Dear Colleagues,

The availability of pervasive sensing and actuating devices, as well as of new wireless standards, at lower and lower prices is fueling the rise of the Internet of Things (IoT) paradigm, with a huge impact on several aspects of everyday life. Indeed, IoT has the potential to revolutionize the behaviors of both private and business users, dramatically impacting several application scenarios in both domestic and working fields, such as domotics, enhanced learning, e-health, and smart cities, as well as automation, industrial manufacturing, agriculture, logistics, and intelligent transportation systems.

Due to the increasing set of application scenarios leading to the pervasive deployment of sensing devices, IoT is among the most important sources of big data, as they generate unprecedented issues related to the acquisition, aggregation, storage, transmission, integration, and analyses needed for understanding and extracting value from such data.

Therefore, IoT data management and analysis is providing novel research challenges—either dictated by the specific application domains or crossing several of them—at sensing, network, and application layers, for both industry and academia. Often, novel architectural solutions involving advanced cloud- or fog-based architectures are imperative to cope with both the limited IoT processing capabilities and the huge data volumes.

To address the aforementioned challenges, this Special Issue is dedicated to the wide field of data science for IoT. We encourage original and high-quality contributions, addressing both theoretical and systems research.

Topics of interest include, but are not limited to:

• IoT data mining and analytics
• Heterogeneous IoT data integration
• IoT data and platforms Interoperability
• IoT scalability of storage and analysis based on AI
• edge/fog/cloud-based architectures for data science
• IoT communication platforms' bottlenecks
• IoT data privacy and security issues
• IoT-based e-health/mobile-health
• IoT for Smart home and smart cities
• Data management solutions for manufacturing, logistics, and Industry 4.0
• Mobile Applications for Crowd-sensing
• Semantic technologies for IoT
• Web platforms for IoT
• Machine learning techniques for big data
• Interfaces to exploit big data
• IoT services built on big data

Prof. Dr. Antonio Pescapé
Dr. Valerio Persico
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Internet of Things (IoT)
• Data science
• Big Data
• Data management and analysis
• Data Integration
• Cloud Computing
• E-health
• Industry 4.0