Cross-Use Case Correlation¶
2.4 CROSS-USE CASE CORRELATION¶
Overview¶
Sections 2.1-2.3 presented three distinct use cases (UC1 Security, UC2 Building Automation, UC3 Safety) as independent capabilities. In practice, these use cases share the same Cisco Unified Edge infrastructure (UCS XE9305 + XE130c M8) and create powerful synergies through multi-use case correlation. This section demonstrates how integrating multiple AI-driven use cases on a single platform delivers compounded value beyond the sum of individual capabilities.
Key Architectural Principle:
Traditional siloed deployments would require: - Separate video analytics server for security - Separate occupancy sensors for building automation - Separate safety monitoring system for compliance
Abhavtech's unified approach deploys: - Single edge AI platform serving all three use cases - Shared camera infrastructure (same cameras feed multiple AI models) - Common integration layer (ISE, Splunk, ServiceNow, Webex used across use cases) - Unified observability (single GPU, single data pipeline, single management plane)
2.4.1 Infrastructure Sharing Model¶
Hardware Consolidation (Per Site):
Unified Edge AI Platform - UCS XE130c M8 (Slot 1, Primary)
┌─────────────────────────────────────────────────────────────┐
│ Hardware Layer (Cisco Unified Edge) │
├─────────────────────────────────────────────────────────────┤
│ Chassis: UCS XE9305 (3 RU, IDF Room Floor 3) │
│ Compute: UCS XE130c M8 (Intel Xeon 6 SoC, 32 cores) │
│ GPU: NVIDIA L4 24GB (120 TOPS INT8, 72W TDP) │
│ Memory: 128GB DDR5-4800 │
│ Storage: 2TB NVMe (512GB boot + 2× 1TB event buffer) │
│ Network: 2× 10G SFP+ LAG to Catalyst 9500 │
│ Power: 350W per node (700W total with standby) │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Camera Layer (Shared Across Use Cases) │
├─────────────────────────────────────────────────────────────┤
│ 135 Cameras per Site (Mumbai/Chennai) │
│ ├─ 65× Indoor Fixed (Axis P3715-PLVE) │
│ ├─ 40× Outdoor PTZ (Axis Q6215-LE) │
│ ├─ 20× 4K LPR (Axis P1455-LE) │
│ └─ 10× Thermal (FLIR A310f) │
│ │
│ Multi-Use Case Camera Assignment: │
│ ├─ Loading Dock (6 cameras): UC1 perimeter + UC3 PPE │
│ ├─ Hallways (14 cameras): UC1 loitering + UC3 slip/fall │
│ ├─ Conference Rooms (21 cameras): UC1 access + UC2 occupancy│
│ ├─ Cafeteria (8 cameras): UC1 crowd + UC2 HVAC + UC3 fall │
│ └─ Server Room (2 cameras): UC1 access + UC3 fire │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ AI Model Layer (GPU Resource Sharing) │
├─────────────────────────────────────────────────────────────┤
│ NVIDIA L4 GPU Utilization: 80-95% (combined UC1+UC2+UC3) │
│ │
│ UC1 Models (55-60% GPU): │
│ ├─ YOLO v8n Person Detection (20ms) │
│ ├─ DeepSORT Object Tracking (10ms) │
│ ├─ PPE CNN Classification (8ms) │
│ └─ LPR Pipeline (127ms) │
│ │
│ UC2 Models (15-20% GPU): │
│ └─ YOLO v8n Occupancy (reuses UC1 model, 20ms) │
│ │
│ UC3 Models (10-15% GPU): │
│ ├─ YOLO v8n + PPE CNN (28ms) │
│ ├─ Thermal Anomaly Detection (CPU-only, 0% GPU) │
│ └─ OpenPose Pose Estimation (45ms, FP16) │
│ │
│ Model Reuse: │
│ └─ YOLO v8n person detection shared by UC1, UC2, UC3 │
│ (single model inference, multiple downstream consumers) │
└─────────────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────────────┐
│ Integration Layer (Common APIs) │
