The study sheds light on the widespread use of CPS in crop management, smart greenhouses, precision irrigation, livestock ...

In the workflow, a machine learning-driven optimization of the amine synthesis was demonstrated with six continuous variables and 20 solvents, using a semiautomated continuous flow setup.

This study applies machine learning to determine rice crop production using sensor information from temperature, humidity, and water levels. This project looks forward to providing insights to ...

Businesses need better planning to make their supply chains more agile and resilient. After explaining the shortcomings of traditional planning systems, the authors describe their new approach ...

Machine Learning Now Helps Sort Seeds and Predict Crop Needs This new AI revolution uses things such as soil, climate and genetic data to anticipate outcomes and turn that information into ...

A new machine-learning model for predicting crop yield using environmental data and genetic information can be used to develop new, higher-performing crop varieties.

For instance, the IoT-based fertigation control system, shown in Figure 19, can monitor various aspects of a hydroponic production, including flow rate, electrical conductivity (EC), and pH of the ...