The perception of AI in agriculture has changed dramatically. What was once a focus on machine learning and deep learning has broadened, ...

Agricultural AI holds immense promise for transforming farming. We envision AI-powered tractors, drones, and robots that can revolutionize..

Remember that time you spent months fine-tuning a machine learning model to predict crop yields? You meticulously collected data, tweaked...

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 ...