I’m upgrading an existing research-grade air-monitoring prototype and need fresh expertise on both its brains and its senses. Right now the unit records basic gas, temperature and humidity data, but sensor accuracy drifts and the firmware is held together by quick fixes. Hardware goals My first priority is the sensor chain. I need informed recommendations on higher-precision sensors and transducers, signal-conditioning circuitry, and a calibration strategy that produces traceable, publication-ready data. If swapping microcontrollers or revising the PCB layout will improve stability, please outline the change. Software goals The current code captures data but offers little filtering, self-diagnostics or scalability. I want clean, well-documented firmware (or a lightweight desktop script, if you prefer) that automatically corrects offsets, logs reliably, and leaves room for later analytics. Language choice is open—you can decide whether Python, C++ or another option best suits the hardware stack. Deliverables • Updated schematic and BOM for the sensor section • Compiled firmware or script with commented source and build instructions • Validation report comparing new versus old performance (accuracy, repeatability, noise levels) The work feeds directly into an academic paper, so precision and clear documentation are essential. If you’ve improved similar biomedical or environmental instruments before, I’d like to hear how you tackled accuracy, calibration and data integrity.