This project addresses the challenge of continuous environmental monitoring for vehicles, particularly in off-road or long-distance travel where real-time data on internal and external conditions is critical for safety and performance. Utilizing an Arduino microcontroller, multiple sensors, and an intuitive OLED display, the system provides comprehensive monitoring by measuring and displaying real-time data for interior and exterior temperature, humidity, and pressure, tank pressure for onboard air systems, vehicle pitch and roll, and altitude. Additionally, the system visualizes trends over time, offering users valuable insights into environmental and system conditions.
This project was chosen to support off-road enthusiasts, frequent travelers, and field operators who require reliable and accurate data to ensure safety and operational efficiency. Automated monitoring enhances real-time decision-making, improves accuracy, and provides convenient data visualization, minimizing manual checks and reducing the risk of human error. Simplifying assumptions include pre-calibrated sensors, stable environmental conditions, fixed sensor configurations, and a reliable power supply, ensuring seamless system operation. By integrating all necessary data into a single display, this project delivers a practical, efficient, and reliable solution for monitoring vehicle and environmental parameters in demanding conditions.
The system follows a structured process:
The system underwent extensive testing to validate its performance and functionality. Initial tests focused on system initialization and sensor verification, ensuring that the BME280 sensors provided consistent environmental data and that the IMU accurately reported pitch and roll values in response to orientation changes. Tank pressure calibration was conducted by comparing readings from the system to a calibrated analog gauge, with discrepancies corrected using an altitude-based correction factor. Data logging and plotting functionality were verified by monitoring and recording temperature, pressure, and humidity data over a 30-minute period, demonstrating smooth updates and transitions between screens without disruptions. Altitude calculations were assessed by comparing sensor readings to the known elevation of the test location (3250 ft), with adjustments yielding an accuracy of ±3 ft. Real-time performance tests validated the responsiveness of live data displays and pitch/roll measurements, with data updating with minimal latency (~0.2 seconds). Measurement errors and uncertainties, such as altitude variations due to atmospheric pressure changes, minor nonlinearities in pressure transducer readings, and potential sensor drift, were identified but deemed minimal for the system's intended application. Overall, the system delivered accurate and efficient monitoring of environmental and system parameters, meeting the project’s objectives effectively.