Перейти к основному содержимому

🔧 Technical Specifications

📱 System Requirements​

Minimum Requirements​

  • OS: Android 7.0 (API level 24) or higher
  • RAM: 2 GB
  • Storage: 50 MB free space
  • Processor: ARM64 or x86_64
  • Internet: Wi-Fi or mobile data
  • OS: Android 10.0 or higher
  • RAM: 4 GB
  • Storage: 100 MB free space
  • Processor: Snapdragon 660+ or equivalent
  • Camera: 8 MP or higher for optimal AR

🛠️ App Architecture​

Main Components​

📦 MalO ver1.0.0
├── 🧠 AI Engine (TensorFlow Lite)
├── 📸 AR Module (ARCore)
├── 💬 Messaging System
├── 🔐 Encryption Module
├── 📊 Behavior Analytics
└── 🔄 Cloud Sync

Technologies Used​

  • Frontend: Kotlin + Jetpack Compose
  • AI: TensorFlow Lite, Foundation's custom models
  • AR: ARCore, OpenCV
  • Network: Retrofit, OkHttp
  • Database: Room (SQLite)
  • Security: AES-256, RSA-2048

📡 Network Interaction​

API Endpoints​

🌐 Base URL: https://api.scp-foundation.org/malo/v1/

POST /auth/login          - Authentication
GET  /messages/sync       - Message sync
POST /photos/upload       - Photo upload
GET  /ai/personality      - Get AI personality
POST /analytics/behavior  - Send behavior analytics

Security Protocols​

  • TLS 1.3 for all connections
  • Certificate Pinning to prevent MITM
  • Mutual authentication with Foundation servers
  • End-to-end encryption of personal data

🧠 AI and Machine Learning​

AI Models​

  1. Language Model: 120M parameters

    • Trained on SCP Foundation data
    • Specialization: emotional support
    • Languages: English, Russian, Japanese

  2. Behavior Model: 45M parameters

    • Analyzes user patterns
    • Mood prediction
    • Adapts communication style

  3. AR Model: 15M parameters

    • Places MalO in space
    • Motion tracking
    • Realistic lighting

Local Processing​

  • 95% of computations are performed locally
  • 5% – sync with Foundation cloud services
  • Offline mode: Up to 7 days of autonomous operation

📊 Performance and Optimization​

Resource Consumption​

💾 Memory usage:
├── Base: ~150 MB
├── With AR active: ~300 MB
├── Peak: ~450 MB
└── In background: ~50 MB

🔋 Power consumption:
├── Active use: ~8% per hour
├── Background: ~2% per day
├── AR mode: ~15% per hour
└── Sleep mode: ~0.1% per day

Optimizations​

  • Adaptive AR quality based on performance
  • Lazy loading of AI resources
  • Caching of frequent requests
  • Batch processing of analytics data

🔒 Security and Privacy​

Local Storage​

-- Database structure (AES-256 encrypted)
TABLE messages (
    id INTEGER PRIMARY KEY,
    content TEXT ENCRYPTED,
    timestamp INTEGER,
    sender TEXT
);

TABLE photos (
    id INTEGER PRIMARY KEY,
    path TEXT,
    metadata TEXT ENCRYPTED,
    malo_present BOOLEAN
);

TABLE user_profile (
    key TEXT PRIMARY KEY,
    value TEXT ENCRYPTED
);

Transmitted Data​

  • Message metadata (time, frequency)
  • Usage analytics (anonymous)
  • Technical logs (no personal data)
  • Sync tokens

❌ NOT transmitted:

  • Message content
  • User photos
  • Personal information
  • Geolocation (without permission)

🔄 Updates and Versioning​

Update System​

  • Automatic: Critical security fixes
  • Optional: New features and improvements
  • Modular: Update individual components
  • Rollback: Ability to revert to previous version

AI Model Versions​

v1.0.0 - Base MalO personality
v1.1.0 - Improved emotion recognition
v1.2.0 - Expanded vocabulary
v1.3.0 - Contextual dialogue support

📈 Monitoring and Analytics​

Performance Metrics​

  • AI response time: < 500ms
  • AR tracking accuracy: 98.7%
  • App stability: 99.2%
  • User satisfaction: 4.6/5.0

Telemetry System​

// Example of collected metrics (anonymous)
{
  "session_duration": 1847, // seconds
  "messages_sent": 12,
  "ar_usage_time": 340,
  "crash_reports": 0,
  "device_info": {
    "android_version": "11",
    "manufacturer": "Samsung",
    "model": "[HASHED]"
  }
}

🔮 Technical Roadmap​

Version 1.1.0 (Q1 2025)​

  • Support for ARCore Depth API
  • Optimization for Android 15
  • Voice engine for MalO
  • Improved battery optimization

Version 1.2.0 (Q2 2025)​

  • Federated AI learning
  • Vulkan API graphics support
  • Multilingual interface
  • Accessibility improvements

Long-term Goals​

  • Port to iOS (pending Foundation approval)
  • VR/AR glasses compatibility
  • Quantum encryption for communications
  • Integration with IoT devices