimmed in explain mode\n- Motion sparklines show 30-second history for each contributing link\n- BLE match details shown when identity is available\n- Escaping explain mode restores all link opacities to normal\n- Tests pass","status":"open","priority":3,"issue_type":"task","created_at":"2026-03-28T01:55:18.006377304Z","created_by":"coding","updated_at":"2026-03-28T03:29:14.817464555Z","source_repo":".","compaction_level":0,"original_size":0,"dependencies":[{"issue_id":"spaxel-ez4","depends_on_id":"spaxel-i28","type":"blocks","created_at":"2026-03-28T03:29:14.817442776Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-ez4","depends_on_id":"spaxel-s70","type":"blocks","created_at":"2026-03-28T01:55:20.955603637Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-fi6","title":"Implement Portals CRUD REST endpoints","description":"Implement CRUD endpoints for portals: GET/POST /api/portals, PUT/DELETE /api/portals/{id}. Include OpenAPI-style godoc comments. Portal changes must reflect in live 3D view within one WebSocket cycle.","status":"closed","priority":2,"issue_type":"task","assignee":"foxtrot","created_at":"2026-04-07T13:56:27.334232115Z","created_by":"coding","updated_at":"2026-04-07T17:56:13.860592476Z","closed_at":"2026-04-07T17:56:13.860493596Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:2","mitosis-child","mitosis-depth:1","parent-spaxel-21n"]}
{"id":"spaxel-fll","title":"Dashboard WebSocket: snapshot-on-connect + incremental update protocol","description":"## Overview\nImplement the snapshot+incremental WebSocket protocol so the dashboard renders immediately on connect without waiting for a full state cycle.\n\n## Protocol spec\n\n### On new /ws/dashboard connection (within 100 ms):\nSend a full snapshot message:\n {type: 'snapshot', blobs: [...], nodes: [...], zones: [...], links: [...], alerts: [...], ble_devices: [...], triggers: [...], timestamp_ms: N}\n\n### Subsequent messages (at 10 Hz):\nOmit type field; send only state that changed since last tick:\n {blobs: [...], nodes: [...], confidence: 0.87, timestamp_ms: N}\nUnchanged arrays may be omitted entirely (null = no change)\n\n## Implementation (mothership/internal/dashboard/hub.go)\n\n- Hub maintains lastSnapshot: full state snapshot updated on each tick\n- On new client connection: serialize lastSnapshot as JSON, send immediately\n- On each tick: compute delta (changed fields only); broadcast to all established clients\n- Snapshot must be sent before the client is added to the broadcast list to avoid race\n\n## Reconnect handling (dashboard/js/app.js)\n- On WebSocket open: set awaitingSnapshot = true\n- On first message: if type === 'snapshot', merge into app state and clear flag\n- On subsequent messages: apply as incremental updates\n\n## Performance requirement\n- Snapshot delivery: < 100 ms after connection established, even with 10+ blobs, 16+ nodes, 20+ zones\n- Test: connect client, measure time to first render; must be < 150 ms end-to-end\n\n## Acceptance\n- Browser devtools shows first WS message with type='snapshot' within 100 ms of upgrade\n- Subsequent messages at 10 Hz omit type field\n- Reconnect after 5s disconnection shows correct current state immediately","status":"closed","priority":2,"issue_type":"task","assignee":"bravo","created_at":"2026-04-06T13:09:42.683611381Z","created_by":"coding","updated_at":"2026-04-07T02:03:04.204480908Z","closed_at":"2026-04-07T02:03:04.204253757Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred"]}
@@ -140,7 +140,7 @@
