This Collection explores the integration of Internet of Things (IoT) technologies with Artificial Intelligence (AI) and Machine Learning (ML) methods for advancing healthcare, remote monitoring, rehabilitation, and assistive systems. With the rapid expansion of wearable devices, sensing platforms, and connected infrastructures, IoT-driven healthcare provides unique opportunities for early diagnosis, personalized therapy, and improved quality of life. The Collection aims to bring together research on novel algorithms, sensing technologies, system architectures, and clinical applications that leverage IoT and AI to address challenges in scalability, data security, usability, and clinical validation. It seeks to highlight both theoretical advances and practical implementations across diverse medical and health-related domains.

This Collection supports and amplifies research related to SDG 9, SDG 11 and SDG 13.

Keywords: Rehabilitation technology; Wearable Sensors; Assistive devices; Machine Learning; Rehabilitation; Data Security; Artificial Intelligence (AI); Internet of Things (IoT)

This Topical Collection is dedicated to highlighting the application of Machine Learning (ML), Artificial Intelligence (AI) and Deep Learning (DL) in the field of Microwave Engineering: Devices and Communication. It will concentrate on AI/ML/DL approaches in Microwave Engineering, which includes new breakthroughs, design and performance techniques of various Microwave Devices like Antennas, Filters, Couplers etc. Starting with single/multiband antennas, this topical collection will showcase the application of AI/ML/DL in the design and/or performance features of wideband to super wideband antennas including Multiple-Input-Multiple-Output (MIMO) antenna structures suited for wireless communication.

It will also focus on the use of AI/ML/DL in various aspects of Terrestrial and/or Satellite-based Microwave Communication: Processes, Algorithms and Protocols.