Hello!

This project uses BME280 and BMP280 with ESP32 and ESP8266 to monitor difference between indoor and outdoor air condition.

A complete IoT environmental monitoring solution consisting of ESP32/ESP8266-based sensor nodes and a Python visualization application. This system provides long-term environmental data collection with minimal power consumption and comprehensive data analysis capabilities.

Overview

This project implements a low-power environmental monitoring system that:

• Dual Platform Support: ESP32 with BME280 (temperature, humidity, pressure) and ESP8266 with BMP280 (temperature, pressure)
• Smart Power Management: Deep sleep cycles (5-minute intervals) for weeks/months of battery operation
• Robust Data Upload: FTP-based data storage with retry mechanisms and error handling
• Professional Visualization: PyQt5 desktop application with interactive time-series plotting
• Router-Based Storage: Utilizes router USB ports for cost-effective, always-on data storage

System Architecture

graph TD
    subgraph "Sensor Nodes"
        A[ESP32 + BME280<br/>Indoor Sensor] 
        B[ESP8266 + BMP280<br/>Outdoor Sensor]
    end
    
    subgraph "Data Collection Cycle"
        C[Wake from Deep Sleep] --> D[Collect 5 Sensor Readings]
        D --> E[Calculate Averages]
        E --> F[Connect to WiFi]
        F --> G[Sync NTP Time]
        G --> H[Upload to FTP Server]
        H --> I[Deep Sleep 5min]
        I --> C
    end
    
    subgraph "Data Storage & Analysis"
        J[Router FTP Server<br/>USB Storage] --> K[Daily CSV Files<br/>DD_MM_YYYY.csv]
        K --> L[Python PyQt5 App]
        L --> M[Interactive Plots<br/>Data Export]
    end
    
    A -.->|WiFi Upload| J
    B -.->|WiFi Upload| J
    H -.->|CSV Upload| J

Loading

Multi-Platform Support

See Hardware Requirements below for board, sensor, and wiring details for ESP32 (indoor) and ESP8266 (outdoor) configurations. File naming conventions and power notes are also summarized there.

Hardware Requirements

• ESP32 (Denky32/WROOM-32) + BME280 (SDA=21, SCL=22, 3.3V)
• ESP8266 (NodeMCU v2) + BMP280 (SDA=D1/GPIO5, SCL=D2/GPIO4, 3.3V)
• Battery or USB power (see Power Consumption section)
• WiFi network, router with USB/FTP, USB storage device

Software Requirements

• PlatformIO IDE (or Arduino IDE) for firmware
• ESP32/ESP8266 Arduino framework, Adafruit BME280/BMP280 libraries
• Python 3.7+ with pip, see graph/requirements.txt for dependencies
• Router with FTP server and USB storage

Quick Start

1. Hardware Setup

# ESP32 (Indoor) - BME280 Connections
VCC  → 3.3V
GND  → GND  
SDA  → GPIO21
SCL  → GPIO22

# ESP8266 (Outdoor) - BMP280 Connections  
VCC  → 3.3V
GND  → GND
SDA  → D1 (GPIO5)
SCL  → D2 (GPIO4)

2. Configure and Flash Firmware

# Open project in PlatformIO IDE
# Select target environment:
#   - "wroom32" for ESP32 + BME280
#   - "nodemcuv2" for ESP8266 + BMP280

# Edit WiFi and FTP credentials in src/main.cpp as shown in the Configuration section below.
# Build and upload firmware
pio run --target upload

3. Setup Router FTP Server

1. Connect USB storage device to router
2. Enable FTP server in router admin panel
3. Configure FTP user credentials
4. Test FTP access from computer

4. Launch Data Visualization

# Windows - Double-click batch file
run_plotter.bat

# Manual setup (any OS)
cd graph
python -m venv .venv
.venv\Scripts\activate          # Windows
source .venv/bin/activate       # Linux/Mac
pip install -r requirements.txt
python environmental_plotter.py

Configuration

Configuration Reference (src/main.cpp)

All key configuration parameters (WiFi, FTP, sensor timing, NTP) are defined at the top of src/main.cpp. Please refer to that file for the latest settings and update as needed. Example parameters include:

• WiFi credentials: WIFI_SSID, WIFI_PASSWORD, WIFI_TIMEOUT
• FTP server: FTP_SERVER, FTP_PORT, FTP_USER, FTP_PASSWORD, FTP_BASE_PATH
• Sensor timing: SLEEP_TIME_US, READINGS_PER_CYCLE, READING_INTERVAL
• NTP: NTP_SERVER, GMT_OFFSET_SEC

See comments in src/main.cpp for details and adjust values for your deployment.