{"id":"spaxel-w40","title":"Passive radar: auto-detect router AP as virtual TX node","description":"## Overview\nAutomatically detect the home router as a passive radar TX source, eliminating need for a dedicated active TX node.\n\n## Firmware changes\n- During hello message, include ap_bssid and ap_channel from esp_wifi_sta_get_ap_info()\n\n## Mothership (mothership/fleet/ or ingestion/)\n- On hello: extract ap_bssid; if >=80% of nodes report same BSSID create virtual node entry with virtual=1, position unset\n- OUI lookup: embed IEEE OUI registry as Go map compiled via go:embed; display router brand\n- Detect AP BSSID change (router reboot/replacement) and emit system alert\n- SQLite nodes table: add virtual BOOL, node_type TEXT, ap_bssid TEXT, ap_channel INT columns\n\n## Dashboard\n- After AP auto-detected: 'I detected your router (ASUS). Place it on the floor plan to improve accuracy.'\n- Drag-to-place virtual node (distinct router icon) in 3D editor\n- Confirmation dialog with 'Use as signal source' toggle\n\n## Acceptance\n- Virtual node appears in /api/nodes with virtual=true\n- 3D view renders virtual node with distinct icon\n- AP change detection fires a system event within 30s of BSSID change","status":"closed","priority":2,"issue_type":"task","assignee":"alpha","created_at":"2026-04-06T13:01:07.745215170Z","created_by":"coding","updated_at":"2026-04-06T18:04:45.975811136Z","closed_at":"2026-04-06T18:04:45.975562593Z","close_reason":"Implemented passive radar auto-detection of router AP\n\nFirmware: Added ap_bssid/ap_channel to hello message using esp_wifi_sta_get_ap_info()\n\nMothership: Created apdetector package for >=80% BSSID agreement detection, OUI lookup for router manufacturer, AP change detection system events\n\nDashboard: AP detection notification, distinct router icon in 3D (box+4antennas), drag-to-place positioning\n\nVirtual nodes appear in /api/nodes with virtual=true, node_type=ap","source_repo":".","compaction_level":0,"original_size":0,"labels":["failure-count:3"]}
{"id":"spaxel-x59","title":"merge: remove phase6 build tag and unify main.go","description":"## Problem\n`cmd/mothership/main_phase6.go` is gated behind `//go:build phase6` which excludes all Phase 6+ code from default builds. The directory has both `main.go` (Phase 5) and `main_phase6.go` (Phase 6) — both define `package main` with `func main()`, so removing the build tag would cause a duplicate symbol error.\n\n## Prerequisites\nAll Phase 6 package compile errors must be fixed first (spaxel-glq, spaxel-9nj, spaxel-19h, spaxel-uln, spaxel-7nk, spaxel-she).\n\n## Steps\n1. Confirm all Phase 6+ packages compile cleanly:\n ```bash\n cd /home/coding/spaxel/mothership\n PATH=$PATH:/home/coding/go/bin go build ./internal/...\n ```\n2. Delete `cmd/mothership/main.go.bak` (stale backup)\n3. Delete `cmd/mothership/main.go` (Phase 5 entrypoint, superseded)\n4. Remove the `//go:build phase6` line and the blank line after it from `cmd/mothership/main_phase6.go`\n5. Build and verify:\n ```bash\n PATH=$PATH:/home/coding/go/bin go build ./...\n PATH=$PATH:/home/coding/go/bin go test ./...\n ```\n\n## Acceptance\n- `go build ./...` passes with no errors\n- Binary is built from the Phase 6 entrypoint\n- No `phase6` build tag exists anywhere in the codebase\n\nDependents:\n <- spaxel-jcc","status":"closed","priority":1,"issue_type":"task","assignee":"delta","created_at":"2026-04-06T22:30:32.363205812Z","created_by":"coding","updated_at":"2026-04-07T05:33:07.064388207Z","closed_at":"2026-04-07T05:33:07.064285866Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["deferred","failure-count:19"],"dependencies":[{"issue_id":"spaxel-x59","depends_on_id":"spaxel-19h","type":"blocks","created_at":"2026-04-06T22:30:41.292760872Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-x59","depends_on_id":"spaxel-7nk","type":"blocks","created_at":"2026-04-06T22:30:41.351817968Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-x59","depends_on_id":"spaxel-9nj","type":"blocks","created_at":"2026-04-06T22:30:41.255304103Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-x59","depends_on_id":"spaxel-glq","type":"blocks","created_at":"2026-04-06T22:30:41.209121103Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-x59","depends_on_id":"spaxel-she","type":"blocks","created_at":"2026-04-06T22:30:41.390256545Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-x59","depends_on_id":"spaxel-uln","type":"blocks","created_at":"2026-04-06T22:30:41.322389944Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-xlo","title":"Create SQLite floorplan table and storage directory","description":"## Task\nCreate the floorplan table in SQLite and ensure /data/floorplan directory exists.