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<div align="center">
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# 🌡️ Lab Weather Tracker
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### *Environmental Monitoring System for Raspberry Pi*
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[](https://opensource.org/licenses/MIT)
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[](https://www.python.org/downloads/)
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[](https://www.raspberrypi.org/)
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*A professional Python-based weather monitoring system for tracking lab environmental conditions using the Pimoroni Enviro HAT*
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[Features](#-features) • [Installation](#-installation) • [Usage](#-usage) • [Dashboard](#-web-dashboard) • [Configuration](#-configuration)
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</div>
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---
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## 📋 Table of Contents
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- [Features](#-features)
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- [Hardware Requirements](#-hardware-requirements)
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- [Installation](#-installation)
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- [Usage](#-usage)
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- [Web Dashboard](#-web-dashboard)
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- [Temperature Compensation](#-temperature-compensation)
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- [Data Storage](#-data-storage)
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- [Running as a Service](#-running-as-a-service)
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- [Configuration](#-configuration)
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- [Troubleshooting](#-troubleshooting)
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- [Future Enhancements](#-future-enhancements)
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- [License](#-license)
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---
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## ✨ Features
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<table>
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<tr>
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<td width="50%">
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### 📊 Data Collection
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- 🌡️ **Temperature Monitoring** with CPU heat compensation
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- 💧 **Humidity Tracking** (relative humidity %)
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- 🔽 **Barometric Pressure** (hPa)
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- 💡 **Ambient Light** levels (lux)
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- 🎨 **Color Detection** (RGB values)
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</td>
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<td width="50%">
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### 🎯 Core Features
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- ⏱️ **5-minute sampling interval** (configurable)
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- 📁 **CSV logging** (one file per day)
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- 📈 **Real-time console display**
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- 🌐 **Web dashboard** with live charts
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- 🔄 **Auto-refresh** every 10 seconds
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- 📊 **Historical data** visualization
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</td>
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</tr>
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</table>
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### 🔥 Temperature Compensation
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This system implements **intelligent CPU temperature compensation** to ensure accurate ambient temperature readings:
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- 🧮 Compensates for Raspberry Pi CPU heat affecting the BME280 sensor
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- 📉 Uses rolling average of 5 CPU temperature samples to reduce jitter
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- 🎯 Applies scientifically-proven compensation formula
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- 📊 Logs both raw and compensated temperatures for analysis
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- ⚙️ Configurable compensation factor (default: 2.25)
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> **Formula:** `compensated_temp = raw_temp - ((avg_cpu_temp - raw_temp) / factor)`
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---
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## 🔧 Hardware Requirements
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| Component | Description |
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|-----------|-------------|
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| **Raspberry Pi** | Any model with 40-pin GPIO header (3/4/Zero recommended) |
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| **Pimoroni Enviro HAT** | Environmental monitoring HAT with BME280 & LTR559 sensors |
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| **Power Supply** | Official Raspberry Pi power supply (5V, 2.5A+) |
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| **microSD Card** | 8GB+ with Raspberry Pi OS installed |
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---
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## 📥 Installation
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### 1️⃣ Install System Dependencies
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```bash
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sudo apt-get update
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sudo apt-get install -y python3-pip python3-dev git
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```
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### 2️⃣ Clone the Repository
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```bash
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git clone https://github.com/yourusername/raspi-enviro.git
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cd raspi-enviro
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```
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### 3️⃣ Install Python Dependencies
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```bash
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pip3 install -r requirements.txt
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```
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### 4️⃣ Enable I2C Interface
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The Enviro HAT requires I2C to be enabled:
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```bash
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sudo raspi-config
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```
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Navigate to: **Interfacing Options → I2C → Enable**
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Then reboot:
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```bash
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sudo reboot
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```
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### 5️⃣ Verify Installation
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```bash
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i2cdetect -y 1
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```
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You should see device addresses `76` (BME280) and `23` (LTR559).
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---
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## 🚀 Usage
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### Console Mode (Data Logger)
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Start the weather tracker to log data every 5 minutes:
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```bash
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python3 weather_tracker.py
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```
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**Output:**
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```
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Lab Weather Tracker Starting...
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Logging interval: 300 seconds (5.0 minutes)
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✓ BME280 sensor initialized
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✓ LTR559 sensor initialized
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==================================================
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Lab Weather Report - 2025-12-03T14:23:45.123456
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==================================================
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Temperature (raw): 24.32°C
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Temperature (compensated): 21.85°C
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Pressure: 1013.25 hPa
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Humidity: 45.60%
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Light Level: 234.50 lux
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Proximity: 12.00
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==================================================
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✓ Data logged to data/weather_log_2025-12-03.csv
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Next reading in 300 seconds...
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```
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**Keyboard Shortcuts:**
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- `Ctrl + C` - Gracefully stop the tracker
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---
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## 🌐 Web Dashboard
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### Starting the Dashboard
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```bash
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python3 web_dashboard.py
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```
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Then open your browser:
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- **Local:** `http://localhost:5000`
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- **Network:** `http://<raspberry-pi-ip>:5000`
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### Dashboard Features
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<table>
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<tr>
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<td width="50%">
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#### 📊 Current Readings Card
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- Live temperature (compensated + raw)
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- Real-time pressure
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- Current humidity
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- Light levels
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- Color swatch visualization
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</td>
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<td width="50%">
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#### 📈 Analytics
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- Min/Max/Average statistics
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- Historical trend charts
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- Last 100 data points
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- Auto-refresh every 60 seconds
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- Responsive mobile design
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</td>
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</tr>
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</table>
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### Dashboard Preview
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```
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╔════════════════════════════════════════════╗
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║ MBTECH Binglab Envoro Dashboard ║
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╠════════════════════════════════════════════╣
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║ ║
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║ 🌡️ Temperature 🔽 Pressure ║
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║ 21.85°C 1013.25 hPa ║
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║ Raw: 24.32°C ║
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║ ║
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║ 💡 Light 🎨 Color ║
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║ 234.5 lux [■■■] ║
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║ ║
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╠════════════════════════════════════════════╣
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║ 📊 Today's Statistics ║
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║ Temperature: 18.2°C - 22.5°C (avg 20.3) ║
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║ Pressure: 1010-1015 hPa (avg 1012.5) ║
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║ ║
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╠════════════════════════════════════════════╣
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║ 📈 Historical Trends (24 hours) ║
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║ [Temperature Chart] ║
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║ [Pressure Chart] ║
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║ [Light Chart] ║
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╚════════════════════════════════════════════╝
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```
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> **💡 Tip:** Run both the tracker and dashboard simultaneously! The tracker logs data, while the dashboard displays it.
