Add your Insight
20 March 2021
Special Issue Editor(s)
Dr. Alireza Souri,
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Iran
Dr. Eyhab Al-Masri,
School of Engineering and Technology, University of Washington, Tacoma, USA
Prof. Giovanna Castellano,
Department of Computer Science, University of Bari, Italy
Prof. Mu-Yen Chen,
Department of Engineering Science, National Cheng Kung University, Taiwan
Nature Inspired Computing for Internet of Things: Methods and Aspects of Intelligent systems
The Internet of Things (IoT) has provided the emerging infrastructure to establish protocols, architectures, standards and integration of sensors and smart devices in high-performance computing. The IoT keeps on enriching and providing interaction between the cyber and the physical world using development of innovative hardware, software and communication technologies fostered the emergence of Internet connected sensor devices which observe the physical world and provide data measurements. On the other hand, Artificial Intelligence (AI) is an emerging technology that has proven to have great potential in IoT ecosystems, cloud-edge computing, big data, and performance optimization. Also, nature inspired computing as one of the powerful branches in AI includes data mining, machine learning, optimization, robotics, control systems, human–computer interaction, IoT, and many others.
Despite the importance of security, privacy, energy efficiency, reliability, and accuracy issues in IoT, this special issue focus on emerging methods and aspects of nature-inspired computing solutions for IoT systems. This special issue invites researchers to publish selected original papers in IoT perspectives. We also are interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research, and new future issues.
Methodologies, and Techniques
- Genetic algorithm and extended new generation techniques
- Deep learning models
- Fuzzy logic and methods
- Nature-Inspired algorithms (PSO, ACO, ABC, GWO, …)
- Hybrid learning schemes (deterministic with heuristics-based, mimetic)
- Incremental learning methods for self-adaptive models
- Supervised and semi-supervised algorithms
- Clustering algorithms
- Security and privacy in autonomous IoT environments
- Energy consumption on data Storage in IoT systems
- Medical and healthcare technologies for cyber physical systems in IoT
- New energy harvesting approaches on IoT systems
- Could-edge resource management for service robotics in IoT
- Industrial equipment and smart manufacturing in IoT
- Reliability and availability issues for IoT ecosystems
- Smart cities and home-care problems in IoT
- Smart agriculture and farming in IoT environments
- smart grid in IoT communications
- Robotics, bio-robotics, and control systems in IoT
- Blockchain technology for IoT communications
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All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least three independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process. Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper). Please Select "NIC-IoT” when submitting your paper to ScholarOne.
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