\n\n## Schema\nSQLite floorplan table: image_path TEXT, cal_ax,cal_ay,cal_bx,cal_by REAL, distance_m REAL, rotation_deg REAL, updated_at INT\n\n## Acceptance\n- /data/floorplan directory exists\n- floorplan table created in SQLite with correct schema","status":"closed","priority":2,"issue_type":"task","assignee":"charlie","created_at":"2026-04-07T17:55:49.108738491Z","created_by":"coding","updated_at":"2026-04-07T18:21:09.020450667Z","closed_at":"2026-04-07T18:21:09.020390325Z","close_reason":"done","source_repo":".","compaction_level":0,"original_size":0,"labels":["mitosis-child","mitosis-depth:1","parent-spaxel-klk"]}
-{"id":"spaxel-xpk","title":"Diurnal adaptive baseline: 24-hour slot learning","description":"## Overview\nExtend the EMA baseline system with per-hour-of-day slots to eliminate false positives caused by daily environmental cycles (sunlight, HVAC, temperature changes).\n\n## Backend (mothership/signal/baseline.go extension)\n- Data structure: 24 hourly slots per link per subcarrier; each slot stores amplitude blob and sample_count\n- Learning phase (7 days): accumulate motion-free CSI into hourly slots; require >=300 samples/slot to mark ready\n- Steady state: on each fusion tick, select active baseline = weighted blend of diurnal slot (if ready) + EMA fallback\n- Crossfade: over first 15 min of each hour, linearly blend from EMA to diurnal slot; after 15 min use diurnal exclusively\n- Motion-gated updates: EMA updates continue during the hourly window, improving diurnal slot over time\n- Outlier protection: skip update if deltaRMS > motion threshold (don't train on motion frames)\n- SQLite diurnal_baselines table: link_id, hour_of_day (0-23), n_sub INT, amplitude BLOB, sample_count INT, confidence REAL, updated_at INT\n\n## Dashboard visualization\n- Per-link detail panel: 24-hour polar chart (or horizontal bar chart) showing baseline amplitude variance by hour\n- 'Diurnal learning' progress indicator: 'Learning hour 14... 6/7 days'\n- Confidence color per hour: green (ready), amber (partial), red (no data)\n\n## Acceptance\n- Baseline correctly crossfades at hour boundaries (±60s)\n- Motion events during learning do not corrupt slots (outlier protection confirmed by test)\n- Polar chart renders for links with >=1 ready slot\n- No performance regression: baseline lookup remains O(1)\n- Requires: spaxel-jcc (phase 6 integration)","status":"in_progress","priority":2,"issue_type":"task","assignee":"hotel","created_at":"2026-04-06T13:02:07.078024506Z","created_by":"coding","updated_at":"2026-04-09T12:15:56.683989979Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["blocked","failure-count:137"],"dependencies":[{"issue_id":"spaxel-xpk","depends_on_id":"spaxel-jcc","type":"blocks","created_at":"2026-04-06T22:30:46.133690574Z","created_by":"coding","metadata":"{}","thread_id":""}]}
+{"id":"spaxel-xpk","title":"Diurnal adaptive baseline: 24-hour slot learning","description":"## Overview\nExtend the EMA baseline system with per-hour-of-day slots to eliminate false positives caused by daily environmental cycles (sunlight, HVAC, temperature changes).