Cloud Computing, Big Data, and Internet of Things Technologies in Healthcare and Industry (Industry 4.0)

Dear Colleagues,

It is my pleasure to announce the opening of a new Special Issue in the Applied Science journal.

Internet of Things (IoT) is one of the new technologies that changed the image of the current world, yielding new possibilities, but also proliferating data. IoT devices may constantly produce enormous amounts of data as data streams that can be analyzed in real-time and also collected for further exploration in huge data centers. Due to their scaling capabilities, these data centers are frequently located in the cloud. Cloud computing has revolutionized many fields that require ample computational power. Today, cloud platforms provide huge support for data analyses performed in healthcare and industry, mainly through disclosing scalable resources of different types. In clouds, these resources are available as services, which simplifies their allocation and releasing. This feature is especially useful during the analysis of large volumes of data, like the one produced by medical equipment in various types of laboratory experiments or by IoT devices. The rapid growth of data in healthcare and industry offers new opportunities, but also raises many challenges. This Special Issue intends to encompass the latest advancements concerning scalable cloud computing, Big Data, and Internet of Things solutions in processing and analyzing biomedical and industrial data. The aim of this Special Issue is to reflect the most recent developments in scalable data analysis used for solving problems in a variety of areas related to Healthcare and Industry 4.0.

The scope of the Special Issue covers the use of scalable cloud computing architectures, Big Data, and Internet of Things technologies in various problems related to those areas, including (but not limited to):

• Cloud-based architectures or Big Data-based algorithms for data analysis and interpretation (e.g., Next Generation Sequencing data or sensor data)
• IoT-driven monitoring health of people and production systems
• Integration and exploration of biomedical and industrial data
• Large-scale AI-driven analytics of data at rest and data streams
• Scalable solutions for industrial and health informatics

Prof. Dariusz Mrozek
Prof. Dr. Vaidy Sunderam
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.