PlatformIO Build Targets

# ESP32 Indoor Sensor (BME280)
[env:wroom32]
build_flags = 
    -DUSE_BME280=1
    -DFILENAME_SUFFIX=\"\"

# ESP8266 Outdoor Sensor (BMP280)  
[env:nodemcuv2]
build_flags = 
    -DUSE_BMP280=1
    -DFILENAME_SUFFIX=\"_outside\"

Design Choice: FTP vs Dedicated Server

This project uses FTP for data storage instead of a dedicated server setup. The reason is simple and practical: many modern routers support USB storage, allowing you to plug in a USB stick and instantly have FTP server functionality. This approach offers several advantages:

• Cost-effective: No need for a separate server or cloud service
• Always available: Router-based storage is always on with your network
• Simple setup: Most routers have built-in FTP server functionality
• Local control: All data stays within your local network
• Minimal power consumption: USB stick consumes negligible power

In this implementation, a leftover USB stick plugged into the router provides reliable, 24/7 data storage without additional hardware costs or complexity.

Data Format & Storage

CSV File Structure

Daily CSV files are automatically created with platform-specific naming:

• ESP32 Indoor: DD_MM_YYYY.csv
• ESP8266 Outdoor: DD_MM_YYYY_outside.csv

CSV Format

Date,Sample Size,Temp (°C),Pressure (hPa),Humidity (RH%)
29/07/2025 14:30,5,25.2,1013.2,65.50
29/07/2025 14:35,5,25.1,1013.1,65.30

Data Collection Process

1. Wake Cycle: Device wakes every 5 minutes from deep sleep
2. Sensor Sampling: Collects 5 readings over 15 seconds (3-second intervals)
3. Averaging: Calculates mean values from valid readings
4. Upload: Appends averaged data to daily CSV file via FTP
5. Sleep: Returns to deep sleep for power conservation

Storage Organization

USB_Storage/
├── 31_07_2025.csv          # ESP32 indoor data
├── 31_07_2025_outside.csv  # ESP8266 outdoor data  
├── 01_08_2025.csv          # Next day indoor
└── 01_08_2025_outside.csv  # Next day outdoor

Power Consumption & Battery Life

ESP32 Power Profile

• Active Operation: ~150-250mA for 30-40 seconds per cycle
• Deep Sleep: <10μA between cycles (WiFi/Bluetooth disabled)
• Daily Data Points: 288 uploads (every 5 minutes)
• Estimated Battery Life:
  • 18650 Li-ion (3000mAh): 3-6 months
  • 6xAA NiMH (2500mAh): 2-4 months

ESP8266 Power Profile

• Active Operation: ~120-200mA for 25-35 seconds per cycle
• Deep Sleep: <20μA between cycles
• Daily Data Points: 288 uploads (every 5 minutes)
• Estimated Battery Life:
  • 18650 Li-ion (3000mAh): 4-8 months
  • 4xAA NiMH (2500mAh): 2-5 months

Power Optimization Features

• Bluetooth completely disabled on ESP32
• WiFi module powered down during sleep
• Efficient sensor sampling with minimal warm-up time
• Optimized FTP upload with connection reuse
• Hardware-level deep sleep implementation

Project Structure

See the repository tree for a full breakdown. Main components:

• src/ (firmware), graph/ (visualization app), platformio.ini (build config), documentation, and test/lib/include folders.

Key Features

• Dual platform firmware (ESP32/ESP8266) with robust sensor, WiFi, and FTP handling
• Power-optimized, reliable data collection and upload
• PyQt5 visualization app: interactive plots, export, multi-threaded FTP, and error handling

Troubleshooting

See comments in src/main.cpp and serial/console output for detailed troubleshooting. Common issues:

• Sensor not detected: check I2C wiring, addresses, and power (3.3V only)
• WiFi/FTP: verify credentials, router/server status, and network connectivity
• Python/visualization: ensure Python 3.7+, install dependencies, check CSV format

Development & Customization

See code comments and examples in src/main.cpp, platformio.ini, and graph/environmental_plotter.py for how to:

• Add new sensor types (update libraries, initialization, CSV format)
• Extend visualization (add columns/plots, update requirements)
• Customize build targets and advanced features

License & Contributing

This project is open source under the Apache License 2.0. You are free to use, modify, and distribute it (see LICENSE for details).