Requirements

System Requirements for VisionAIre

Hardware Requirements

GPU Acceleration:

• Minimum: NVIDIA GPU (e.g., NVIDIA GeForce RTX 1080 or equivalent)

• Recommended: NVIDIA Tesla, Quadro, or RTX series GPUs with CUDA Compute Capability 7.5 or higher for optimal performance and efficiency in processing video streams.

VisionAIre leverages GPU acceleration to efficiently process real-time video streams. Our AI models are optimized for CUDA-enabled NVIDIA GPUs, which significantly enhance the speed and efficiency of video analysis and processing tasks.

CPU:

• Minimum: Intel Core i5 or equivalent with at least 8 cores

• Recommended: Intel Xeon series or equivalent with 8 cores or more for improved overall system responsiveness and multitasking capabilities.

Memory:

• Minimum: 8 GB RAM

• Recommended: 16 GB RAM or higher to ensure smooth operation and handling of multiple video streams.

Storage:

• Solid State Drive (SSD) with at least 256 GB of available space for the installation and efficient operation of the VisionAIre platform, including space for temporary files and data caching.

Networking Hardware

Network Interface:

• Gigabit Ethernet (1 Gbps) for reliable and fast data transmission between VisionAIre and connected devices or network storage solutions.

Recommended Network Setup:

• High-speed internet connection with a minimum bandwidth of 100 Mbps for cloud-based model updates and real-time data exchange with external APIs or services.

• Quality of Service (QoS) configurations on network routers or switches to prioritize VisionAIre traffic, ensuring minimal latency and packet loss during critical operations.

• If applicable, consider setting up a dedicated network segment or VLAN for VisionAIre devices to isolate and protect video stream data.

Additional Considerations

Operating System:

• Linux distribution (Ubuntu 20.04 LTS or later).

• Ensure that the system has the latest drivers compatible with the GPU and other hardware components.

Software Dependencies:

• CUDA Toolkit and cuDNN library (matching the version requirements for the used NVIDIA GPU) for GPU acceleration.

• Docker (optional) for containerized deployment of the VisionAIre platform, simplifying installation and scalability.

Power Supply:

• Ensure a stable and sufficient power supply, especially for high-performance GPUs, which may require additional power connectors.

Cooling System:

• Adequate cooling solutions to maintain optimal operating temperatures for the GPU and CPU during intensive processing tasks.

Installation Guide