Paper Contents
Abstract
The presented project is an IoT-based Weather and Air Quality Monitoring System developed using an ESP32 microcontroller, integrated with a DHT22 sensor for temperature and humidity readings, and an MQ-135 gas sensor to assess air quality. The system also features a 16x2 I2C LCD for real-time local data display and supports Wi-Fi connectivity to periodically upload sensor readings to ThingSpeak, a cloud-based IoT analytics platform. At the heart of the system, the ESP32 microcontroller collects environmental data through its connected sensors. The DHT22 sensor measures temperature and humidity with high accuracy, while the MQ-135 analog sensor provides air quality values, which are mapped to a 0100 scale representing pollution levels. To provide user-friendly feedback, the LCD displays temperature (with a custom degree symbol), humidity, air quality percentage, and Wi-Fi connection status including signal strength (RSSI). This two-screen cycle ensures continuous feedback to users about both environmental conditions and system connectivity. The code is designed to transmit data every 30 seconds to the ThingSpeak server using the builtin Wi-Fi capability of the ESP32. The transmission includes four fields: temperature, humidity, air quality index, and Wi-Fi RSSI value. If the device loses internet connectivity, it automatically attempts to reconnect while updating the user on the LCD screen. All sensor readings and system activities are also logged to the Serial Monitor for debugging and real-time observation. The program enhances the user experience by introducing a custom character for the degree symbol on the LCD, and by providing intuitive messages for successful data transmission, error reporting, and initialization steps. Furthermore, the system includes a utility function to describe air quality levels based on numerical value rangesclassifying them as Excellent, Good, Moderate, Poor, or Hazardous. This project demonstrates a compact, yet comprehensive solution for remote weather and air quality monitoring, combining embedded systems, wireless networking, and cloud computing. It vi is highly suitable for educational, environmental, or smart home applications where real-time monitoring and cloud integration are essential.
Copyright
Copyright © 2025 More Dinesh. This is an open access article distributed under the Creative Commons Attribution License.