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---
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## 🌡️ Temperature Compensation
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### Why Temperature Compensation?
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The BME280 sensor is located near the Raspberry Pi CPU, which generates heat. This causes raw temperature readings to be **2-5°C higher** than actual ambient temperature.
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### How It Works
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1. **Read CPU Temperature** from `/sys/class/thermal/thermal_zone0/temp`
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2. **Smooth with Rolling Average** of last 5 readings to reduce jitter
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3. **Apply Compensation Formula:**
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```python
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compensated_temp = raw_temp - ((avg_cpu_temp - raw_temp) / 2.25)
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```
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4. **Log Both Values** for comparison and analysis
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### Adjusting the Compensation Factor
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Edit the `TEMP_COMP_FACTOR` in both files:
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```python
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# weather_tracker.py (line 27)
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TEMP_COMP_FACTOR = 2.25 # Decrease for more compensation, increase for less
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# web_dashboard.py (line 40)
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TEMP_COMP_FACTOR = 2.25 # Keep values synchronized
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```
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**Tuning Guide:**
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- **Too Hot?** Decrease factor → `2.0` (more aggressive compensation)
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- **Too Cold?** Increase factor → `2.5` (less aggressive compensation)
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---
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## 💾 Data Storage
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Data is automatically saved to the `data/` directory:
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```
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data/
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├── weather_log_2025-12-01.csv
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├── weather_log_2025-12-02.csv
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└── weather_log_2025-12-03.csv
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```
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### CSV Format
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| Column | Description | Unit |
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|--------|-------------|------|
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| `timestamp` | ISO 8601 timestamp | - |
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| `temperature_raw_c` | Raw BME280 reading | °C |
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| `temperature_c` | CPU-compensated temperature | °C |
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| `pressure_hpa` | Barometric pressure | hPa |
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| `humidity_percent` | Relative humidity | % |
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| `light_lux` | Ambient light level | lux |
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| `proximity` | Proximity sensor value | - |
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**Example:**
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```csv
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timestamp,temperature_raw_c,temperature_c,pressure_hpa,humidity_percent,light_lux,proximity
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2025-12-03T14:23:45.123456,24.32,21.85,1013.25,45.60,234.50,12.00
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```
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---
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## 🔄 Running as a Service
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For 24/7 operation, configure systemd services:
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### Weather Tracker Service
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```bash
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sudo nano /etc/systemd/system/weather-tracker.service
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```
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```ini
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[Unit]
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Description=Lab Weather Tracker with Temperature Compensation
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After=network.target
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[Service]
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Type=simple
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User=pi
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WorkingDirectory=/home/pi/raspi-enviro
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ExecStart=/usr/bin/python3 /home/pi/raspi-enviro/weather_tracker.py
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Restart=on-failure
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RestartSec=10
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StandardOutput=journal
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StandardError=journal
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[Install]
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WantedBy=multi-user.target
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```
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### Web Dashboard Service
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```bash
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sudo nano /etc/systemd/system/weather-dashboard.service
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```
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```ini
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[Unit]
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Description=Lab Weather Dashboard
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After=network.target weather-tracker.service
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[Service]
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Type=simple
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User=pi
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WorkingDirectory=/home/pi/raspi-enviro
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ExecStart=/usr/bin/python3 /home/pi/raspi-enviro/web_dashboard.py
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Restart=on-failure
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RestartSec=10
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Environment="FLASK_ENV=production"
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StandardOutput=journal
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StandardError=journal
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[Install]
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WantedBy=multi-user.target
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```
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### Enable and Start Services
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```bash
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# Enable auto-start on boot
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sudo systemctl enable weather-tracker.service
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sudo systemctl enable weather-dashboard.service
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# Start services now
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sudo systemctl start weather-tracker.service
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sudo systemctl start weather-dashboard.service
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# Check status
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sudo systemctl status weather-tracker.service
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sudo systemctl status weather-dashboard.service
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# View logs
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journalctl -u weather-tracker.service -f
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journalctl -u weather-dashboard.service -f
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```
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### Service Management Commands
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```bash
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# Stop services
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sudo systemctl stop weather-tracker.service
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sudo systemctl stop weather-dashboard.service
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# Restart services
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sudo systemctl restart weather-tracker.service
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sudo systemctl restart weather-dashboard.service
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# Disable auto-start
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sudo systemctl disable weather-tracker.service
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sudo systemctl disable weather-dashboard.service
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```
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---
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## ⚙️ Configuration
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### weather_tracker.py
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```python
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# Line 25-27
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DATA_DIR = "data" # Change data storage location
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LOG_INTERVAL = 300 # Seconds between readings (300 = 5 min)
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TEMP_COMP_FACTOR = 2.25 # Temperature compensation tuning
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```
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### web_dashboard.py
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```python
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# Line 38-40
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DATA_DIR = "data" # Must match weather_tracker.py
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MAX_HISTORY_POINTS = 100 # Number of points on charts
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TEMP_COMP_FACTOR = 2.25 # Temperature compensation tuning
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```
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**Common Configurations:**
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| Interval | Seconds | Use Case |
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|----------|---------|----------|
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| 1 minute | `60` | High-frequency monitoring |
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| 5 minutes | `300` | **Default** - Balanced |
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| 15 minutes | `900` | Low power consumption |
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| 1 hour | `3600` | Long-term trends |
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---
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## 🔍 Troubleshooting
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### ❌ `ImportError: No module named 'bme280'`
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**Solution:**
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```bash
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pip3 install pimoroni-bme280
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pip3 install smbus2
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```
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||||
### ❌ I2C Errors / Sensor Not Detected
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**Solution:**
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```bash
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# 1. Enable I2C
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sudo raspi-config # Interface Options → I2C → Enable
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# 2. Check I2C devices
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i2cdetect -y 1
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||||
# 3. Add user to i2c group
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sudo usermod -a -G i2c $USER
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newgrp i2c # Or logout and login again
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# 4. Verify connections
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# BME280 should show at 0x76
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# LTR559 should show at 0x23
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||||
```
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||||
### ❌ Permission Denied Errors
|
||||
|
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**Solution:**
|
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```bash
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sudo usermod -a -G i2c,gpio $USER
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sudo chmod 644 /sys/class/thermal/thermal_zone0/temp
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||||
```
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||||
### ❌ Web Dashboard Not Accessible from Network
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**Solution:**
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```bash
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# 1. Check firewall
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sudo ufw allow 5000/tcp
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# 2. Find Raspberry Pi IP address
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hostname -I
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# 3. Verify Flask is running on all interfaces
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# web_dashboard.py line 176 should be:
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# app.run(host='0.0.0.0', port=5000, ...)
