How tiwariraman884/deepsee works
DeepSea Guardian is an ocean-monitoring and mission-control platform. Sensor readings enter through the ESP32 gateway or other sensor clients, are analyzed for anomalies, and can trigger drone dispatch and an inspection; the dashboard presents live monitoring, alerts, maps, and forecasts. The backend also supports camera-based inspection evidence, species classification, reporting, and user accounts. The README documents the product workflow; source excerpts show pipeline orchestration, persistence, and live event delivery, but do not expose every route-to-worker connection.
Main entry points: sensorPipeline.ts Pipeline Orchestrator · droneDispatcher.ts Drone Dispatcher · inspectionSimulator.ts Inspection Simulator · server.ts API Server
Components 23
Field Monitoring
- ESP32 Gateway
hardware/esp32/src/main.cpp - Device API Client
hardware/esp32/src/transport/ApiClient.h
Backend Processing
- Sensor API
backend/src/routes/sensors.ts - Pipeline Orchestrator
backend/src/lib/sensorPipeline.ts - Sensor Consumer
backend/src/lib/pipeline/sensorConsumer.ts - Event Bus
backend/src/lib/eventBus.ts - Telemetry Database
backend/src/db/index.ts - Drone Dispatcher
backend/src/lib/pipeline/droneDispatcher.ts - Inspection Simulator
backend/src/lib/pipeline/inspectionSimulator.ts - Incident Reports
backend/src/routes/reports.ts - Account Access
backend/src/routes/auth.ts - API Server
backend/src/server.ts - Live Event Push
backend/src/lib/sseManager.ts
AI & Inspection
- Anomaly Worker
backend/src/lib/mlWorker.ts - Python Inference
backend/src/lib/python.ts - Vision Pipeline
backend/src/lib/vision/pipeline.ts - Frame Storage
backend/src/lib/vision/storage.ts - Species Inference
backend/src/lib/speciesWorker.ts
Mission Control
- Mission Dashboard
frontend/src/app/dashboard/page.tsx - Ocean Map
frontend/src/app/map/page.tsx - Species Classifier UI
frontend/src/app/species/page.tsx - AI Insights
frontend/src/app/system-intelligence/page.tsx
Other components
- Ocean Operator
Connections 25
- Ocean Operator → Mission Dashboard: uses
- ESP32 Gateway → Device API Client: sends readings
hardware/esp32/src/main.cpp - Device API Client → Sensor API: posts telemetry
hardware/esp32/src/transport/ApiClient.h - Sensor API → Pipeline Orchestrator: feeds readings
- API Server → Sensor API: registers route
backend/src/server.ts - Pipeline Orchestrator → Sensor Consumer: starts
backend/src/lib/sensorPipeline.ts - Pipeline Orchestrator → Drone Dispatcher: starts
backend/src/lib/sensorPipeline.ts - Pipeline Orchestrator → Inspection Simulator: starts
backend/src/lib/sensorPipeline.ts - Sensor Consumer → Anomaly Worker: requests inference
backend/src/lib/pipeline/sensorConsumer.ts - Anomaly Worker → Python Inference: spawns process
backend/src/lib/mlWorker.ts - Sensor Consumer → Telemetry Database: persists readings
backend/src/lib/pipeline/sensorConsumer.ts - Drone Dispatcher → Telemetry Database: records missions
backend/src/lib/pipeline/droneDispatcher.ts - Drone Dispatcher → Inspection Simulator: signals inspection
- Inspection Simulator → Vision Pipeline: uses camera analysis
backend/src/lib/pipeline/inspectionSimulator.ts - Vision Pipeline → Telemetry Database: stores evidence
backend/src/lib/vision/pipeline.ts - Vision Pipeline → Frame Storage: stores frames
backend/src/lib/vision/pipeline.ts - Inspection Simulator → Live Event Push: streams findings
backend/src/lib/pipeline/inspectionSimulator.ts - Drone Dispatcher → Live Event Push: pushes updates
backend/src/lib/pipeline/droneDispatcher.ts - Species Classifier UI → Species Inference: classifies species
- Ocean Operator → Account Access: signs in
backend/src/routes/auth.ts - Mission Dashboard → API Server: uses REST and SSE
- Mission Dashboard → Live Event Push: receives live events
- Ocean Map → API Server: requests monitoring data
- AI Insights → API Server: views insights
- Incident Reports → Telemetry Database: reads inspection data