├─────────────────────────────────────────────────────────────┤
│ ISE pxGrid: Badge correlation (UC1, UC2 after-hours, UC3) │
│ Splunk MLTK: Historical pattern validation (UC1, UC2) │
│ ThousandEyes: Network health validation (UC1) │
│ AppDynamics: Application health validation (UC1) │
│ BMS Honeywell: HVAC/lighting control (UC2), Fire alarm (UC3)│
│ FTD Firewall: Network blocking (UC1) │
│ XDR SecureX: Security incidents (UC1) │
│ ServiceNow: Incident management (UC1, UC2, UC3) │
│ Webex Teams: Mobile alerts (UC1, UC2, UC3) │
└─────────────────────────────────────────────────────────────┘
Infrastructure Utilization Breakdown:
| Resource | UC1 | UC2 | UC3 | Combined | Capacity | Utilization |
|---|---|---|---|---|---|---|
| GPU Compute | 55-60% | 15-20% | 10-15% | 80-95% | 100% | Optimal |
| GPU Memory | 18 GB | 850 MB | 4.3 GB | 23.15 GB | 24 GB | 96% (tight) |
| CPU Cores | 8 cores | 4 cores | 6 cores | 18 cores | 32 cores | 56% |
| Network (Inbound) | 960 Mbps | 0 Mbps* | 0 Mbps* | 960 Mbps | 20 Gbps | 5% |
| Network (Outbound) | 50 Mbps | 5 Mbps | 3 Mbps | 58 Mbps | 20 Gbps | <1% |
| Storage (Event Buffer) | 1.2 TB | 200 GB | 350 GB | 1.75 TB | 2 TB | 88% |
*UC2 and UC3 reuse video streams already ingested for UC1, requiring zero additional inbound bandwidth.
2.4.2 Summary: Unified Platform Benefits¶
Technical Benefits:
- Infrastructure Consolidation: Single UCS XE9305 platform replaces 3 separate systems
- Resource Efficiency: 80-95% GPU utilization across combined workloads (optimal target)
- Camera Reuse: Same cameras serve multiple use cases (security + occupancy + safety)
- Model Sharing: YOLO v8n person detection reused by UC1, UC2, UC3 (single inference, multiple consumers)
- Network Efficiency: 960 Mbps inbound (cameras) + 58 Mbps outbound (APIs) = 5% of 20 Gbps capacity
- Integration Layer: Common APIs (ISE, BMS, ServiceNow, Webex) shared across use cases
Operational Benefits:
- Single Management Plane: Cisco Intersight manages entire edge AI platform (vs 3 separate consoles)
- Unified Monitoring: All use cases visible in single Splunk dashboard
- Simplified Troubleshooting: Single hardware platform, single software stack
- Reduced Vendor Complexity: Single Cisco platform vs 3+ vendors
Business Benefits:
- Faster Deployment: Incremental use case enablement (UC1 → UC2 → UC3) vs parallel projects
- Enhanced Decision Quality: Cross-use case correlation creates context-aware automation
- Scalability: Phase 5 branch expansion leverages same platform (Slots 3-5 reserved)
Chapter 2 Summary¶
Chapter 2 documents three integrated use cases deployed on Abhavtech's Cisco Unified Edge platform:
- Section 2.1 (UC1): Intelligent Physical Security - 6 security functions, <500ms detection to response
- Section 2.2 (UC2): Building Automation - HVAC/lighting optimization, BMS integration
- Section 2.3 (UC3): Safety & Compliance - PPE detection, fire/smoke monitoring, slip/fall detection
- Section 2.4: Cross-Use Case Correlation - Multi-use case synergies and infrastructure sharing
Platform: Cisco UCS XE9305 chassis with UCS XE130c M8 compute nodes, NVIDIA L4 24GB GPU Network: Catalyst 9300 access + Catalyst 9500 distribution, 4ms camera-to-inference latency Integration: ISE, Splunk MLTK, ThousandEyes, AppDynamics, BMS, FTD, XDR, ServiceNow, Webex