Sensing and Actuating Tasks in IoT Environments
A special issue of Actuators (ISSN 2076-0825).
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 12757
Special Issue Editors
Interests: Internet of Things; edge computing; artificial intelligence; deep learning; optimization; task scheduling; complex problem solving
2. Computer Engineering Department, Jeju National University, Jeju 63243, Republic of Korea
Interests: internet of things; edge computing; digital twin; blockchain; artificial intelligence; on-device AI; federated learning; swarm learning; swarm intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear colleagues,
The Internet of Things (IoT) is an emerging paradigm that inspires industries to develop intelligent and autonomous systems based on Internet-connected devices. The IoT comprises heterogeneous devices, applications, and platforms using multiple communication technologies to connect the Internet to ubiquitously provide seamless services. Leveraging cloud computing, the IoT can be supported to apply not only large-scale and personalized data, but also artificial-intelligence (AI) algorithms based on offloading AI approaches to high-performance servers to work with huge volumes of data in the cloud. Through the task scheduling of IoT services, various continuous scenarios can be deployed for controlling actuators to update the IoT environment.
Contributions from all fields related to Internet of Things are welcome to this Special Issue, and particularly the following:
- theory, applications, case studies, and project reports related with emerging IoT standard protocols, frameworks, and platforms;
- IoT and edge-computing solutions in smart spaces such as homes, buildings, factories, farms, and cities;
- distributed edge computing for compuational offloading;
- real-time inference and prediction approaches in edge computing;
- controlling based on AI approaches;
- energy optimization in smart spaces;
- task scheduling for intelligent IoT services;
- complex problem solving based on IoT and edge computing.
Prof. Dr. Do-Hyeun Kim
Dr. Wenquan Jin
Guest Editors
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Keywords
- Internet of Things
- edge computing
- task scheduling
- control
- optimization
- deep learning
- complex problem solving
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