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||||
```
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||||
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||||
### ❌ Temperature Readings Too High/Low
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**Solution:**
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Adjust the `TEMP_COMP_FACTOR`:
|
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- **Too high?** Decrease factor (e.g., `2.0` for more compensation)
|
||||
- **Too low?** Increase factor (e.g., `2.5` for less compensation)
|
||||
|
||||
Test with a calibrated thermometer and adjust accordingly.
|
||||
|
||||
---
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||||
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||||
## 🎯 Future Enhancements
|
||||
|
||||
### Planned Features
|
||||
|
||||
- [ ] 📧 Email/SMS alerts for threshold breaches
|
||||
- [ ] 🏠 Home Assistant integration
|
||||
- [ ] 🗄️ Database storage (SQLite/InfluxDB)
|
||||
- [ ] 📥 CSV export from web dashboard
|
||||
- [ ] 📊 Multi-day comparison views
|
||||
- [ ] 🔔 Push notifications
|
||||
- [ ] 📱 Mobile app
|
||||
- [ ] ☁️ Cloud sync capabilities
|
||||
- [ ] 🤖 AI-powered anomaly detection
|
||||
- [ ] 📈 Predictive analytics
|
||||
|
||||
### Contributing
|
||||
|
||||
Contributions are welcome! Feel free to:
|
||||
- 🐛 Report bugs
|
||||
- 💡 Suggest features
|
||||
- 🔧 Submit pull requests
|
||||
|
||||
---
|
||||
|
||||
## 📄 License
|
||||
|
||||
```
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2025 MBTECH
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
<div align="center">
|
||||
|
||||
### Made with ❤️ by MBTECH
|
||||
|
||||
**MBTECH Binglab Environmental Monitoring System**
|
||||
|
||||
*Keeping your lab conditions perfect, one reading at a time.*
|
||||
|
||||
[](https://github.com/yourusername/raspi-enviro)
|
||||
[](#)
|
||||
[](#)
|
||||
|
||||
</div>
|
||||
4
requirements.txt
Normal file
4
requirements.txt
Normal file
@@ -0,0 +1,4 @@
|
||||
pimoroni-bme280>=1.0.0
|
||||
ltr559>=1.0.0
|
||||
smbus2
|
||||
Flask>=2.3.0
|
||||
218
static/style.css
Normal file
218
static/style.css
Normal file
@@ -0,0 +1,218 @@
|
||||
* {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
|
||||
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
|
||||
min-height: 100vh;
|
||||
padding: 20px;
|
||||
color: #333;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 1400px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
header {
|
||||
text-align: center;
|
||||
color: white;
|
||||
margin-bottom: 40px;
|
||||
}
|
||||
|
||||
header h1 {
|
||||
font-size: 2.5rem;
|
||||
margin-bottom: 10px;
|
||||
text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.subtitle {
|
||||
font-size: 1.1rem;
|
||||
opacity: 0.9;
|
||||
}
|
||||
|
||||
h2 {
|
||||
color: white;
|
||||
margin-bottom: 20px;
|
||||
font-size: 1.5rem;
|
||||
}
|
||||
|
||||
.current-readings {
|
||||
background: white;
|
||||
border-radius: 15px;
|
||||
padding: 30px;
|
||||
margin-bottom: 30px;
|
||||
box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.reading-cards {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
|
||||
gap: 20px;
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.card {
|
||||
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
|
||||
border-radius: 12px;
|
||||
padding: 25px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 15px;
|
||||
transition: transform 0.3s ease, box-shadow 0.3s ease;
|
||||
}
|
||||
|
||||
.card:hover {
|
||||
transform: translateY(-5px);
|
||||
box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
|
||||
.temperature-card {
|
||||
background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
|
||||
}
|
||||
|
||||
.pressure-card {
|
||||
background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
|
||||
}
|
||||
|
||||
.light-card {
|
||||
background: linear-gradient(135deg, #ffecd2 0%, #fcb69f 100%);
|
||||
}
|
||||
|
||||
.color-card {
|
||||
background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);
|
||||
}
|
||||
|
||||
.card-icon {
|
||||
font-size: 2.5rem;
|
||||
}
|
||||
|
||||
.card-content {
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
.card-value {
|
||||
font-size: 2rem;
|
||||
font-weight: bold;
|
||||
color: white;
|
||||
text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.card-label {
|
||||
font-size: 0.9rem;
|
||||
color: rgba(255, 255, 255, 0.9);
|
||||
margin-top: 5px;
|
||||
}
|
||||
|
||||
.color-swatch {
|
||||
width: 60px;
|
||||
height: 60px;
|
||||
border-radius: 8px;
|
||||
border: 3px solid white;
|
||||
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.last-update {
|
||||
text-align: right;
|
||||
color: #666;
|
||||
font-size: 0.9rem;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
.stats-section {
|
||||
background: white;
|
||||
border-radius: 15px;
|
||||
padding: 30px;
|
||||
margin-bottom: 30px;
|
||||
box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.stats-grid {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
|
||||
gap: 20px;
|
||||
}
|
||||
|
||||
.stat-card {
|
||||
background: #f8f9fa;
|
||||
border-radius: 10px;
|
||||
padding: 20px;
