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ca-grow-ops-manager/specs/advanced-features.md
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feat: Full Spec Kit compliance implementation 
Photo Management (per specs/photo-management.md):
- Sharp integration for 3-size compression (thumb/medium/full)
- WebP output with 80-90% quality
- Client-side compression with browser-image-compression
- PhotoUpload component with camera/drag-drop support
- Upload API with bulk support and stats endpoint

Testing:
- Backend: Jest tests for all major API endpoints
- Frontend: Vitest tests for utilities and API clients
- CI: Updated Forgejo workflow for test execution

Specs (100% coverage):
- visitor-management.md (Phase 8)
- messaging.md (Phase 9)
- audit-and-documents.md (Phase 10)
- accessibility-i18n.md (Phase 11)
- hardware-integration.md (Phase 12)
- advanced-features.md (Phase 13)

Documentation:
- OpenAPI 3.0 spec (docs/openapi.yaml)
- All endpoints documented with schemas
2025-12-11 09:53:32 -08:00

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Feature Spec: Environmental Monitoring & Financial Tracking

Priority: 🟡 Medium
Phase: 13
Status: ✅ Implemented

Overview

Advanced features for environmental sensor monitoring, financial tracking with cost-per-gram analysis, and AI-powered yield predictions.

Environmental Monitoring

Models

Sensor

  • id: UUID
  • name: string
  • type: enum (TEMPERATURE, HUMIDITY, CO2, LIGHT_PAR, PH, EC, VPD, SOIL_MOISTURE)
  • roomId: FK (optional)
  • location: string (e.g., "North wall")
  • deviceId: string (hardware ID)
  • minThreshold: number
  • maxThreshold: number
  • isActive: boolean

SensorReading

  • id: UUID
  • sensorId: FK
  • value: number
  • unit: string (°F, %, ppm, etc.)
  • timestamp: datetime

EnvironmentAlert

  • id: UUID
  • sensorId: FK (optional)
  • roomId: FK (optional)
  • type: string (TEMP_HIGH, HUMIDITY_LOW, etc.)
  • severity: enum (INFO, WARNING, CRITICAL, EMERGENCY)
  • message: string
  • acknowledgedAt: datetime
  • resolvedAt: datetime

API Endpoints

  • GET /api/environment/sensors - List sensors
  • POST /api/environment/sensors - Create sensor
  • POST /api/environment/sensors/:id/readings - Submit reading
  • GET /api/environment/sensors/:id/readings - Get reading history
  • GET /api/environment/alerts - Get alerts
  • POST /api/environment/alerts/:id/acknowledge - Ack alert
  • GET /api/environment/dashboard - Real-time dashboard

Financial Tracking

Models

FinancialTransaction

  • id: UUID
  • type: enum (EXPENSE, REVENUE, ADJUSTMENT)
  • category: enum (LABOR, NUTRIENTS, SUPPLIES, EQUIPMENT, UTILITIES, etc.)
  • amount: number
  • description: string
  • batchId: FK (optional)
  • date: datetime

BatchCost

  • id: UUID
  • batchId: FK (unique)
  • laborCost: number
  • nutrientCost: number
  • utilityCost: number
  • totalCost: number
  • yieldGrams: number
  • costPerGram: number

Sale

  • id: UUID
  • batchId: FK (optional)
  • product: string
  • quantity: number
  • pricePerUnit: number
  • totalPrice: number

API Endpoints

  • GET /api/financial/transactions - List transactions with totals
  • POST /api/financial/transactions - Create transaction
  • GET /api/financial/sales - List sales
  • POST /api/financial/sales - Record sale
  • GET /api/financial/batches/:id/costs - Batch cost breakdown
  • GET /api/financial/reports/profit-loss - P&L report
  • GET /api/financial/reports/category-breakdown - Expense breakdown
  • GET /api/financial/reports/cost-per-gram - CPG analysis

AI/ML Insights

Models

YieldPrediction

  • id: UUID
  • batchId: FK
  • predictedYield: number (grams)
  • confidence: number (0-1)
  • factors: JSON
  • actualYield: number (filled after harvest)
  • accuracy: number

AnomalyDetection

  • id: UUID
  • entityType: string
  • entityId: FK
  • anomalyType: string
  • severity: string
  • description: string
  • isResolved: boolean

API Endpoints

  • POST /api/insights/predict/yield - Generate yield prediction
  • GET /api/insights/predictions/:batchId - Get predictions history
  • POST /api/insights/detect/anomalies - Run anomaly detection
  • GET /api/insights/anomalies - List anomalies
  • GET /api/insights/dashboard - AI insights overview

Future Enhancements

  • Real ML model integration (TensorFlow/PyTorch)
  • Predictive maintenance
  • Automated threshold adjustment
  • Integration with accounting software