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boc/vims-backend/STATUS.md
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# VIMS - Build Status
## ✅ Completed Components
### Backend API (Port 3450)
- [x] Express.js server with security middleware
- [x] Health checks (/health, /health/ready, /health/live)
- [x] Object management API (CRUD + baseline images)
- [x] Observation API (upload, process, compare)
- [x] Detection API (list, verify)
- [x] Alert API (list, update status, escalate)
- [x] Dashboard API (overview, map objects, timeline, top alerts)
### AI Services
- [x] Object Detection Service (YOLO-based, ONNX Runtime)
- [x] Change Detection Service (pixel, structural, hash comparison)
- [x] Risk Classification Service (Green/Yellow/Orange/Red)
- [x] Component definitions for ATM, charging station, parking meter, defibrillator
### Database Models (PostgreSQL + Sequelize)
- [x] ObjectType (ATM, charging_station, parking_meter, defibrillator)
- [x] MonitoredObject (with location, baseline images, status)
- [x] Observation (image upload, quality metadata)
- [x] Detection (AI findings with bounding boxes)
- [x] Alert (risk-based alerting system)
- [x] Customer (multi-tenant support)
- [x] ModelVersion (AI model tracking)
### Background Workers
- [x] Queue-based processing (Bull + Redis)
- [x] Observation processing pipeline
- [x] Notification service (email, SMS, webhook, push)
### Integrations
- [x] Landvex API integration
- [x] quiXzoom API integration
- [x] Webhook support
### Infrastructure
- [x] Docker + Docker Compose setup
- [x] PostgreSQL database
- [x] Redis cache/queue
- [x] MinIO object storage
- [x] Environment configuration
### Testing
- [x] 31 tests passing
- [x] Object Detection tests
- [x] Risk Classifier tests (97.72% coverage)
- [x] Integration tests
### Documentation
- [x] API documentation (docs/API.md)
- [x] Deployment guide (docs/DEPLOYMENT.md)
- [x] README with quick start
- [x] Environment example
### Landvex Website
- [x] VIMS product page (/infrastructure-monitoring)
- [x] Feature overview
- [x] Risk level visualization
- [x] Use cases
## 📊 Test Results
```
Test Suites: 3 passed, 3 total
Tests: 31 passed, 31 total
Coverage:
- Risk Classifier: 97.72% statements
- Object Detection: 67.39% statements
- Overall: 79.12% lines
```
## 🚀 Quick Start
```bash
cd vims-backend
# Install dependencies
npm install
# Start infrastructure
docker-compose up -d postgres redis minio
# Run tests
npm test
# Start server
npm run dev
# Start worker
npm run worker
```
## 📁 Project Structure
```
vims-backend/
├── src/
│ ├── index.js # Main application
│ ├── models/ # Database models
│ ├── api/ # REST API routes
│ ├── services/ # AI services
│ ├── workers/ # Background workers
│ ├── integrations/ # External integrations
│ ├── utils/ # Utilities
│ └── middleware/ # Express middleware
├── tests/ # Test suite
├── docs/ # Documentation
├── demo/ # Demo script
├── scripts/ # Setup scripts
├── Dockerfile
├── docker-compose.yml
└── package.json
```
## 🔄 Next Steps for Production
1. **AI Model Training**
- Collect training images for each object type
- Train YOLO models for object detection
- Export to ONNX format
2. **Image Storage**
- Configure S3/MinIO credentials
- Implement image upload/download
3. **Authentication**
- Implement JWT authentication
- Add role-based access control
4. **Monitoring**
- Add Prometheus metrics
- Setup Grafana dashboards
- Configure alerting
5. **Scaling**
- Deploy to Kubernetes
- Add horizontal pod autoscaling
- Setup load balancing
## 📝 API Endpoints
| Endpoint | Method | Description |
|----------|--------|-------------|
| /health | GET | Health check |
| /api/v1/objects | GET/POST | List/Create objects |
| /api/v1/objects/:id | GET/PUT/DELETE | Object management |
| /api/v1/objects/:id/baseline | POST | Set baseline images |
| /api/v1/observations | POST | Upload observations |
| /api/v1/observations/:id | GET | Get observation |
| /api/v1/observations/:id/process | POST | Reprocess |
| /api/v1/detections | GET | List detections |
| /api/v1/alerts | GET | List alerts |
| /api/v1/alerts/:id/status | PUT | Update alert |
| /api/v1/dashboard/overview | GET | Dashboard stats |
| /api/v1/dashboard/objects | GET | Map objects |
| /api/v1/dashboard/timeline | GET | Activity timeline |
## 🎯 Key Features Implemented
1. **Visual Anomaly Detection**
- Baseline per object (not generic model)
- Change detection with multiple algorithms
- Component-level detection
2. **Risk Classification**
- Green/Yellow/Orange/Red levels
- Confidence-based escalation
- Customizable rules per object type
3. **Continuous Monitoring**
- Queue-based processing
- Real-time alerts
- Historical tracking
4. **Integration Ready**
- Landvex API
- quiXzoom missions
- Webhook notifications
## 📞 Support
- Documentation: docs/API.md
- Deployment: docs/DEPLOYMENT.md
- Tests: npm test