|
||||
border-left: 4px solid #667eea;
|
||||
}
|
||||
|
||||
.stat-title {
|
||||
font-size: 1.2rem;
|
||||
font-weight: bold;
|
||||
color: #667eea;
|
||||
margin-bottom: 15px;
|
||||
}
|
||||
|
||||
.stat-values {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 10px;
|
||||
}
|
||||
|
||||
.stat-item {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
padding: 8px 0;
|
||||
border-bottom: 1px solid #e0e0e0;
|
||||
}
|
||||
|
||||
.stat-item:last-child {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.stat-label {
|
||||
color: #666;
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
.stat-value {
|
||||
font-weight: bold;
|
||||
color: #333;
|
||||
}
|
||||
|
||||
.charts-section {
|
||||
background: white;
|
||||
border-radius: 15px;
|
||||
padding: 30px;
|
||||
box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
|
||||
}
|
||||
|
||||
.chart-container {
|
||||
background: #f8f9fa;
|
||||
border-radius: 10px;
|
||||
padding: 20px;
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.chart-container:last-child {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
@media (max-width: 768px) {
|
||||
header h1 {
|
||||
font-size: 2rem;
|
||||
}
|
||||
|
||||
.reading-cards {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
|
||||
.stats-grid {
|
||||
grid-template-columns: 1fr;
|
||||
}
|
||||
|
||||
.card {
|
||||
padding: 20px;
|
||||
}
|
||||
|
||||
.card-value {
|
||||
font-size: 1.5rem;
|
||||
}
|
||||
}
|
||||
366
templates/dashboard.html
Normal file
366
templates/dashboard.html
Normal file
@@ -0,0 +1,366 @@
|
||||
<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Lab Weather Dashboard</title>
|
||||
<link
|
||||
rel="stylesheet"
|
||||
href="{{ url_for('static', filename='style.css') }}"
|
||||
/>
|
||||
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<header>
|
||||
<h1>MBTECH Binglab Envoro Dashboard</h1>
|
||||
<p class="subtitle">Environmental Monitoring System</p>
|
||||
</header>
|
||||
|
||||
<div class="current-readings">
|
||||
<h2>Current Conditions</h2>
|
||||
<div class="reading-cards">
|
||||
<div class="card temperature-card">
|
||||
<div class="card-icon">🌡️</div>
|
||||
<div class="card-content">
|
||||
<div class="card-value" id="current-temp">--</div>
|
||||
<div class="card-label">Temperature (°C)</div>
|
||||
<div class="card-sublabel" id="temp-raw" style="font-size: 0.85em; color: #888; margin-top: 4px;">Raw: --°C</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card pressure-card">
|
||||
<div class="card-icon">🔽</div>
|
||||
<div class="card-content">
|
||||
<div class="card-value" id="current-pressure">
|
||||
--
|
||||
</div>
|
||||
<div class="card-label">Pressure (hPa)</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card light-card">
|
||||
<div class="card-icon">💡</div>
|
||||
<div class="card-content">
|
||||
<div class="card-value" id="current-light">--</div>
|
||||
<div class="card-label">Light (lux)</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card color-card">
|
||||
<div class="card-icon">🎨</div>
|
||||
<div class="card-content">
|
||||
<div class="color-swatch" id="color-swatch"></div>
|
||||
<div class="card-label">Detected Color</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="last-update">
|
||||
Last update: <span id="last-update">--</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="stats-section">
|
||||
<h2>Today's Statistics</h2>
|
||||
<div class="stats-grid">
|
||||
<div class="stat-card">
|
||||
<div class="stat-title">Temperature</div>
|
||||
<div class="stat-values">
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Min:</span>
|
||||
<span class="stat-value" id="temp-min">--</span
|
||||
>°C
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Max:</span>
|
||||
<span class="stat-value" id="temp-max">--</span
|
||||
>°C
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Avg:</span>
|
||||
<span class="stat-value" id="temp-avg">--</span
|
||||
>°C
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="stat-card">
|
||||
<div class="stat-title">Pressure</div>
|
||||
<div class="stat-values">
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Min:</span>
|
||||
<span class="stat-value" id="pressure-min"
|
||||
>--</span
|
||||
>
|
||||
hPa
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Max:</span>
|
||||
<span class="stat-value" id="pressure-max"
|
||||
>--</span
|
||||
>
|
||||
hPa
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Avg:</span>
|
||||
<span class="stat-value" id="pressure-avg"
|
||||
>--</span
|
||||
>
|
||||
hPa
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="stat-card">
|
||||
<div class="stat-title">Light</div>
|
||||
<div class="stat-values">
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Min:</span>
|
||||
<span class="stat-value" id="light-min"
|
||||
>--</span
|
||||
>
|
||||
lux
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Max:</span>
|
||||
<span class="stat-value" id="light-max"
|
||||
>--</span
|
||||
>
|
||||
lux
|
||||
</div>
|
||||
<div class="stat-item">
|
||||
<span class="stat-label">Avg:</span>
|
||||
<span class="stat-value" id="light-avg"
|
||||
>--</span
|
||||
>
|
||||
lux
