Imagine you've developed a versatile datalogger-controller using an Arduino board to monitor and control environmental conditions. This device can accept signals from a variety of sensors, including soil moisture, electrical conductivity, and pH sensors, and can control solenoid valves using a relay board. To add a layer of precision, the datalogger incorporates a GPS module to geotag sensor data during field installations.

Signal processing includes steps such as baseline calculation, feature extraction, and normalization. These steps consider user settings ...

I trained a machine learning model to accurately classify leaf wetness events into categories such as rainfall, dew, and frost. The model ..

Building upon our previous work in biophysical modeling, we employ advanced machine learning techniques to investigate the impact of ...

I'm excited to announce the availability of a Python version of the CWSI and transpiration module/class originally developed in C++ for...