\n\n## Backend (mothership/signal/baseline.go extension)\n- Data structure: 24 hourly slots per link per subcarrier; each slot stores amplitude blob and sample_count\n- Learning phase (7 days): accumulate motion-free CSI into hourly slots; require >=300 samples/slot to mark ready\n- Steady state: on each fusion tick, select active baseline = weighted blend of diurnal slot (if ready) + EMA fallback\n- Crossfade: over first 15 min of each hour, linearly blend from EMA to diurnal slot; after 15 min use diurnal exclusively\n- Motion-gated updates: EMA updates continue during the hourly window, improving diurnal slot over time\n- Outlier protection: skip update if deltaRMS > motion threshold (don't train on motion frames)\n- SQLite diurnal_baselines table: link_id, hour_of_day (0-23), n_sub INT, amplitude BLOB, sample_count INT, confidence REAL, updated_at INT\n\n## Dashboard visualization\n- Per-link detail panel: 24-hour polar chart (or horizontal bar chart) showing baseline amplitude variance by hour\n- 'Diurnal learning' progress indicator: 'Learning hour 14... 6/7 days'\n- Confidence color per hour: green (ready), amber (partial), red (no data)\n\n## Acceptance\n- Baseline correctly crossfades at hour boundaries (±60s)\n- Motion events during learning do not corrupt slots (outlier protection confirmed by test)\n- Polar chart renders for links with >=1 ready slot\n- No performance regression: baseline lookup remains O(1)\n- Requires: spaxel-jcc (phase 6 integration)","status":"in_progress","priority":2,"issue_type":"task","assignee":"hotel","created_at":"2026-04-06T13:02:07.078024506Z","created_by":"coding","updated_at":"2026-04-09T12:26:09.997708333Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["blocked","deferred","failure-count:137"],"dependencies":[{"issue_id":"spaxel-xpk","depends_on_id":"spaxel-jcc","type":"blocks","created_at":"2026-04-06T22:30:46.133690574Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-yxr","title":"Ingestion: CSI frame validation with malformed counter and auto-close","description":"## Overview\nImplement strict CSI binary frame validation with per-connection malformed frame counters and automatic connection closure on persistent malformed input.\n\n## Validation rules (plan lines 303-324):\n- Minimum frame length: 24 bytes (header only, zero subcarriers valid)\n- Maximum frame length: 280 bytes (24 header + 128 subcarriers × 2 bytes I/Q)\n- n_sub field: must be ≤128\n- Payload length: must equal n_sub × 2 bytes exactly\n- channel: must be in [1,14] for 2.4 GHz; drop if 0 or >14\n- rssi: int8; 0 treated as invalid/missing (not an error, but log at DEBUG)\n- timestamp_us: any uint64 value accepted\n\n## Per-connection malformed counter (sliding 60-second window):\n- Track malformed_count and window_start_ms per WebSocket connection\n- On each validation failure: increment malformed_count; log at DEBUG\n- Every 60s: check counts → if malformed_count > 100: log WARN 'Node {mac} sent {N} malformed frames in 60s'\n- If malformed_count > 1000 within 60s: close WebSocket with message 'Excessive malformed frames — possible firmware bug'\n- Reset counter every 60s\n\n## Acceptance\n- Valid frame: passes all checks in <1 μs\n- Frame with n_sub=200: rejected (n_sub > 128)\n- Frame with len=10: rejected (< 24 bytes)\n- Frame with channel=0: dropped silently\n- 1001 malformed frames in 60s: connection closed with correct message\n- 101 malformed frames: WARN logged, connection kept open","status":"closed","priority":2,"issue_type":"task","assignee":"charlie","created_at":"2026-04-06T16:44:21.981852269Z","created_by":"coding","updated_at":"2026-04-07T16:23:24.731432820Z","closed_at":"2026-04-07T16:23:24.731370070Z","close_reason":"Implemented CSI frame validation with DEBUG logging and performance benchmark.\n\nAll validation rules from plan lines 303-324 implemented:\n- Minimum frame length: 24 bytes ✓\n- Maximum frame length: 280 bytes ✓ \n- n_sub ≤ 128 ✓\n- Payload length = n_sub × 2 bytes ✓\n- Channel in [1,14] for 2.4 GHz ✓\n- RSSI=0 logged at DEBUG (allowed) ✓\n- timestamp_us any value ✓\n\nPer-connection malformed counter (60s sliding window):\n- DEBUG log on each validation failure ✓\n- WARN log when count > 100 ✓\n- Auto-close when count > 1000 ✓\n- Counter resets every 60s ✓\n\nAdded benchmark tests to verify <1 μs validation performance for valid frames.","source_repo":".","compaction_level":0,"original_size":0,"labels":["failure-count:1"]}
