This workshop aims to bring together practitioners and researchers with a specific focus on the emerging trends and industry needs associated with real-time data processing and applications for IoT. Both theoretical and experimental submissions are encouraged. Papers should elaborate real-time data processing and applications for IoT, issues associated with data preparation, visualization, analytics, privacy issues, and new applications.

Data induction through smart devices is more significant compared to information processing capacity.  Now a day, data becomes humongous even coming from the single source, therefore, when data emanates from all heterogeneous sources distributed over the globe, its magnitude makes it harder to process up-to a needed scale. Big data have become standard in providing well-known solutions built-up using algorithms and techniques in resolving data processing issues.

IoT makes the device capable of emanating data paving the way to many applications even in the classic industrial manufacturing scenario. For instance, a device can benefit from an inline upgrade of specific features or specific environmental settings, increasing its performance and its ability to react to environmental changes. These improvements can derive from an underlying big data processing occurred in real time based on the data collected from the device as well as from other devices of the same type.

The intelligence after an era of distribution in the peripherals is becoming centralized again, and the central entity, the big data engine, is then able to distribute processing and storing needs.

Map reduce feature of big data supports massive data-oriented process execution using distributed processing. Continuous training and deep learning for improvements of distributed IoT device as well as advanced predictions are nowadays enabled by such an architecture making behavioral prediction available for many vertical applications.

This workshop focused but not restricted to in data-related applications in IoT and Industrial scenario that can exploit big data features. It is intended to present the current state-of-the-art in this field as well as future trends.

The topics of interest include, but are not limited to:

• IoT based real-time communication system using image processing techniques.
• Big data storage management for IoT applications.
• Data collection, mining, and prediction methods based on big data.
• Video and image data processing in industrial applications.
• Human behavioral extraction and monitoring in big data and IoT applications.
• Models and parallel algorithms for medical imaging for IoT.
• Real-time human behavioral measurement, modeling, evaluation, reputation. generation, and tools for IoT Big Data.
• Real-time behavior assessment in big data transmission with efficiency for IoT.
• Behavioral feature based learning from big data to facilitate monitoring.
• Scalable and semantics-driven indexing of ever-growing multimedia data.
• Security and privacy management and assurance in IoT

Submission Guideline

Papers must be submitted electronically as PDF files, formatted for 8.5×11-inch paper. The length of the paper must be no more than 6 pages (+2 extra pages with over-length charge of $100/page) in the IEEE double-column format (10-pt font).

Papers should neither have been published elsewhere nor being currently under review by another conference or journal. The reviews will be single blind. At least one of the authors of every accepted paper must register and present the paper at the workshop. Accepted papers will be published in the combined ICNC Workshop proceedings and will be submitted to IEEE Xplore.

Tentative program committee

• Abdellah Chehri, University of Quebec- UQAC, Canada.
• Marcelo Keese Albertini Federal University of Uberlandia, Brazil.
• Salvatore Cuomo Univ. of Naples Federico, Italy.
• Awais Ahmad, Bahria University, Pakistan
• Marco Anisetti, University of Milan, Italy
• Ernesto Damiani, Khalifa University, UAE
• Gwanggil Jeon, Incheon National niversity, Korea

Contact information of the organizers

• Abdellah Chehri, University of Quebec, UQAC, Chicoutimi, Canada, Email: achehri@uqac.ca
• Gwanggil Jeon, Incheon National University, Korea, Email: gjeon@inu.ac.kr
• Marco Anisetti, University of Milan, Italy, Email: marco.anisetti@unimi.it