Overview

A manufacturing plant, equipped with 100 cameras, sought to fortify its security measures and operational efficiency through a comprehensive Video Management System (VMS). The goal was to implement sophisticated video analytics ensuring compliance, safety, and incident response across the facility.

Challenges

• Managing feeds from 100 cameras simultaneously for various security and compliance purposes.
• Ensuring adherence to safety protocols, fire detection, intrusion monitoring, and operational area management.
• Efficiently allocating GPU resources to handle diverse video analytics requirements.
• Cost-effective hardware selection for seamless and efficient operations.

Solution

The implementation involved leveraging Nvidia Tesla V100 GPUs known for their computational prowess and adeptness in handling complex AI-driven tasks. Use case distribution across cameras was meticulously mapped to optimize GPU utilization efficiently. SOP compliance, fire detection, intrusion monitoring, and area management were allocated to Tesla V100 GPUs for optimal performance. A singular setup of Tesla V100 GPUs was chosen to streamline management, reduce complexity, and meet the computational demands efficiently.

Use Case Distribution

• SOP Compliance: 80 cameras
• Fire & Loss of Primary Containment Detection: 100 cameras
• Vehicle Movement and Manpower Detection in No Entry Zone: 80 cameras
• Pathway Obstruction Detection: 30 cameras
• Monitoring Number of People in the Operational Area: 4 cameras in Dahej + 6 cameras in Uran
• Vehicle Speed Monitoring and NPR: 15 cameras
• Flare Monitoring: Only on Thermal Cameras (Edge Analytics)

Pricing

• Tesla V100 GPU: $8,000 per GPU (9 GPUs required) - Total cost for GPUs: $72,000
• System Requirements: Estimated at $10,000 per setup - Total cost for system setups: $90,000

Implementation

Tesla V100 GPUs efficiently managed multiple use cases assigned to different camera feeds using their 64 cores and high computational capacity. The allocation of use cases based on load (light, medium, heavy) optimized GPU resource utilization, ensuring seamless real-time monitoring and compliance enforcement. The VMS, powered by Tesla V100 GPUs, swiftly responded to security threats, compliance violations, and operational inefficiencies, ensuring accurate detection and rapid incident resolution.

Results

• Streamlined video analytics: Across 100 cameras, ensuring real-time monitoring and compliance enforcement.
• High accuracy and reliability: In identifying security breaches and compliance violations significantly bolstered the facility's security posture.
• Cost-effectiveness: The consolidation of use cases onto Tesla V100 GPUs maintained exceptional performance standards.

Conclusion

The strategic implementation of Nvidia Tesla V100 GPUs in the VMS highlighted their pivotal role in fortifying security and compliance in a manufacturing setting. By concentrating use cases onto a singular high-performance GPU type, the facility achieved operational efficiency, cost-effectiveness, and enhanced security measures.