feat(boc): Complete Business Operations Center v1.0

- Go backend API with full CRUD for all modules (CRM, Sales, Finance, HR, Legal, Marketing, Support, Purchase, Inventory, Projects, Automation, Analytics)
- Rust analytics service with parallel report generation
- C runtime with POSIX shared memory IPC
- PostgreSQL schema with 30+ tables, full migrations
- Redis cache, sessions, pub/sub
- Kafka event streaming with Zookeeper
- WebSocket hub for real-time updates
- Automation engine with cron jobs, workflows, event triggers
- JWT authentication, multi-tenant from start
- Docker Compose with all services
- Nginx reverse proxy with rate limiting
- Integration tests passing
- Feature gap analysis against Fortnox/Odoo/Visma

Refs: BOC-001

vims-core/instances/construction-site/README.md

@@ -0,0 +1,27 @@
+# Construction Site Monitoring
+
+VIMS instance for construction-site.
+
+## Related Article
+[/insights/the-future-of-infrastructure-monitoring/](https://landvex.com/insights/the-future-of-infrastructure-monitoring/)
+
+## Anomaly Classes
+- safety_violation
+- equipment_idle
+- material_waste
+- progress_delay
+- unauthorized_access
+
+## Quick Start
+
+1. Add training images to `data/raw/`
+2. Annotate using LabelImg (YOLO format)
+3. Run preprocessing: `python src/detector.py`
+4. Train model: `python src/detector.py --train`
+5. Run inference: `python src/detector.py --predict data/test/image.jpg`
+
+## API
+
+Once deployed, access via:
+- REST: `POST /api/construction-site/predict`
+- WebSocket: `ws://host/ws/construction-site/alerts`

vims-core/instances/construction-site/config.yaml

@@ -0,0 +1,20 @@
+# construction-site configuration
+
+topic: construction-site
+display_name: Construction Site Monitoring
+article_url: /insights/the-future-of-infrastructure-monitoring/
+
+anomaly_classes:
+  - safety_violation
+  - equipment_idle
+  - material_waste
+  - progress_delay
+  - unauthorized_access
+
+model:
+  base: yolov8n.pt
+  input_size: 640
+  
+training:
+  epochs: 100
+  batch_size: 16

vims-core/instances/construction-site/src/database.py

@@ -0,0 +1,20 @@
+"""
+Database setup for Construction Site Monitoring
+"""
+
+import sys
+from pathlib import Path
+sys.path.append(str(Path(__file__).parent.parent.parent / "core"))
+
+from database import VIMSDatabase
+
+
+def setup():
+    """Initialize database for construction-site."""
+    db = VIMSDatabase("construction-site")
+    db.create_schema(anomaly_classes=['safety_violation', 'equipment_idle', 'material_waste', 'progress_delay', 'unauthorized_access'])
+    print(f"Database initialized for Construction Site Monitoring")
+
+
+if __name__ == "__main__":
+    setup()

vims-core/instances/construction-site/src/detector.py

@@ -0,0 +1,42 @@
+"""
+construction-site Anomaly Detector
+Generated by VIMS Instance Creator
+Related article: /insights/the-future-of-infrastructure-monitoring/
+"""
+
+import sys
+from pathlib import Path
+sys.path.append(str(Path(__file__).parent.parent.parent / "core"))
+
+from base_detector import VIMSBaseDetector, VIMSInstanceRegistry
+
+
+class ConstructionSiteDetector(VIMSBaseDetector):
+    """
+    Anomaly detector for Construction Site Monitoring.
+    
+    Article: /insights/the-future-of-infrastructure-monitoring/
+    """
+    
+    TOPIC = "construction-site"
+    CLASS_NAMES = {
+        0: "safety_violation", 1: "equipment_idle", 2: "material_waste", 3: "progress_delay", 4: "unauthorized_access"
+    }
+    
+    SEVERITY_MAP = {
+        "safety_violation": 3, "equipment_idle": 3, "material_waste": 3, "progress_delay": 3, "unauthorized_access": 3
+    }
+    
+    def preprocess(self, image):
+        """construction-site-specific preprocessing."""
+        # TODO: Implement specific preprocessing
+        return image
+    
+    def postprocess(self, raw_output):
+        """construction-site-specific postprocessing."""
+        # TODO: Implement specific postprocessing
+        return raw_output
+
+
+# Register instance
+VIMSInstanceRegistry.register("construction-site", ConstructionSiteDetector)