{"id":"spaxel-zpt","title":"Spatial context notifications with floor-plan thumbnails","description":"## Background\n\nPush notifications without context are ignored or disabled. \"Motion detected\" tells you nothing useful. \"Alice walked into the Kitchen — Bob is already there\" is genuinely interesting. \"Possible fall: Alice in Hallway — unacknowledged for 3 minutes\" demands immediate attention. The plan specifies server-side rendering of mini floor-plan thumbnails attached to notifications to provide instant spatial context without opening the app.\n\n## Server-Side Floor-Plan Renderer\n\nNew package: mothership/internal/render/floorplan.go\n\nThe renderer produces a top-down 2D PNG (300x300 pixels) showing:\n- Room outline: outer boundary of all zones as white rectangles on dark background\n- Zone fills: each zone as a semi-transparent coloured fill (zone.color at 20% opacity)\n- Zone labels: zone name in small white text at zone centroid\n- Node positions: small white circle dots\n- Person blobs: coloured circles (person.color) at their last-known position, diameter proportional to detection confidence (min 10px, max 20px)\n- Name labels: person name in white text above each blob circle, if identity is known\n- Portal planes: thin lines in purple (#a855f7)\n- Event highlight: the zone where the event occurred rendered with brighter fill and a white border\n\nRendering library: use github.com/fogleman/gg (a pure-Go 2D graphics library). Alternative: standard image/draw + image/png for maximum portability. The fogleman/gg approach is recommended for its higher-level drawing API (bezier curves, text, etc.).\n\nThe PNG must be generated within 200ms to not delay notification delivery. At 300x300 with simple geometry, this should be easily achievable.\n\nThe rendered PNG is stored as a []byte and passed to the notification delivery function. It is base64-encoded for attachment in webhook payloads or passed as a file to ntfy/Pushover APIs.\n\n## Notification Types and Triggers\n\n1. zone_enter: \"{{person_name}} entered {{zone_name}}\" — LOW priority unless security mode is active\n2. zone_leave: \"{{person_name}} left {{zone_name}}\" — LOW priority\n3. zone_vacant: \"{{zone_name}} is now empty\" — LOW priority\n4. fall_detected: \"Possible fall: {{person_name}} in {{zone_name}}\" — URGENT, always immediate\n5. fall_escalation: \"URGENT: Fall unacknowledged for 5 minutes — {{person_name}} in {{zone_name}}\" — URGENT\n6. anomaly_alert: \"Unexpected presence: {{zone_name}}\" — HIGH priority (breaks quiet hours)\n7. node_offline: \"Node {{node_label}} has gone offline\" — MEDIUM priority\n8. sleep_summary: \"Last night: {{sleep_duration}}\" — LOW priority, morning delivery\n\n## Smart Batching\n\nIf multiple LOW or MEDIUM priority events fire within a 30-second window, batch them into a single notification:\n- \"Alice entered Kitchen. Bob left Living Room.\"\n- \"2 presence events in the last 30 seconds.\"\n\nBatching rules:\n- Batch only events of the same priority level\n- Never batch URGENT events — those are always immediate\n- Never batch events involving different notification types if the combination is confusing\n- Batch counter: if more than 5 events in 30s, summarise as \"N presence events in the last minute\"\n\nBatching implementation: a 30-second window timer per notification channel. When the first LOW event fires, start the 30s timer. Accumulate events. On timer expiry: merge into one notification and deliver.\n\n## Quiet Hours\n\nUser-configurable quiet hours: from_time, to_time (e.g. \"22:00\" to \"07:00\"). Stored in SQLite notifications_config (channel, quiet_from, quiet_to, quiet_days_bitmask).