Yield Prediction with AIML and Digital Twin Technology

With the increase in population across the globe, demand for food increases with it, putting extreme pressure on the agricultural sector to increase its production despite climate changes and natural disasters. To counter these challenges, we recommend a system that uses artificial intelligence and machine learning, coupled with Digital Twin technology, in making yield predictions. This project presentation discusses Agriculture 5.0 and how cutting-edge technologies can change the way farming is done conventionally. This can show how improvements in technology enhance productivity, sustainability, and efficiency based on yield prediction and digital twins. For example, with yield prediction analytics and IoT help farmers predict crop yields to help guide their decisions; with digital twins, for instance, we can create virtual representations of physical assets to monitor and analyze the operation enhancements that result in real time, close to it. We demonstrate, through case studies, the power of these innovations to potentially make a difference in significantly increasing output and efficiency of use in addressing global demand and sustainability challenges for food. This project underlines a high transforming potential in technology for modern agriculture.