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Cross-Platform CPU Info App with Kotlin Multiplatform

Discover CPU Info: A Comprehensive Cross-Platform Hardware and Software Analysis Tool CPU Info is an open-source application developed using Kotlin…

Discover CPU Info: A Comprehensive Cross-Platform Hardware and Software Analysis Tool

CPU Info is an open-source application developed using Kotlin Multiplatform (KMP) that provides detailed insights into your device’s hardware and software components. Designed for versatility, it supports multiple platforms including Android, Android TV, Wear OS, iOS, Desktop, and WebAssembly (Wasm). This makes it an ideal choice for developers and tech enthusiasts seeking a unified solution for system diagnostics across various devices.

Key Features:

  • CPU Specifications: View detailed information about your device’s CPU, including current frequencies for each core.
  • GPU Details: Access comprehensive data on your device’s graphics processing unit.
  • Memory and Storage: Monitor RAM usage and storage status, covering internal, external, and SD card memory.
  • Display Metrics: Obtain screen resolution, density, and other display-related information.
  • Operating System Info: Get insights into your device’s OS version and build details.
  • Sensor Data: Explore available sensors and their real-time data.
  • Battery Status: Check battery health, temperature, and charging status.
  • Network Interfaces: Retrieve MAC addresses for Wi-Fi and Bluetooth (on supported Android versions).
  • Audio Hardware: Identify audio components and configurations.
  • Application Management: Manage installed applications and view running processes (on supported Android versions).

Technical Stack:

CPU Info leverages modern technologies to ensure a robust and responsive user experience:

  • Kotlin Multiplatform for shared codebase across platforms.
  • Compose Multiplatform for declarative UI development.
  • Jetpack ViewModel/Lifecycle for efficient state management.
  • Coroutines for asynchronous programming.
  • Koin for dependency injection.
  • Coil for image loading.
  • DataStore for data persistence.
  • Integration with pytorch/cpuinfo and OSHI libraries for hardware information retrieval.

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