\n\nDuring quiet hours:\n- LOW priority notifications are queued\n- MEDIUM priority notifications are queued\n- HIGH and URGENT notifications are delivered immediately regardless of quiet hours\n\nAt the end of quiet hours (07:00 on non-override days): deliver all queued notifications as a morning digest bundle: \"While you were asleep: [summary of queued events]\"\n\n## Delivery Channels\n\nntfy:\n- POST to https://ntfy.sh/{topic} (or self-hosted server URL)\n- Headers: Authorization: Bearer {token} (if configured), Priority: urgent/high/default/low/min\n- Body: the notification text\n- Headers: Attach: {base64_encoded_png_url} — for ntfy, attach the floor-plan as a URL if mothership is publicly accessible, or send as base64 data URL for local deployments\n\nPushover:\n- POST to https://api.pushover.net/1/messages.json\n- Fields: token, user, message, title, priority, attachment (PNG as multipart form upload)\n\nGeneric webhook:\n- POST to user-configured URL\n- Body: {\"event_type\":\"...\", \"message\":\"...\", \"person_id\":\"...\", \"zone_id\":\"...\", \"timestamp\":\"...\", \"floorplan_png_base64\":\"...\"}\n\n## Configuration UI\n\nDashboard Settings panel -> \"Notifications\" tab:\n- Delivery channel selector: None / ntfy / Pushover / Webhook\n- Channel-specific credential fields (ntfy server URL + topic + token, Pushover API key, webhook URL)\n- Test notification button: sends a test notification to verify configuration\n- Event type enable/disable toggles: per event type, can disable e.g. \"zone_enter\" while keeping \"fall_detected\" enabled\n- Quiet hours: time picker from/to, day-of-week selector\n- Smart batching toggle (default on)\n- \"Morning digest\" toggle (default on — delivers batched quiet-hours events at wake time)\n\n## Files to Create or Modify\n\n- mothership/internal/render/floorplan.go: floor-plan PNG renderer\n- mothership/internal/notifications/manager.go: NotificationManager, batching, quiet hours logic\n- mothership/internal/notifications/ntfy.go: ntfy delivery client\n- mothership/internal/notifications/pushover.go: Pushover delivery client\n- mothership/internal/notifications/webhook.go: generic webhook delivery\n- mothership/internal/dashboard/routes.go: GET/PUT /api/settings/notifications, POST /api/notifications/test\n\n## Tests\n\n- Test floor-plan renderer produces a 300x300 PNG with correct dimensions\n- Test that zone boundaries appear in the rendered PNG at correct coordinates (check pixel colors at known positions)\n- Test batching: 3 LOW events within 10s -> 1 notification; 1 URGENT event -> immediate even if batching timer is active\n- Test quiet hours gate: LOW event at 23:00 with quiet hours 22:00-07:00 -> queued; URGENT event at 23:00 -> delivered immediately\n- Test morning digest delivery: queued events are bundled and delivered at quiet_hours_end\n- Test ntfy delivery with mock HTTP server: verify correct headers and body format\n- Test webhook delivery with mock HTTP server: verify correct JSON body and base64 PNG field\n- Test test-notification endpoint fires correctly\n\n## Acceptance Criteria\n\n- Notification received via ntfy within 5 seconds of trigger event for URGENT priority\n- Floor-plan PNG correctly shows zone boundaries and person positions in the notification\n- Smart batching prevents more than one notification per 30-second window for LOW events\n- Quiet hours suppress LOW/MEDIUM notifications and queue them for morning digest\n- Fall detection and anomaly alerts always bypass quiet hours\n- Morning digest delivered correctly at quiet hours end\n- Test notification button correctly verifies channel configuration\n- Tests pass","status":"open","priority":3,"issue_type":"task","created_at":"2026-03-28T01:48:19.528717849Z","created_by":"coding","updated_at":"2026-03-28T03:29:14.371730406Z","source_repo":".","compaction_level":0,"original_size":0,"dependencies":[{"issue_id":"spaxel-zpt","depends_on_id":"spaxel-c0q","type":"blocks","created_at":"2026-03-28T03:29:14.371640840Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-zpt","depends_on_id":"spaxel-c1c","type":"blocks","created_at":"2026-03-28T01:48:23.948107860Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-zpt","depends_on_id":"spaxel-qlh","type":"blocks","created_at":"2026-03-28T01:48:23.975916991Z","created_by":"coding","metadata":"{}","thread_id":""}]}
