signal.repair

signal.repair is a utility application designed to monitor, diagnose, and forecast wireless and cellular connectivity issues on Android.

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🔍 Overview signal.repair is a utility app designed to monitor, diagnose, and forecast wireless and cellular connectivity issues on Android. It uses real-time telemetry extraction, statistical trends, linear regression modeling, and LLM-powered diagnostics to help users optimize their connection parameters and predict failures before they happen.

⚡ Key Features

  • 📊 Real-time Telemetry Dashboard: monitor live metrics like RSRP, RSRQ, RSSI, SINR, carrier details, active cell tower identifier, Wi-Fi link status, and real-time bandwidth (download/upload speeds and ping latency).
  • 📉 Predictive Failure Alerts: a background monitoring service runs linear regression trend forecasting on telemetry logs, alerting users to network degradation or handoff instabilities minutes before they occur.
  • 🧠 AI Signal Doctor: integrated with the Groq API Engine to read signal health snapshots and provide tailored troubleshooting recommendations.
  • 📋 Telecom Diagnostic Reports: generate and export downloadable PDF summaries of local connection stability, signal histories, and diagnostics.
  • 🔗 P2P Diagnostics Sharing: quickly broadcast local connection parameters and receive reports over a local network.
  • 🎨 Modern Design: built using Jetpack Compose, featuring smooth glassmorphism designs, dark mode styling, and clean charting using Vico.

🏗️ Architecture and Data Flow Below is the high-level system topology representing how data is collected, monitored, analyzed, and surfaced in signal.repair:

graph TD
    %% Telemetry Sources
    subgraph Telemetry Core
        TC[TelephonyManager] --> SDC[SignalDataCollector]
        WC[WifiManager] --> SDC
        NT[Active Ping/Speed Test] --> SDC
    end

    %% Storage and Background Processing
    subgraph Background Service
        SDC --> SMS[SignalMonitorService]
        SMS --> SP[SignalPredictor ML]
        SP -->|High Risk Trend| AN[Alert Notifications]

        SMS -->|Save Snapshot| SR[SignalRepository]
        SR --> RDB[(Room Database)]
    end

    %% UI and Output
    subgraph Presentation Layer
        RDB --> DVM[DashboardViewModel]
        RDB --> RVM[ReportViewModel]

        DVM --> DS[Dashboard Screen]
        RVM --> RS[Report Screen]
        RVM -->|iText Engine| PDF[Exported PDF Report]

        %% AI Integration
        SM[SettingsManager DataStore] -->|Dynamic Key| GAS[GroqApiService]
        RDB --> GAS
        GAS --> DrS[Doctor Screen]
    end

    classDef core fill:#00E5FF,stroke:#333,stroke-width:2px,color:#000;
    classDef storage fill:#ffab00,stroke:#333,stroke-width:2px,color:#000;
    classDef ui fill:#9c27b0,stroke:#333,stroke-width:2px,color:#fff;

    class SDC,SMS,SP core;
    class RDB,SR storage;
    class DS,RS,DrS,PDF ui;

🛠️ Tech Stack

  • UI Framework: Jetpack Compose
  • Architecture: MVVM (Model-View-ViewModel) + Repository Pattern
  • Dependency Injection: Dagger Hilt
  • Database: Room SQLite (Local Persistence)
  • Network Client: Retrofit 2 & OkHttp 4
  • AI Integration: Groq API (REST API)
  • Charts: Vico Chart Engine
  • PDF Generation: iText Core
  • Local Storage: Jetpack DataStore Preferences

🚀 Getting Started

📋 Prerequisites

  • Android SDK 26 (Android 8.0 Oreo) or higher
  • Android Studio Jellyfish / Koala or newer
  • A Groq API Key (optional, for AI features) from the Groq Console

🔑 Local Environment Setup

  1. Clone the Repository:

    git clone https://github.com/your-username/signalrepair.git
cd signalrepair

  2. Configure Environment Variables: Copy the template .env.example file to .env:

    cp .env.example .env

  3. Insert your Groq API Key inside .env:

    GROQ_API_KEY=gsk_your_actual_groq_api_key

    (Note: .env is automatically added to .gitignore and will never be pushed to your version control).

  4. Open in Android Studio and wait for Gradle sync to complete.

  5. **Build and Run

Built With

  • kotlin
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