Special Issue "Recent Machine Learning Applications to Internet of Things (IoT)"
Deadline for manuscript submissions: closed (30 June 2020).
Interests: computational intelligence; machine learning; neural networks; clustering; data mining in bioinformatics and ecological informatics; wireless sensor networks; IoT; soft computing
Special Issues and Collections in MDPI journals
Interests: soft computing; machine learning; computational intelligence; data mining; data mining for astrophysics; geology and biology data; signal processing; audio streaming; brain–computer interface
Special Issues and Collections in MDPI journals
It was a long time ago that Mark Weiser envisioned a world of small, cheap, and robust networked processing devices, distributed across human and natural environments at all scales, to aid our everyday life. Since then, the technological developments, from nanotechnologies to computation and communication systems, have converged into what is nowadays known as Internet of Things (IoT), and made what Weiser envisioned a reality. IoT has paved the way to a plethora of new application domains, at the same time posing, however, several challenges as a multitude of devices, protocols, communication channels, architectures. and middleware exist. Nevertheless, IoT is growing exponentially in the number and heterogeneity of actors; indeed, a number between 50 and 100 billion objects are expected by 2020, and this growth makes “intelligence” a critical turning point for the success of IoT.
In particular, we are witnessing an incremental development of interconnections between devices (smartphones, tablets, smartwatches, fitness trackers and wearable devices in general, smart TVs, home appliances, and more), people, processes, and data.
Data generated by the devices are becoming big data and call for advanced learning and data mining techniques to efficiently and effectively understand, learn, and reason with this amazing volume of information.
Moreover, thanks to the latest results of research on Artificial Intelligence, applications can count on an “intelligent” network of billions of sensors “aware” of their operating environment, able to listen, learn, and respond to offer new services and functionalities in the most disparate application domains, which guarantee greater security, simplicity, and reliability.
This Special Issue aims at collecting contributions concerning any use of intelligent techniques to any IoT aspects related to the IoT domain, from protocols to applications, to give the reader an up-to-date picture of the state-of-the-art on the connection between machine learning, computational intelligence, and IoT.
General topics covered in this Special Issue include but are not limited to the following methodologies and IoT applications:
- Soft computing (e.g., fuzzy logic, rough sets);
- Neural networks;
- Neuro-fuzzy systems;
- Deep learning;
- Evolutionary and bio-inspired algorithms;
- Machine learning and computational intelligence-aided IoT;
- Intelligent middleware solutions IoT;
- Brain–computer interface and IoT;
- IoT and cloud computing;
- Semantic web of things;
- Social network IoT;
- Internet of vehicles;
- Context awareness;
- Security and IoT.
Dr. Antonino Staiano
Dr. Angelo Ciaramella
Manuscript Submission Information
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