Special Issue "Smart Objects in the Internet of Things: From Sensor to Data Processing"
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 34649
Interests: Internet of Things; edge computing; distributed systems; digital twins; mobile computing; pervasive computing
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The information technology ecosystem has been recently and significantly revolutionized by the advent of the Internet of things (IoT), and its quick and pervasive evolution. The IoT will consist of billions of interconnected devices denoted as “smart objects”, able to generate and consume a massive amount of heterogenous data. The massive amount of information being created by the IoT has the power to revolutionize everything from industry to healthcare, allowing them to work more efficiently and profitably. In this challenging context, data collection and data processing are two of the crucial pillars that will allow for extracting technological and business values from IoT applications and real deployments.
Furthermore, the mission of critical application will need real-time actionable intelligence and powerful user interfaces in order to make decisions and/or support decision makers in complex tasks. The seamless and efficient cooperation between data collection and processing, analytics, edge computing, and networking will be a fundamental enabler for the next generation of applications.
This Special Issue focuses on the innovative developments, technologies, and challenges related to Internet of things data generation, collection, modeling, and processing. The Special Issue is seeking the latest findings from research and ongoing projects. Additionally, review articles that provide readers with current research trends and solutions are also welcome. The potential topics include, but are not limited to, the following:
- Data discovery in IoT applications
- IoT data analytics
- Machine learning for IoT
- Integrating IoT data with external data sources
- Data generation, collection, and synchronization technologies
- Data processing for IoT
- Data science applications and services
- Data presentation and user interfaces (conversational interfaces, VR/AR)
- IoT application orchestration and coordination
- Distributed data management
- IoT Real-time application
- Real-time data processing for IoT
- Edge computing and efficient data processing
- Heterogeneity management
- Data modeling and seamless interoperability
- Application and data integration for IoT applications
Dr. Marco Picone
Dr. Marco Mamei
Dr. Màrius Montón
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. Journal of Sensor and Actuator Networks 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 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
- edge computing
- fog computing
- data processing
- big data
- machine learning