# VIMS Core Integration Report

## Test Results

**Date:** 2026-07-11  
**Status:** ✅ ALL TESTS PASSED (9/9)

### Test Coverage

| Test | Status |
|------|--------|
| All instances exist | ✅ PASS |
| Instance structure valid | ✅ PASS |
| Detector files present | ✅ PASS |
| Database creation | ✅ PASS |
| Config validity | ✅ PASS |
| Article links | ✅ PASS |
| ATM database setup | ✅ PASS |
| ATM detector initialization | ✅ PASS |
| API endpoints | ✅ PASS |

## Instances Created (20 total)

### ATM Monitoring (separate system)
- `atm-monitoring` — ATM Anomaly Detection (14 classes)

### VIMS Core Instances (19)
| # | Instance | Article | Classes |
|---|----------|---------|---------|
| 1 | street-lighting | Evidence-Driven Municipal Maintenance | 4 |
| 2 | bridge-inspection | Bridge Inspection Software Comparison | 5 |
| 3 | retail-analytics | Retail Site Selection Data | 5 |
| 4 | insurance-risk | Pre-Loss Surveys Insurance | 5 |
| 5 | municipal-maintenance | Evidence-Driven Municipal Maintenance | 6 |
| 6 | construction-site | Future of Infrastructure Monitoring | 5 |
| 7 | real-estate-condition | Real Estate Due Diligence | 5 |
| 8 | urban-decay | How to Measure Urban Decay | 5 |
| 9 | crowdsourced-verification | Ground Truth Verification | 5 |
| 10 | data-quality | Can You Trust Crowdsourced Data? | 5 |
| 11 | insurance-contradiction | Insurance Contradiction Analysis | 5 |
| 12 | continuous-monitoring | Continuous vs Periodic Inspection | 5 |
| 13 | decision-intelligence | Decision-First Intelligence | 5 |
| 14 | satellite-validation | Field Intelligence vs Satellite | 5 |
| 15 | cost-stale-data | Calculate Cost of Stale Data | 5 |
| 16 | contradiction-gap | The Contradiction Gap | 5 |
| 17 | consensus-engine | How the Consensus Engine Works | 5 |
| 18 | official-statistics | The Problem with Official Statistics | 5 |
| 19 | preventive-maintenance | Economics of Preventive Maintenance | 5 |

## Architecture

```
┌─────────────────────────────────────────┐
│         VIMS Core Framework             │
├─────────────────────────────────────────┤
│  Core:                                  │
│  • base_detector.py (abstract base)     │
│  • database.py (SQLite/PostgreSQL)      │
│  • api_base.py (FastAPI router)         │
├─────────────────────────────────────────┤
│  Instances:                             │
│  • 19 topic-specific detectors          │
│  • 19 databases (SQLite)                │
│  • 19 API endpoints                     │
├─────────────────────────────────────────┤
│  ATM System (separate):                 │
│  • Full FastAPI server                  │
│  • WebSocket alerts                     │
│  • Dashboard (HTML/JS)                  │
│  • Docker + docker-compose              │
│  • CI/CD (GitHub Actions)               │
└─────────────────────────────────────────┘
```

## Next Steps

1. **Train models** — Add training images to each instance's `data/raw/`
2. **Deploy** — Run `docker-compose up` in atm-anomaly-detection/
3. **Scale** — Create more instances with `scripts/create_instance.py`

## Commands

```bash
# Run all tests
cd vims-core && python3 -m pytest tests/ -v

# Create new instance
python3 vims-core/scripts/create_instance.py \
  --name "new-topic" \
  --display-name "New Topic Monitoring" \
  --classes "class1,class2,class3" \
  --article-url "/insights/article-slug/"

# Start ATM system
cd atm-anomaly-detection && docker-compose up
```