{"id":"spaxel-zvb","title":"Mothership: adaptive load shedding & resource throttling","description":"## Overview\nImplement a 4-level load shedding system to keep the fusion pipeline responsive under CPU/memory pressure, especially for large fleets.\n\n## Pipeline instrumentation\n- Time each of the 8 fusion pipeline stages per iteration using time.Since()\n- Maintain 5-iteration rolling average of total iteration time (ring buffer of 5 durations)\n\n## Load shedding state machine\nLevel 0 (normal): rolling avg < 80 ms — full pipeline\nLevel 1 (light): rolling avg >= 80 ms — suspend crowd flow accumulation (~3 ms saved/iter)\nLevel 2 (moderate): rolling avg >= 90 ms — also suspend CSI replay buffer writes (~2 ms saved/iter)\nLevel 3 (heavy): rolling avg >= 95 ms — drop CSI frames when ingest channel > 50% full; push rate reduction config to all nodes (10 Hz cap)\n\nRecovery: when rolling avg < 60 ms for 10 consecutive iterations, step down one level\n\n## Integration points\n- Health endpoint GET /healthz: include shedding_level (0-3) in response\n- Dashboard status bar: show 'System load: NOMINAL / LIGHT / MODERATE / HIGH'\n- WS alert when Level 3 triggered: {type: 'alert', severity: 'warning', description: 'System under load — CSI rate reduced to 10 Hz'}\n- Level 3 recovery: push config message to all nodes restoring their prior rate\n\n## Acceptance\n- Load shedding level changes logged at INFO\n- Level 3 triggers correctly when ingest channel >50% full\n- Node rate restoration confirmed after Level 3 recovery\n- Health endpoint reflects current level\n- No mutex contention from shedding logic itself (must be lock-free reads)","status":"in_progress","priority":2,"issue_type":"task","assignee":"delta","created_at":"2026-04-06T13:09:29.689754824Z","created_by":"coding","updated_at":"2026-04-07T20:49:19.853741601Z","source_repo":".","compaction_level":0,"original_size":0,"labels":["blocked","deferred","failure-count:228"],"dependencies":[{"issue_id":"spaxel-zvb","depends_on_id":"spaxel-54i","type":"blocks","created_at":"2026-04-07T06:33:23.124863668Z","created_by":"coding","metadata":"{}","thread_id":""},{"issue_id":"spaxel-zvb","depends_on_id":"spaxel-5yq","type":"blocks","created_at":"2026-04-07T06:33:23.159852888Z","created_by":"coding","metadata":"{}","thread_id":""}]}
diff --git a/.needle-predispatch-sha b/.needle-predispatch-sha
index 98934d6..abe1f52 100644
--- a/.needle-predispatch-sha
+++ b/.needle-predispatch-sha
@@ -1 +1 @@
-f2cd1ebf0b9fbae48af27de003536623ab91688f
+3ff80c294d817bffc2c455069fbc592932c211ab
diff --git a/dashboard/css/floorplan.css b/dashboard/css/floorplan.css
new file mode 100644
index 0000000..06492d9
--- /dev/null
+++ b/dashboard/css/floorplan.css
@@ -0,0 +1,261 @@
+/**
+ * Floor Plan Setup Panel Styles
+ */
+
+.floorplan-panel {
+ position: fixed;
+ top: 60px;
+ right: 340px;
+ width: 380px;
+ max-height: calc(100vh - 80px);
+ background: rgba(0, 0, 0, 0.9);
+ border-radius: 8px;
+ z-index: 100;
+ overflow-y: auto;
+}
+
+.floorplan-header {
+ display: flex;
+ justify-content: space-between;
+ align-items: center;
+ padding: 12px 16px;
+ border-bottom: 1px solid rgba(255, 255, 255, 0.1);
+}
+
+.floorplan-header h3 {
+ font-size: 14px;
+ color: #888;
+ text-transform: uppercase;
+ letter-spacing: 1px;
+ margin: 0;
+}
+
+.floorplan-close {
+ background: none;
+ border: none;
+ color: #888;
+ font-size: 24px;
+ cursor: pointer;
