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 ...

The increase in precision agriculture has promoted the development of picking robot technology, and the visual recognition ...

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 ...

This study explores the development of two predictive models for the yield sooting index (YSI) of various fuels using the advanced capabilities of machine learning (ML), particularly multilayer ...

Data Preprocessing: Cleaning, normalizing, and integrating data for effective analysis. Model Development: Employing machine learning models (e.g., LSTM, ARIMA, SVM) for weather prediction, crop ...