Smart Agriculture
Smart agriculture utilizes Internet of Things (IoT) technologies and artificial intelligence (AI) to optimize farming practices and enhance efficiency. Current research heavily focuses on applying machine learning, particularly deep learning models like CNNs and support vector machines, for tasks such as disease detection, yield prediction, and precision resource management. This field is significant for improving crop yields, resource utilization, and sustainability, impacting both scientific understanding of agricultural systems and the practical implementation of data-driven farming techniques.
Papers
IoT-Aerial Base Station Task Offloading with Risk-Sensitive Reinforcement Learning for Smart Agriculture
Turgay Pamuklu, Anne Catherine Nguyen, Aisha Syed, W. Sean Kennedy, Melike Erol-Kantarci
Deep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks
Anne Catherine Nguyen, Turgay Pamuklu, Aisha Syed, W. Sean Kennedy, Melike Erol-Kantarci