Analysis

Hardware Specifications

1. User Device Requirements:

   • Device: iPhone or iPad with iOS 15 or later.

   • Processor: A12 Bionic or newer for optimized machine learning performance.

   • Memory: Minimum 2GB RAM.

   • Storage: 100 MB free space for app installation (excluding user data).

   • Camera: Front or rear camera for optional photo capturing.

   • Connectivity: Wi-Fi or mobile data for API access and data synchronization.

2. Backend Server Requirements:

   • Processor: 4-core CPU or better (e.g., Intel Xeon or AMD EPYC).

   • Memory: 8GB RAM or higher for handling multiple user requests.

   • Storage: SSD storage with at least 100GB for user data and ML model storage.

   • Network: High-speed internet with 99.9% uptime for seamless connectivity.

Software Specifications

1. Frontend:

   • Operating System: iOS 15 or later.

   • Framework: SwiftUI for a responsive and clean user interface.

   • APIs: Integration with Apple CoreML for on-device machine learning and Vision framework for image recognition.

2. Backend:

   • Cloud Platform: AWS, Google Cloud, or Microsoft Azure for scalability and reliability.

   • Server: Node.js or Python-based backend for handling API requests.

   • Database: MongoDB or PostgreSQL for storing user outfit history and preferences.

   • APIs: OpenWeatherMap API for weather data, and Mood analysis API (e.g., Microsoft Azure Emotion API).

3. Machine Learning:

   • Model Framework: TensorFlow Lite or PyTorch for on-device ML model inference.

   • Pre-trained Models: Models for fashion recommendation and mood analysis fine-tuned on custom datasets.

   • Training Environment: High-performance GPUs or TPUs for training large datasets.

4. Security:

   • Authentication: OAuth 2.0 integration for secure login (e.g., Apple ID, Google, Facebook).

   • Data Encryption: TLS/SSL for data in transit; AES-256 for data at rest.

5. Development Tools:

   • IDE: Xcode for iOS app development.

   • Version Control: Git/GitHub for collaboration and versioning.