This Special Issue aims to promote a deeper understanding of the major conceptual and technical challenges in smart farming, which is the use of artificial intelligence (AI), big data analytics, Internet of Things (IoT), and automation/robotics to improve productivity and quality. Areas of innovation and advancement include multi- and hyper-spectral imaging, thermal imaging, and color and 3D imaging. AIoT-based systems are increasingly used for smart agriculture applications such as crop growth monitoring, pest and disease detection, microclimate monitoring and control, crop yield mapping, targeted spraying, smart irrigation, and nutrient management. Powerful computational infrastructure and associated data analytics techniques, including deep learning, are also playing an instrumental role in improving the robustness and reliability of sensing technologies in production agriculture.
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