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Internet of Things (IoT) and Machine Learning (ML) have been two among the most popular research topics for the last two decades. The benefits that these two technologies offer are indeed prominent. Nevertheless, the combination of these two breakthrough technologies can even bring more groundbreaking advantages to society, also transforming the classic IoT to an enhanced version called Internet of Intelligent Things (IoIT). In this paper, a large-scale evaluation of this enhanced concept is conducted, analyzing all of its core aspects, as well as explaining the advantages and potentials of…mehr

Produktbeschreibung
Internet of Things (IoT) and Machine Learning (ML) have been two among the most popular research topics for the last two decades. The benefits that these two technologies offer are indeed prominent. Nevertheless, the combination of these two breakthrough technologies can even bring more groundbreaking advantages to society, also transforming the classic IoT to an enhanced version called Internet of Intelligent Things (IoIT). In this paper, a large-scale evaluation of this enhanced concept is conducted, analyzing all of its core aspects, as well as explaining the advantages and potentials of this groundbreaking concept. Nonetheless, many challenges, that may act as an impediment on the benefits received through the IoIT, exist. In our large-scale evaluation, these challenges are detected and carefully examined, also suggesting ways to effectively overcome them. Data Mining (DM) is the process of extracting useful insights from large volumes of data. In this paper, we explain how ML- based DM techniques and methodologies could be utilized for the effective and efficient extraction of insights and valuable information from complex sequential data volumes.
Autorenporträt
Antreas Dionysiou, Deep Learning - Security - Wireless Networks Special Scientist; Università di Cyprurs - Cipro.