Data induction through smart devices is more significant compared to information processing capacity. Now a day, data becomes humongous, even coming from a 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.
The proposed special session focuses, 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.
• Digital transformation and artificial intelligence.
• Big data storage management for IoT applications.
• Data collection, data mining, and prediction models.
• Video and image 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, and tools for IoT Big Data.
• Real-time behavior assessment in big data transmission with efficiency for Industrial IoT.
• Behavioral feature-based learning from big data to facilitate monitoring.
• Scalable and semantics-driven indexing of ever-growing multimedia data.
• Security and privacy in IoT.


Important deadlines
– Submission deadline: 15 Feb 2020
– Acceptance/Reject notification: 2 March 2020
– Camera-ready: 10 March 2020
– Author Registration: 10 March 2020
– Conference Sessions: 17- 19 June 2020


Publication
The Full Papers conference proceedings will be published by Springer as book chapters in a volume of the KES Smart Innovation Systems and Technologies series, submitted for indexing in Scopus and Thomson-Reuters Conference Proceedings Citation Index (CPCI) and the Web of Science.

https://www.springer.com/series/8767