+ padding: 0 4px;
+ line-height: 1;
+ transition: color 0.2s;
+}
+
+.floorplan-close:hover {
+ color: #eee;
+}
+
+.floorplan-content {
+ padding: 12px;
+}
+
+.floorplan-section {
+ margin-bottom: 20px;
+}
+
+.floorplan-section h4 {
+ font-size: 13px;
+ color: #ccc;
+ margin-bottom: 8px;
+}
+
+.floorplan-hint {
+ font-size: 11px;
+ color: #888;
+ margin-bottom: 8px;
+}
+
+/* Upload area */
+.floorplan-upload-area {
+ display: flex;
+ align-items: center;
+ gap: 12px;
+}
+
+.floorplan-btn {
+ padding: 6px 14px;
+ border-radius: 4px;
+ font-size: 12px;
+ cursor: pointer;
+ transition: background 0.2s;
+ border: none;
+ display: inline-flex;
+ align-items: center;
+ gap: 6px;
+}
+
+.floorplan-btn-primary {
+ background: #4fc3f7;
+ color: #1a1a2e;
+}
+
+.floorplan-btn-primary:hover:not(:disabled) {
+ background: #29b6f6;
+}
+
+.floorplan-btn-primary:disabled {
+ opacity: 0.5;
+ cursor: not-allowed;
+}
+
+.floorplan-btn-secondary {
+ background: rgba(255, 255, 255, 0.1);
+ color: #ccc;
+ border: 1px solid rgba(255, 255, 255, 0.2);
+}
+
+.floorplan-btn-secondary:hover {
+ background: rgba(255, 255, 255, 0.15);
+}
+
+.floorplan-icon {
+ font-size: 14px;
+}
+
+.floorplan-file-name {
+ font-size: 11px;
+ color: #888;
+ max-width: 180px;
+ overflow: hidden;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+}
+
+/* Preview */
+.floorplan-preview {
+ margin-top: 12px;
+ text-align: center;
+}
+
+.floorplan-preview img {
+ max-width: 100%;
+ max-height: 200px;
+ border-radius: 4px;
+ border: 1px solid rgba(255, 255, 255, 0.1);
+}
+
+/* Calibration */
+.floorplan-calibration-container {
+ margin-top: 12px;
+}
+
+.floorplan-image-wrapper {
+ position: relative;
+ display: inline-block;
+ border: 1px solid rgba(255, 255, 255, 0.1);
+ border-radius: 4px;
+ overflow: hidden;
+}
+
+#floorplan-canvas {
+ display: block;
+ cursor: crosshair;
+ max-width: 100%;
+}
+
+.floorplan-marker {
+ position: absolute;
+ width: 24px;
+ height: 24px;
+ border-radius: 50%;
+ color: #fff;
+ font-size: 12px;
+ font-weight: bold;
+ display: flex;
+ align-items: center;
+ justify-content: center;
+ transform: translate(-50%, -50%);
+ pointer-events: none;
+ text-shadow: 0 1px 3px rgba(0, 0, 0, 0.8);
+}
+
+.floorplan-controls {
+ margin-top: 12px;
+}
+
+.floorplan-instructions {
+ font-size: 12px;
+ color: #bbb;
+ background: rgba(255, 255, 255, 0.05);
+ padding: 8px 10px;
+ border-radius: 4px;
+ text-align: center;
+}
+
+.floorplan-points-info {
+ background: rgba(0, 0, 0, 0.3);
+ border-radius: 4px;
+ padding: 8px 10px;
+ margin-top: 8px;
+}
+
+.floorplan-point-info {
+ display: flex;
+ justify-content: space-between;
+ font-size: 11px;
+ margin-bottom: 4px;
+}
+
+.point-label {
+ color: #888;
+}
+
+.floorplan-distance-input {
+ margin-top: 8px;
+}
+
+.floorplan-distance-input label {
+ display: block;
+ font-size: 11px;
+ color: #aaa;
+ margin-bottom: 4px;
+}
+
+.floorplan-distance-input input {
+ width: 100%;
+ padding: 6px 10px;
+ background: rgba(255, 255, 255, 0.08);
+ border: 1px solid rgba(255, 255, 255, 0.15);
+ border-radius: 4px;
+ color: #eee;
+ font-size: 13px;
+ box-sizing: border-box;
+}
+
+.floorplan-distance-input input:focus {
+ outline: none;
+ border-color: #4fc3f7;
+ box-shadow: 0 0 0 2px rgba(79, 195, 247, 0.2);
+}
+
+.floorplan-actions {
+ display: flex;
+ justify-content: space-between;
+ margin-top: 12px;
+ gap: 8px;
+}
+
+.floorplan-status-info {
+ display: grid;
+ grid-template-columns: 1fr 1fr;
+ gap: 8px;
+ margin-bottom: 12px;
+}
+
+.status-item {
+ display: flex;
+ justify-content: space-between;
+ font-size: 11px;
+}
+
+.status-label {
+ color: #888;
+}
+
+/* Responsive adjustments */
+@media (max-width: 1200px) {
+ .floorplan-panel {
+ right: 20px;
+ width: 340px;
+ }
+}
diff --git a/dashboard/index.html b/dashboard/index.html
index 547fd78..9f95ada 100644
--- a/dashboard/index.html
+++ b/dashboard/index.html
@@ -12,6 +12,7 @@
+