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="charts-section">
|
||||
<h2>Historical Data</h2>
|
||||
<div class="chart-container">
|
||||
<canvas id="temperatureChart"></canvas>
|
||||
</div>
|
||||
<div class="chart-container">
|
||||
<canvas id="pressureChart"></canvas>
|
||||
</div>
|
||||
<div class="chart-container">
|
||||
<canvas id="lightChart"></canvas>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
let tempChart, pressureChart, lightChart;
|
||||
|
||||
// Initialize charts
|
||||
function initCharts() {
|
||||
const commonOptions = {
|
||||
responsive: true,
|
||||
maintainAspectRatio: true,
|
||||
aspectRatio: 3,
|
||||
plugins: {
|
||||
legend: {
|
||||
display: false,
|
||||
},
|
||||
},
|
||||
scales: {
|
||||
x: {
|
||||
type: "category",
|
||||
ticks: {
|
||||
maxTicksLimit: 10,
|
||||
},
|
||||
},
|
||||
y: {
|
||||
beginAtZero: false,
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
tempChart = new Chart(
|
||||
document.getElementById("temperatureChart"),
|
||||
{
|
||||
type: "line",
|
||||
data: {
|
||||
labels: [],
|
||||
datasets: [
|
||||
{
|
||||
label: "Temperature (°C)",
|
||||
data: [],
|
||||
borderColor: "#ff6b6b",
|
||||
backgroundColor: "rgba(255, 107, 107, 0.1)",
|
||||
tension: 0.4,
|
||||
fill: true,
|
||||
},
|
||||
],
|
||||
},
|
||||
options: commonOptions,
|
||||
},
|
||||
);
|
||||
|
||||
pressureChart = new Chart(
|
||||
document.getElementById("pressureChart"),
|
||||
{
|
||||
type: "line",
|
||||
data: {
|
||||
labels: [],
|
||||
datasets: [
|
||||
{
|
||||
label: "Pressure (hPa)",
|
||||
data: [],
|
||||
borderColor: "#4ecdc4",
|
||||
backgroundColor: "rgba(78, 205, 196, 0.1)",
|
||||
tension: 0.4,
|
||||
fill: true,
|
||||
},
|
||||
],
|
||||
},
|
||||
options: commonOptions,
|
||||
},
|
||||
);
|
||||
|
||||
lightChart = new Chart(document.getElementById("lightChart"), {
|
||||
type: "line",
|
||||
data: {
|
||||
labels: [],
|
||||
datasets: [
|
||||
{
|
||||
label: "Light (lux)",
|
||||
data: [],
|
||||
borderColor: "#ffe66d",
|
||||
backgroundColor: "rgba(255, 230, 109, 0.1)",
|
||||
tension: 0.4,
|
||||
fill: true,
|
||||
},
|
||||
],
|
||||
},
|
||||
options: commonOptions,
|
||||
});
|
||||
}
|
||||
|
||||
// Update current readings
|
||||
async function updateCurrent() {
|
||||
try {
|
||||
const response = await fetch("/api/current");
|
||||
const data = await response.json();
|
||||
|
||||
document.getElementById("current-temp").textContent =
|
||||
data.temperature;
|
||||
|
||||
// Update raw temperature if available
|
||||
if (data.temperature_raw !== undefined) {
|
||||
document.getElementById("temp-raw").textContent =
|
||||
`Raw: ${data.temperature_raw}°C`;
|
||||
}
|
||||
|
||||
document.getElementById("current-pressure").textContent =
|
||||
data.pressure;
|
||||
document.getElementById("current-light").textContent =
|
||||
data.light;
|
||||
document.getElementById("last-update").textContent =
|
||||
data.timestamp;
|
||||
|
||||
// Update color swatch if RGB data is available
|
||||
if (data.rgb) {
|
||||
const colorSwatch = document.getElementById("color-swatch");
|
||||
colorSwatch.style.backgroundColor = `rgb(${data.rgb.r}, ${data.rgb.g}, ${data.rgb.b})`;
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching current data:", error);
|
||||
}
|
||||
}
|
||||
|
||||
// Update statistics
|
||||
async function updateStats() {
|
||||
try {
|
||||
const response = await fetch("/api/stats");
|
||||
const data = await response.json();
|
||||
|
||||
if (data.temperature) {
|
||||
document.getElementById("temp-min").textContent =
|
||||
data.temperature.min;
|
||||
document.getElementById("temp-max").textContent =
|
||||
data.temperature.max;
|
||||
document.getElementById("temp-avg").textContent =
|
||||
data.temperature.avg;
|
||||
}
|
||||
|
||||
if (data.pressure) {
|
||||
document.getElementById("pressure-min").textContent =
|
||||
data.pressure.min;
|
||||
document.getElementById("pressure-max").textContent =
|
||||
data.pressure.max;
|
||||
document.getElementById("pressure-avg").textContent =
|
||||
data.pressure.avg;
|
||||
}
|
||||
|
||||
if (data.light) {
|
||||
document.getElementById("light-min").textContent =
|
||||
data.light.min;
|
||||
document.getElementById("light-max").textContent =
|
||||
data.light.max;
|
||||
document.getElementById("light-avg").textContent =
|
||||
data.light.avg;
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching stats:", error);
|
||||
}
|
||||
}
|
||||
|
||||
// Update historical charts
|
||||
async function updateHistory() {
|
||||
try {
|
||||
const response = await fetch("/api/history");
|
||||
const data = await response.json();
|
||||
|
||||
if (data.length === 0) return;
|
||||
|
||||
const labels = data.map((d) => {
|
||||
const date = new Date(d.timestamp);
|
||||
return date.toLocaleTimeString("en-US", {
|
||||
hour: "2-digit",
|
||||
minute: "2-digit",
|
||||
});
|
||||
});
|
||||
|
||||
const temps = data.map((d) => d.temperature);
|
||||
const pressures = data.map((d) => d.pressure);
|
||||
const lights = data.map((d) => d.light);
|
||||
|
||||
tempChart.data.labels = labels;
|
||||
tempChart.data.datasets[0].data = temps;
|
||||
