📊 Device Monitoring Dashboard

A lightweight real-time system monitoring dashboard for multiple devices (Raspberry Pi, servers, PCs).

This project consists of:

• A Python API (Flask) that exposes system metrics
• A frontend dashboard that visualizes metrics in real-time

🚀 Features

• 🔥 Real-time CPU usage (total + per core)
• 🌡️ CPU temperature monitoring
• ⚡ CPU power usage (if supported)
• 🧠 RAM usage (GB + %)
• 💾 Disk usage
• 🌐 Network traffic (sent / received)
• 🔋 Battery status (for laptops)
• ⏱️ Uptime tracking
• ⚠️ Automatic warnings for:
• High CPU usage
• High RAM usage
• High temperature
• 📡 Multi-device support (monitor multiple machines at once)

🧠 How it works

• Backend (Python API)
• Uses Flask to expose a /metrics endpoint
• Uses psutil to collect system stats
• Returns all metrics as JSON
• Frontend (Dashboard)
• Fetches /metrics every 5 seconds
• Uses Chart.js for visualization
• Displays: CPU per core (bar chart) RAM & disk usage (doughnut charts) Temperature (bar) Shows warnings dynamically

⚙️ Tech Stack

• Python 3
• Flask
• psutil
• Chart.js
• HTML / CSS / JavaScript

🔧 Setup

1. Clone repository

git clone https://github.com/JorenS15/device-dashboard.git

2. Create virtual environment

python3 -m venv venv
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Run backend (I use docker for making this run in the background. But it doesn't matter how you do it)

python3 app.py

API runs on:

http://<device-ip>:5000/metrics

5. Configure frontend

Open the HTML file and change the placeholder Device names and ip adresses to yours:

const devices = [
    { name: "Raspberry Pi 5", url: "http://<ip>:5000/metrics" },
    { name: "Desktop PC", url: "http://<ip>:5000/metrics" },
];

6. Open dashboard

Open the HTML file in your browser.

⚠️ Notes

CPU temperature & power: Works best on Linux / Raspberry Pi
May not work on all systems
CPU power (RAPL): Only supported on some Intel CPUs
This project is designed for local network usage Not secured for public internet exposure

📌 Status

Actively used in a personal homelab environment.

Future improvements could include:

• Authentication
• Historical data storage
• Alerts via notifications (e.g. Home Assistant)

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Dashboard

Warning of cpu/ram/disk/temperature/...