- Verified
sensors.py:- Confirmed continuous execution via
asyncioloops. - Validated range-based data generation for Power, Traffic, and Environment sensors.
- Confirmed
chaos_coordinatorcorrectly cycles throughNORMAL,BLACKOUT_CRASH, andHAZMAT_FIREscenarios. - Identified that
post_datais currently in mock/print mode. - Noted
datetime.utcnow()deprecation for future fix.
- Confirmed continuous execution via
- Endpoints in
sensors.py(/api/power,/api/traffic,/api/environment) perfectly matchnginx.confrouting rules.
- Upgraded Workers to ML:
trafficWorker.py,powerWorker.py, andenviornWorker.pynow usescikit-learnIsolation Forest for unsupervised anomaly detection. - Dynamic Training: Models learn the city's baseline from a 100-event sliding window, with a baseline requirement of 50 events before activation.
- Hybrid Logic: The Power worker prioritizes hard failure status (
OUTAGE) over ML predictions for safety. - Dependency Update:
pyproject.tomlnow includesscikit-learn,numpy, and updated versions forfastapianduvicorn.
- Phase 1 (Simulators): Complete (Enabled real POST requests to
localhost:8080). - Phase 2 (Edge Workers): Complete (ML-enhanced).
- Sensors Fix: Resolved
datetime.utcnow()deprecation and verifiedaiohttpenvironment.
- Handoff Logic: Workers now use
requeststo push anomalies toORCHESTRATOR_URL. - Structured Payloads: Confirmed that all workers send
source_worker,trigger_reason,trigger_data, andhistorical_context. - Resilience: Added
try/exceptblocks and timeouts to the handoff logic to prevent worker crashes. - Dependency Alert: Identified need for
requestslibrary in the environment.