tempChart.update();
|
||||
|
||||
pressureChart.data.labels = labels;
|
||||
pressureChart.data.datasets[0].data = pressures;
|
||||
pressureChart.update();
|
||||
|
||||
lightChart.data.labels = labels;
|
||||
lightChart.data.datasets[0].data = lights;
|
||||
lightChart.update();
|
||||
} catch (error) {
|
||||
console.error("Error fetching history:", error);
|
||||
}
|
||||
}
|
||||
|
||||
// Initialize and start auto-refresh
|
||||
initCharts();
|
||||
updateCurrent();
|
||||
updateStats();
|
||||
updateHistory();
|
||||
|
||||
// Refresh current readings every 10 seconds
|
||||
setInterval(updateCurrent, 10000);
|
||||
|
||||
// Refresh stats and history every 60 seconds
|
||||
setInterval(() => {
|
||||
updateStats();
|
||||
updateHistory();
|
||||
}, 60000);
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
196
weather_tracker.py
Normal file
196
weather_tracker.py
Normal file
@@ -0,0 +1,196 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Lab Weather Tracker using Pimoroni Enviro Plus sensors
|
||||
Monitors temperature, humidity, pressure, and light levels
|
||||
"""
|
||||
|
||||
import time
|
||||
import csv
|
||||
import os
|
||||
from datetime import datetime
|
||||
from smbus2 import SMBus
|
||||
|
||||
try:
|
||||
from bme280 import BME280
|
||||
except ImportError:
|
||||
from pimoroni_bme280 import BME280
|
||||
|
||||
try:
|
||||
from ltr559 import LTR559
|
||||
ltr559 = LTR559()
|
||||
except ImportError:
|
||||
import ltr559
|
||||
|
||||
# Configuration
|
||||
DATA_DIR = "data"
|
||||
LOG_INTERVAL = 300 # 5 minutes in seconds
|
||||
TEMP_COMP_FACTOR = 2.25 # Tuning factor for temperature compensation
|
||||
|
||||
# Initialize sensors
|
||||
try:
|
||||
bus = SMBus(1)
|
||||
bme280 = BME280(i2c_dev=bus)
|
||||
print("✓ BME280 sensor initialized")
|
||||
except Exception as e:
|
||||
print(f"✗ Failed to initialize BME280: {e}")
|
||||
bme280 = None
|
||||
|
||||
try:
|
||||
if not isinstance(ltr559, LTR559):
|
||||
# Fallback initialization
|
||||
from ltr559 import LTR559
|
||||
ltr559 = LTR559()
|
||||
print("✓ LTR559 sensor initialized")
|
||||
except Exception as e:
|
||||
print(f"✗ Failed to initialize LTR559: {e}")
|
||||
ltr559 = None
|
||||
|
||||
# CPU temperature tracking for compensation
|
||||
cpu_temps = []
|
||||
|
||||
def get_cpu_temperature():
|
||||
"""Get the temperature of the CPU for compensation"""
|
||||
try:
|
||||
with open("/sys/class/thermal/thermal_zone0/temp", "r") as f:
|
||||
temp = f.read()
|
||||
temp = int(temp) / 1000.0
|
||||
return temp
|
||||
except Exception as e:
|
||||
print(f"Warning: Could not read CPU temperature: {e}")
|
||||
return None
|
||||
|
||||
def ensure_data_directory():
|
||||
"""Create data directory if it doesn't exist"""
|
||||
if not os.path.exists(DATA_DIR):
|
||||
os.makedirs(DATA_DIR)
|
||||
|
||||
def get_csv_filename():
|
||||
"""Generate CSV filename with current date"""
|
||||
date_str = datetime.now().strftime("%Y-%m-%d")
|
||||
return os.path.join(DATA_DIR, f"weather_log_{date_str}.csv")
|
||||
|
||||
def read_sensors():
|
||||
"""Read all sensor data and return as dictionary"""
|
||||
global cpu_temps
|
||||
|
||||
try:
|
||||
data = {
|
||||
'timestamp': datetime.now().isoformat(),
|
||||
}
|
||||
|
||||
# Read BME280 sensors (temperature, pressure, humidity)
|
||||
if bme280:
|
||||
try:
|
||||
raw_temp = bme280.get_temperature()
|
||||
pressure = bme280.get_pressure()
|
||||
humidity = bme280.get_humidity()
|
||||
|
||||
# Get CPU temperature and calculate compensated temperature
|
||||
cpu_temp = get_cpu_temperature()
|
||||
comp_temp = raw_temp # Default to raw if compensation fails
|
||||
|
||||
if cpu_temp is not None:
|
||||
# Smooth out with some averaging to decrease jitter
|
||||
cpu_temps.append(cpu_temp)
|
||||
if len(cpu_temps) > 5:
|
||||
cpu_temps = cpu_temps[-5:] # Keep only last 5 readings
|
||||
|
||||
if len(cpu_temps) > 0:
|
||||
avg_cpu_temp = sum(cpu_temps) / float(len(cpu_temps))
|
||||
# Compensate temperature using CPU temp
|
||||
comp_temp = raw_temp - ((avg_cpu_temp - raw_temp) / TEMP_COMP_FACTOR)
|
||||
|
||||
data.update({
|
||||
'temperature_raw_c': round(raw_temp, 2),
|
||||
'temperature_c': round(comp_temp, 2),
|
||||
'pressure_hpa': round(pressure, 2),
|
||||
'humidity_percent': round(humidity, 2),
|
||||
})
|
||||
except Exception as e:
|
||||
print(f"Error reading BME280: {e}")
|
||||
return None
|
||||
else:
|
||||
print("Error: BME280 sensor not available")
|
||||
return None
|
||||
|
||||
# Read LTR559 sensors (light and proximity)
|
||||
if ltr559:
|
||||
try:
|
||||
lux = ltr559.get_lux()
|
||||
proximity = ltr559.get_proximity()
|
||||
|
||||
data.update({
|
||||
'light_lux': round(lux, 2),
|
||||
'proximity': round(proximity, 2),
|
||||
})
|
||||
except Exception as e:
|
||||
print(f"Error reading LTR559: {e}")
|
||||
# Still return partial data
|
||||
|
||||
return data
|
||||
except Exception as e:
|
||||
print(f"Error reading sensors: {e}")
|
||||
return None
|
||||
|
||||
def log_to_csv(data):
|
||||
"""Append sensor data to CSV file"""
|
||||
filename = get_csv_filename()
|
||||
file_exists = os.path.isfile(filename)
|
||||
|
||||
try:
|
