Machine Learning Techniques For Wireless Time Series In The Context Of Wireless Sensor Networks And Iot

This Special Issue aims to highlight the latest machine learning advancements in the field of wireless sensors networks. Topics include supervised and unsupervised ML, embedded TinyML, reinforcement learning, distributed ML, autoencoders, transformers, zero- and few-shot learning, meta-learning, and more. These techniques are suitable for various sensor applications, such as wireless network management and optimization, connected healthcare, wearable sensors, indoor localization systems, and industrial sensor networks. Submissions are invited to be submitted online until the deadline.