System Requirements

This section details the hardware and software prerequisites to implement the Private Identity® Facial Age Estimation Portal effectively. It ensures developers, architects, and IT teams can design environments that meet performance and security demands.

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Hardware Requirements

1. Minimum CPU
   

   ARM Cortex-A53 or Intel Core i3 (or equivalents) with SIMD capabilities for optimized inference.

2. RAM
   

   ≥2 GB recommended for stable real-time inference; 4 GB for multi-tasking environments.

3. Camera
   

   Built-in or external camera with minimum 720p resolution for consistent facial capture.

4. Optional GPU Acceleration
   

   Devices with OpenCL or CUDA can achieve further inference speed-ups.

Software Requirements

1. Operating Systems
   
   • Mobile
     

     Android 8.0 (Oreo) or newer, iOS 12 or newer.

   • Desktop
     

     Windows 10+, macOS 10.13+, Linux (Ubuntu 20.04+, CentOS 7+)

   • Edge/IoT
     

     Linux-based distributions (e.g., Raspbian, Debian 10) with TensorFlow Lite or PyTorch Mobile support.

2. Runtime Environments
   
   • Node.js (v14.x+)
     

     For server-side APIs.

   • Python (3.7+)
     

     For advanced scripting or integration with data science pipelines.

   • Docker & Kubernetes
     

     For containerization and orchestration in production.

3. AI/ML Frameworks
   

   • TensorFlow Lite or PyTorch Mobile for local model execution.

   • MobileNetV2 (pre-quantized) model files for distribution with the Portal.

4. Security & Authentication
   

   • Google IAM or compatible identity platform for JWT token creation.

   • HTTPS/TLS 1.3 for secure channel encryption.

Integration Dependencies

1. REST Client Libraries: Axios, Fetch API, Retrofit, or any standard HTTP client.

2. Front-End Frameworks: React.js, Angular, Vue.js (for easy embedding of verification flows).

3. Middleware: OAuth 2.0 or OpenID Connect, if delegated identity control is required.