Forecasts in the Internet of Things

A special issue of Forecasting (ISSN 2571-9394). This special issue belongs to the section "Forecasting in Computer Science".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 579

Special Issue Editors


E-Mail Website
Guest Editor
Department of Informatics, University of Hamburg, Vogt-Kölln-Str. 30, 22527 Hamburg, Germany
Interests: distributed systems; mobile computing; mobile cloud computing; context-aware and -adaptive applications; context-adaptive application architectures

E-Mail Website
Guest Editor
Department of Informatics, University of Hamburg, Vogt-Kölln-Str. 30, 22527 Hamburg, Germany
Interests: distributed systems; middleware; mobile; ubiquitous; and pervasive systems; self-organization; cloud computing

Special Issue Information

Dear Colleagues,

The number of Internet-connected devices, referred to as the Internet of Things (IoT), is constantly growing. The huge amount of data they generate by sensing their environment can be used to develop a multitude of smart IoT applications. Nevertheless, many of these use cases, such as prescriptive analytics or predictive maintenance, benefit from forecasts of these data.

In the past, many different research communities explored forecasting systems, each from their own perspective. Relevant work can be found in different areas, including autonomic computing, self-adaptive and self-organizing software and systems, machine learning, artificial intelligence, multi-agent systems, and context-aware systems.

This Special Issue aims to provide a forum for academic researchers and technical professionals to exchange their recent works on advancements in the field. We invite you to submit high-quality research papers—a non-exhaustive set of topics of interest includes:

  • Evaluation of forecasting methods;
  • Application of forecasting methods;
  • Development support for forecasting systems;
  • Context prediction—models and applications;
  • Contextual computing—models and applications.

Conference papers should be cited and noted on the first page of the paper; authors are asked to disclose that it is a conference paper in their cover letter and include a statement on what has been changed compared to the original conference paper. Please note that the submitted extended paper should contain at least 30% new content (e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases). The introduction and conclusion need to be rewritten.

Dr. Gabriel Orsini
Prof. Dr. Winfried Lamersdorf
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forecasting is an international peer-reviewed open access quarterly 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 1800 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.

Keywords

  • forecasting
  • Internet of Things
  • prediction
  • machine learning
  • context adaptation

Published Papers

There is no accepted submissions to this special issue at this moment.
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