The Aerial Climate Monitor is a custom-built environmental monitoring system designed by integrating a DJI Tello drone with an Arduino Uno, Wi-Fi shield, and DHT22 temperature-humidity sensor. The system was developed to collect and store climate data such as temperature and humidity in real time while maintaining the drone’s ability to perform stable aerial flights. A custom 3D-printed mounting bracket was designed to securely attach the electronic components to the drone without significantly affecting its balance or performance. The project successfully demonstrated data collection, wireless transmission, and onboard storage during aerial tests.
Introduction
Indoor environments such as offices, laboratories, and industrial spaces rely heavily on HVAC (Heating, Ventilation, and Air Conditioning) systems to maintain comfortable and safe conditions. However, temperature and humidity levels can vary significantly across different zones in the same building due to airflow patterns, obstructions, or equipment placement. Traditional fixed sensors provide only localized data, often failing to capture these variations accurately. The Aerial Climate Monitor addresses this challenge by using a lightweight drone-mounted sensor system to measure indoor climate conditions dynamically and across multiple locations. By enabling mobility, the system enhances HVAC performance analysis and provides more comprehensive data for energy optimization, occupant comfort, and indoor air quality studies.
System Design and Components
The hardware configuration of the system includes an Arduino Uno microcontroller, a Wi-Fi shield, a DHT22 sensor, and an SD card module. The DHT22 sensor provides accurate temperature and humidity measurements, which are then processed by the Arduino. Data is transmitted wirelessly over Wi-Fi for real-time monitoring and simultaneously logged to an SD card for backup and offline analysis. To accommodate these components, a lightweight and durable mounting bracket was modeled and fabricated using 3D printing techniques. Careful consideration was given to the bracket’s design to minimize weight and aerodynamic drag, ensuring that the drone’s stability and flight efficiency were not compromised.
Testing and Performance Evaluation
Testing was conducted to evaluate the drone’s flight time, stability, and data acquisition accuracy with the mounted payload. Baseline flight tests without the additional hardware were compared against flights with the bracket and electronics installed. Results indicated a slight reduction in flight time due to the added weight but no significant issues in stability or maneuverability. The sensor consistently transmitted and logged accurate data during both static and in-flight conditions. For HVAC-focused testing, the drone was flown in a controlled indoor environment to map variations in temperature and humidity across different zones of the space, demonstrating its value for diagnosing airflow imbalances and identifying areas of poor climate control.
Results and Discussion
The Aerial Climate Monitor successfully achieved its design goals, demonstrating that low-cost sensors and microcontrollers can be effectively integrated with small drones for indoor climate monitoring. The combination of real-time Wi-Fi transmission and SD card logging ensures data redundancy and flexibility for further analysis. While the payload introduced minor reductions in battery life, the drone remained operationally efficient for short indoor flights. Future improvements could include the use of lighter hardware or more advanced drones to extend flight duration, as well as incorporating additional sensors (such as CO₂ or air quality sensors) for broader HVAC diagnostics.
Conclusion
This project illustrates the potential of combining compact drones with low-power sensing systems to create mobile indoor climate monitoring platforms. The Aerial Climate Monitor can serve as a tool for HVAC engineers, facility managers, and researchers to gain detailed insights into temperature and humidity distributions within buildings. With continued refinement, such systems could play a significant role in energy efficiency optimization, indoor air quality management, and occupant comfort analysis in modern smart building applications.