Since its origination from P&G and MIT Auto-ID Center in 1999, the term “Internet of Things” (IoT) has been elevated from a specific application concept, based on RFID, to a vastly prominent phrase that represents the general direction to the future of many important aspects of human life. From the application perspective, all the major industries and sectors are now experiencing a certain level of paradigm shift thanks to IoT.
The healthcare system is moving from hospital-centered care to distributed omnipresent care; the transportation is gradually replacing human involvement with driver less technologies and vehicle-to-vehicle (V2V) communications; in manufacture, Industry 4.0, which is empowered by IoT, is taking the leading role in changing the face of factories everywhere in the world. From technology perspective, trending research/development fields in electrical and computer engineering, such as Device-to-Device Network, Wireless Sensor Networks, 5G, Lora Wan, Bluetooth LE, MIMO, deep learning, and distributed low power computing, have all been directly or indirectly contributing to the evolution of IoT.
Due to the timeliness and importance of the topics:
We received a large number of submissions. In the review process, each paper was reviewed by multiple experts in relevant fields. After a rigorous two-round review process, we decided to accept 10 excellent articles addressing cutting-edge wireless communications and mobile computing technologies and applications around the latest trend of IoT. Since the topics of articles cover broad technology scopes, we will introduce them below according to the themes of IoT applications.
The paper “Optimized Power Allocation and Relay Location Selection in Cooperative Relay Networks” focused on power allocation optimization in cooperation communication used in MIMO.
Finally, yet importantly, the last theme is cyber physical systems for IoT. Here we have one paper “SIM-Based Dynamic Reconfiguration CPS for Manufacturing System in Industry 4.0,” in which a cyber physical system framework was designed using learning algorithm SVM to support Industry 4.0.