Theme and Scope With the increasing demand for high-speed and low-latency connections, the development of 6G networks that surpass the performance of existing 5G networks is accelerating. 6G networks, which will enable enhanced mobile broadband, a wide range of mechanical communications, highly reliable low latency, sensing capabilities, and application services covering artificial intelligence (AI), will integrate edge and core computing as components of a unified communication and computational infrastructure. As high communication speed and efficient data processing become possible, the utilization of IoT and edge computing technologies based on 6G networks will be applied in various fields such as human-centered real-life technology, safety, convenience technology, autonomous vehicles, smart cities, and telemedicine. Various business models and strategies applying this technology will also emerge. For edge computing platforms, instead of transferring all the collected data directly to the centralized cloud, they can preprocess the data at edge nodes, reducing service latency and energy consumption compared to centralized cloud platforms. In particular, intelligent edge computing provides an opportunity to improve the energy efficiency of IoT and meet the requirements of remote IoT services. Due to these advantages, intelligent edge computing based on 6G is being studied in various fields and methods such as human-centered convenience, efficiency, and service support in smart homes, offices, transportation, healthcare and medical, smart cities, intelligent communication, and smart agriculture. Additionally, in recent years, various IoT devices such as home appliances, sensors, actuators, and drones are being connected to an integrated IoT network where each component can interact. Research on device-edge-cloud continuum platforms that utilize the rich functions and resources provided by edge nodes and the cloud is also underway. This special issue collects the latest technologies and research papers on 6G enabled intelligent edge computing technology and human-centric IoT application, system and platform development, and empirical service implementation and utilization. It also includes application technologies in various fields such as machine learning for IoT, intelligent edge computing management using deep learning, business models and verification, human-centeric IoT utilization and services, and intelligent smart agriculture based on edge computing. Submitted papers are processed by peer review and must adhere to journal regulations. The topics of the special issue are as follows: Keywords:
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