||||
with open(filename, 'a', newline='') as csvfile:
|
||||
fieldnames = data.keys()
|
||||
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
|
||||
|
||||
if not file_exists:
|
||||
writer.writeheader()
|
||||
|
||||
writer.writerow(data)
|
||||
|
||||
print(f"✓ Data logged to {filename}")
|
||||
except Exception as e:
|
||||
print(f"Error writing to CSV: {e}")
|
||||
|
||||
def display_data(data):
|
||||
"""Display current sensor readings"""
|
||||
print("\n" + "="*50)
|
||||
print(f"Lab Weather Report - {data['timestamp']}")
|
||||
print("="*50)
|
||||
if 'temperature_raw_c' in data:
|
||||
print(f"Temperature (raw): {data['temperature_raw_c']}°C")
|
||||
print(f"Temperature (compensated): {data['temperature_c']}°C")
|
||||
print(f"Pressure: {data['pressure_hpa']} hPa")
|
||||
if 'humidity_percent' in data:
|
||||
print(f"Humidity: {data['humidity_percent']}%")
|
||||
print(f"Light Level: {data['light_lux']} lux")
|
||||
if 'proximity' in data:
|
||||
print(f"Proximity: {data['proximity']}")
|
||||
print("="*50 + "\n")
|
||||
|
||||
def main():
|
||||
"""Main monitoring loop"""
|
||||
print("Lab Weather Tracker Starting...")
|
||||
print(f"Logging interval: {LOG_INTERVAL} seconds ({LOG_INTERVAL/60} minutes)")
|
||||
|
||||
ensure_data_directory()
|
||||
|
||||
try:
|
||||
while True:
|
||||
data = read_sensors()
|
||||
|
||||
if data:
|
||||
display_data(data)
|
||||
log_to_csv(data)
|
||||
|
||||
print(f"Next reading in {LOG_INTERVAL} seconds...")
|
||||
time.sleep(LOG_INTERVAL)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n\nShutting down gracefully...")
|
||||
print("Weather tracking stopped.")
|
||||
except Exception as e:
|
||||
print(f"\nUnexpected error: {e}")
|
||||
raise
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
212
web_dashboard.py
Normal file
212
web_dashboard.py
Normal file
@@ -0,0 +1,212 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Web Dashboard for Lab Weather Tracker
|
||||
Provides a simple web interface to view current and historical weather data
|
||||
"""
|
||||
|
||||
from flask import Flask, render_template, jsonify, request
|
||||
import csv
|
||||
import os
|
||||
from datetime import datetime, timedelta
|
||||
from collections import deque
|
||||
from smbus2 import SMBus
|
||||
|
||||
try:
|
||||
from bme280 import BME280
|
||||
except ImportError:
|
||||
from pimoroni_bme280 import BME280
|
||||
|
||||
try:
|
||||
from ltr559 import LTR559
|
||||
ltr559 = LTR559()
|
||||
except ImportError:
|
||||
import ltr559
|
||||
|
||||
# Initialize sensors
|
||||
SENSORS_AVAILABLE = False
|
||||
try:
|
||||
bus = SMBus(1)
|
||||
bme280_sensor = BME280(i2c_dev=bus)
|
||||
SENSORS_AVAILABLE = True
|
||||
except (ImportError, RuntimeError, OSError) as e:
|
||||
SENSORS_AVAILABLE = False
|
||||
print(f"Warning: Sensor libraries not available: {e}")
|
||||
print("Using mock data for testing.")
|
||||
|
||||
app = Flask(__name__)
|
||||
|
||||
DATA_DIR = "data"
|
||||
MAX_HISTORY_POINTS = 100 # Number of historical points to display
|
||||
TEMP_COMP_FACTOR = 2.25 # Tuning factor for temperature compensation
|
||||
|
||||
# CPU temperature tracking for compensation
|
||||
cpu_temps = []
|
||||
|
||||
def get_cpu_temperature():
|
||||
"""Get the temperature of the CPU for compensation"""
|
||||
try:
|
||||
with open("/sys/class/thermal/thermal_zone0/temp", "r") as f:
|
||||
temp = f.read()
|
||||
temp = int(temp) / 1000.0
|
||||
return temp
|
||||
except Exception as e:
|
||||
# CPU temp not available (e.g., on non-Linux systems)
|
||||
return None
|
||||
|
||||
def read_current_sensors():
|
||||
"""Read current sensor data"""
|
||||
global cpu_temps
|
||||
|
||||
if SENSORS_AVAILABLE:
|
||||
try:
|
||||
# Read temperature, pressure, humidity from BME280
|
||||
raw_temp = bme280_sensor.get_temperature()
|
||||
pressure = bme280_sensor.get_pressure()
|
||||
humidity = bme280_sensor.get_humidity()
|
||||
|
||||
# Get CPU temperature and calculate compensated temperature
|
||||
cpu_temp = get_cpu_temperature()
|
||||
comp_temp = raw_temp # Default to raw if compensation fails
|
||||
|
||||
if cpu_temp is not None:
|
||||
# Smooth out with some averaging to decrease jitter
|
||||
cpu_temps.append(cpu_temp)
|
||||
if len(cpu_temps) > 5:
|
||||
cpu_temps = cpu_temps[-5:] # Keep only last 5 readings
|
||||
|
||||
if len(cpu_temps) > 0:
|
||||
avg_cpu_temp = sum(cpu_temps) / float(len(cpu_temps))
|
||||
# Compensate temperature using CPU temp
|
||||
comp_temp = raw_temp - ((avg_cpu_temp - raw_temp) / TEMP_COMP_FACTOR)
|
||||
|
||||
# Read light data from LTR559
|
||||
lux = ltr559.get_lux()
|
||||
proximity = ltr559.get_proximity()
|
||||
|
||||
return {
|
||||
'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||
'temperature_raw': round(raw_temp, 2),
|
||||
'temperature': round(comp_temp, 2),
|
||||
'pressure': round(pressure, 2),
|
||||
'humidity': round(humidity, 2),
|
||||
'light': round(lux, 2),
|
||||
'proximity': round(proximity, 2)
|
||||
}
|
||||
except (OSError, IOError, RuntimeError) as e:
|
||||
print(f"Warning: I/O error reading sensors: {e}")
|
||||
print("Falling back to mock data. Check if sensors are properly connected.")
