The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

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

In this study, the effects of dynamic climate and biophysical parameters and static soil parameters obtained from earth observation satellites on cotton yield estimation were examined with four ...

DFKI has developed a system that makes agriculture more predictable, reduces risks and optimises the use of resources. With the help of satellite data and machine learning, the platform analyses ...

Global solar radiation (Hg) is a foundational input for calculating evapotranspiration, crop growth, irrigation needs, and ...

But amid all the hype, the real story that has emerged doesn’t focus on the technology itself but on the people using it ... logic to it through machine learning, and ultimately helping the farmer to ...

Machine learning techniques such as Random Forests and Support Vector Regression are used, which provide more robust models than traditional linear regression models. An analysis has been undertaken ...