Group Design

Groups are the organizational containers in Anava that hold cameras, skills, and profiles. Well-designed group structure makes management scalable and efficient.

Understanding Groups

What is a Group?

A group is a logical container that:

• Holds one or more cameras
• Contains skills (AI analysis definitions)
• Contains profiles (trigger-to-skill mappings)
• Provides unified configuration for all devices

Group Properties

Property	Description
Name	Display name for the group
Description	Purpose and scope
Status	Active or inactive
Skills	AI analysis configurations
Profiles	Trigger-to-skill mappings
Cameras	Assigned devices

Design Principles

1. Group by Function, Not Location

Recommended:

├── Security Operations
│   ├── Perimeter Security (cameras: gates, fences)
│   ├── Entrance Control (cameras: doors, lobbies)
│   └── Restricted Areas (cameras: server rooms)
├── Safety Compliance
│   ├── PPE Zones (cameras: work areas)
│   └── Emergency Exits (cameras: exit paths)
└── Operations
    ├── Queue Monitoring (cameras: service areas)
    └── Occupancy Tracking (cameras: common spaces)

Avoid:

├── Building A (mixed purposes)
├── Building B (mixed purposes)
└── Parking (no clear function)

2. One Skill Set Per Group

Keep groups focused:

Good	Avoid
"Entrance Security" with entrance-focused skills	"All Security" with 20+ different skills
"PPE Compliance" with safety skills	"Everything" with unrelated skills mixed

3. Right-Size Your Groups

Scale	Recommended Cameras per Group
Small site	5-15 cameras
Medium site	10-25 cameras
Enterprise	15-50 cameras

Why? Groups that are too large become hard to manage. Too small creates configuration sprawl.

Common Patterns

Pattern 1: Function-Based Groups

Organize by what cameras monitor:

Best for:

• Clear functional boundaries
• Different teams manage different functions
• Skills are distinct per function

Pattern 2: Shift-Based Groups

Organize by when cameras are active:

├── 24/7 Critical (always monitored)
├── Business Hours (office areas)
├── After Hours (security focus)
└── Weekend Only (special events)

Best for:

• Strong schedule-based requirements
• Different security levels by time
• Resource optimization

Pattern 3: Zone-Based Groups

Organize by physical security zones:

├── Public Zone (visitor areas)
├── Semi-Secure (employee areas)
├── Secure Zone (controlled access)
└── Critical Zone (highest security)

Best for:

• Compliance requirements (NERC CIP, etc.)
• Access control integration
• Graduated response protocols

Pattern 4: Hybrid Approach

Combine patterns for complex sites:

├── Perimeter Security (function + 24/7)
│   ├── Fence Line Cameras
│   └── Gate Cameras
├── Building Entrance (function + business hours)
│   ├── Lobby Cameras
│   └── Door Cameras
└── Data Center (zone + 24/7)
    ├── Cage Cameras
    └── Aisle Cameras

Sizing Guidelines

When to Split Groups

Split a group when:

• Camera count exceeds 50
• Skills have conflicting purposes
• Different teams need different access
• Schedules are fundamentally different

When to Combine Groups

Combine groups when:

• Cameras share identical configurations
• Management overhead exceeds value
• Skills are reused across small groups

Group Limits

Metric	Soft Limit	Hard Limit
Cameras per group	50	100
Skills per group	10	25
Profiles per group	20	50

Enterprise Examples

Example 1: Corporate Campus

Groups:
  - name: "Campus Perimeter"
    cameras: 35
    skills: [Intrusion Detection, Vehicle Recognition]
    profiles: [24/7 Perimeter Watch, Gate Activity]

  - name: "Building Entrances"
    cameras: 24
    skills: [Entrance Security, Tailgating Detection]
    profiles: [Business Hours Entry, After Hours Alert]

  - name: "Executive Floor"
    cameras: 12
    skills: [Authorization Check, VIP Recognition]
    profiles: [Always On - High Alert]

  - name: "Parking Facilities"
    cameras: 28
    skills: [Vehicle Monitoring, Pedestrian Safety]
    profiles: [24/7 Vehicle Watch]

Example 2: Manufacturing Plant

Groups:
  - name: "Production Floor Safety"
    cameras: 40
    skills: [PPE Compliance, Hazard Zone]
    profiles: [Shift Hours PPE, Emergency Detection]

  - name: "Loading Dock Operations"
    cameras: 15
    skills: [Vehicle Detection, Package Tracking]
    profiles: [Business Hours Dock, Delivery Verification]

  - name: "Plant Perimeter"
    cameras: 25
    skills: [Intrusion Detection]
    profiles: [24/7 Perimeter]

  - name: "Quality Control"
    cameras: 10
    skills: [Defect Detection, Process Monitoring]
    profiles: [Production Hours QC]

Example 3: Retail Chain

# Per-Store Template
Groups:
  - name: "Store 001 - Sales Floor"
    cameras: 12
    skills: [Customer Analytics, Theft Prevention]
    profiles: [Store Hours Analytics]

  - name: "Store 001 - Backroom"
    cameras: 6
    skills: [Inventory Security, Employee Safety]
    profiles: [24/7 Backroom Watch]

  - name: "Store 001 - Entrance"
    cameras: 4
    skills: [Customer Counting, Shoplifting Alert]
    profiles: [Store Hours Entry]

Migration Planning

From Flat Structure

If you have all cameras in one group:

1. Inventory current setup

   • List all cameras and their purposes
   • Identify skill requirements per camera

2. Design new structure

   • Apply function-based or zone-based pattern
   • Create new groups (don't modify existing)

3. Migrate incrementally

   • Move 5-10 cameras at a time
   • Verify functionality after each batch
   • Keep old group until migration complete

From Legacy VMS Groups

If importing from VMS structure:

1. Don't replicate VMS groups directly

   • VMS groups often based on recorder capacity
   • Anava groups should be based on function

2. Map functions to new groups

   • Identify what each camera monitors
   • Group by analysis needs, not hardware

Best Practices

Naming Conventions

Pattern	Example	Use Case
Function-Location	Security-MainEntrance	Clear purpose
Zone-Function	ZoneA-Perimeter	Compliance-focused
Site-Function	HQ-ExecutiveFloor	Multi-site deployment

Documentation

Maintain for each group:

• Purpose and scope
• Camera inventory with purposes
• Skill/profile explanations
• Contact/escalation information

Review Cadence

Frequency	Review
Monthly	Camera additions/removals
Quarterly	Skill effectiveness
Annually	Group structure optimization

Troubleshooting

Too Many Groups

Symptoms:

• Configuration sprawl
• Duplicate skills across groups
• Management overhead high

Solution:

• Consolidate groups with similar purposes
• Use profiles for scheduling instead of separate groups

Too Few Groups

Symptoms:

• 100+ cameras in one group
• Conflicting skill requirements
• Can't give team-specific access

Solution:

• Split by function or zone
• Create focused groups with specific purposes

Related Topics

• Bulk Operations - Managing many cameras
• Device Overrides - Per-camera customization
• Groups Reference - Group configuration