|
||||
return get_mock_data()
|
||||
except Exception as e:
|
||||
print(f"Unexpected error reading sensors: {e}")
|
||||
return get_mock_data()
|
||||
else:
|
||||
return get_mock_data()
|
||||
|
||||
def get_mock_data():
|
||||
"""Generate mock data for testing when sensors aren't available"""
|
||||
import random
|
||||
raw_temp = 20 + random.uniform(-2, 2)
|
||||
comp_temp = raw_temp - 2 # Mock compensation
|
||||
return {
|
||||
'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||
'temperature_raw': round(raw_temp, 2),
|
||||
'temperature': round(comp_temp, 2),
|
||||
'pressure': round(1013 + random.uniform(-10, 10), 2),
|
||||
'humidity': round(50 + random.uniform(-10, 10), 2),
|
||||
'light': round(300 + random.uniform(-50, 50), 2),
|
||||
'proximity': round(50 + random.uniform(-20, 20), 2)
|
||||
}
|
||||
|
||||
def get_csv_files():
|
||||
"""Get list of CSV log files, most recent first"""
|
||||
if not os.path.exists(DATA_DIR):
|
||||
return []
|
||||
|
||||
files = [f for f in os.listdir(DATA_DIR) if f.startswith('weather_log_') and f.endswith('.csv')]
|
||||
files.sort(reverse=True)
|
||||
return files
|
||||
|
||||
def read_historical_data(days=1):
|
||||
"""Read historical data from CSV files"""
|
||||
data = []
|
||||
files = get_csv_files()[:days] # Get most recent day(s)
|
||||
|
||||
for filename in reversed(files): # Oldest first
|
||||
filepath = os.path.join(DATA_DIR, filename)
|
||||
try:
|
||||
with open(filepath, 'r') as csvfile:
|
||||
reader = csv.DictReader(csvfile)
|
||||
for row in reader:
|
||||
data.append({
|
||||
'timestamp': row['timestamp'],
|
||||
'temperature': float(row['temperature_c']),
|
||||
'pressure': float(row['pressure_hpa']),
|
||||
'light': float(row['light_lux'])
|
||||
})
|
||||
except Exception as e:
|
||||
print(f"Error reading {filename}: {e}")
|
||||
|
||||
# Limit to most recent points
|
||||
if len(data) > MAX_HISTORY_POINTS:
|
||||
data = data[-MAX_HISTORY_POINTS:]
|
||||
|
||||
return data
|
||||
|
||||
@app.route('/')
|
||||
def index():
|
||||
"""Render main dashboard page"""
|
||||
return render_template('dashboard.html')
|
||||
|
||||
@app.route('/api/current')
|
||||
def api_current():
|
||||
"""API endpoint for current sensor readings"""
|
||||
return jsonify(read_current_sensors())
|
||||
|
||||
@app.route('/api/history')
|
||||
def api_history():
|
||||
"""API endpoint for historical data"""
|
||||
days = int(request.args.get('days', 1))
|
||||
return jsonify(read_historical_data(days))
|
||||
|
||||
@app.route('/api/stats')
|
||||
def api_stats():
|
||||
"""API endpoint for statistics"""
|
||||
data = read_historical_data(1)
|
||||
|
||||
if not data:
|
||||
return jsonify({})
|
||||
|
||||
temps = [d['temperature'] for d in data]
|
||||
pressures = [d['pressure'] for d in data]
|
||||
lights = [d['light'] for d in data]
|
||||
|
||||
return jsonify({
|
||||
'temperature': {
|
||||
'min': round(min(temps), 2),
|
||||
'max': round(max(temps), 2),
|
||||
'avg': round(sum(temps) / len(temps), 2)
|
||||
},
|
||||
'pressure': {
|
||||
'min': round(min(pressures), 2),
|
||||
'max': round(max(pressures), 2),
|
||||
'avg': round(sum(pressures) / len(pressures), 2)
|
||||
},
|
||||
'light': {
|
||||
'min': round(min(lights), 2),
|
||||
'max': round(max(lights), 2),
|
||||
'avg': round(sum(lights) / len(lights), 2)
|
||||
}
|
||||
})
|
||||
|
||||
if __name__ == '__main__':
|
||||
# Create data directory if it doesn't exist
|
||||
if not os.path.exists(DATA_DIR):
|
||||
os.makedirs(DATA_DIR)
|
||||
|
||||
print("Starting Lab Weather Dashboard...")
|
||||
print("Access the dashboard at: http://localhost:5000")
|
||||
print("Or from another device: http://<raspberry-pi-ip>:5000")
|
||||
|
||||
# Run on all interfaces so it's accessible from other devices
|
||||
# use_reloader=False to prevent input() errors in non-interactive environments
|
||||
app.run(host='0.0.0.0', port=5000, debug=False, use_reloader=False)
|
||||
Reference in New Issue
Block a user