[AISWorld] [RIIAB2018] Deadline Extended: 26 January 2018

[Fulvio Frati]

*** SUBMISSION DEADLINE EXTENDED: 26 January 2018 ***

###################### CALL FOR PAPER ################################# 

Real-time image and video processing in Industrial and IoT Applications
using 
Big Data Analytics (RIIAB2018)

within

11th KES International Symposium on Intelligent Interactive Multimedia
Systems and Services
(KES-IIMSS 2018)
#######################################################################

20-22 June 2018, Mantra, Gold Coast, Australia.
http://iimss-18.kesinternational.org

* Scope of the Workshop

AData induction through electric smart devices is greater 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 device capable to
emanate data paving the way to a
number of applications even in the classical industrial manufacturing
scenario. For instance, a device can
benefit of 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 underling 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
behavioural prediction available
for many vertical applications.
This workshop focused but not restricted to in image- and video- related
applications in IoT and Industrial
scenario that can exploits big data features. It is intended to present the
current state-of-the-art in this field as
well as the future trends.
The topics of interest include, but are not limited to:

- IoT based real-time communication system using image
- Image and video enhancement approaches
- Image processing techniques in big data analysis
- Image based big data storage management for IoT applications
- Image data collection, mining, and prediction methods based on big data
- Video and image data processing in industrial applications
- Human behavioural extraction and monitoring in big data and IoT
applications
- Models and parallel algorithms for medical imaging for IoT
- Real-time human behavioural measurement, modelling, evaluation, reputation
generation, and tools for IoT Big Data
- Formal models and ontologies for information and human behaviour human
feature extraction and behaviour recognition
- Real-time behaviour assessment in big data transmission with efficiency
for IoT
- Administration and interpretation of multimedia big data
- Image base content and structure-based analytics
- Behavioural feature based learning from big data to facilitate monitoring
- Scalable and semantics-driven indexing of ever growing multimedia data
- Other

* Chairs 

- Awais Ahmad, Yeungnam University, Korea <awais at ynu.ac.kr>
- Marco Anisetti, Università degli Studi di Milano, Italy
<marco.anisetti at unimi.it>
- Ernesto Damiani, Khalifa University, UAE <ernesto.damiani at kustar.ac.ae>
- Gwanggil Jeon, Incheon National University, Korea <gjeon at inu.ac.kr>


* Important Dates

- Submission of Papers: EXTENDED! 26 January 2018
- Notification of Acceptance: 9 February 2018
- Upload Final Publication Files: 16 March 201

* Publication

Relevant best papers presented at this workshop can be extended and
submitted to the special issue of “Real-time
Behavioral Monitoring in IoT Applications using Big Data Analytics,”
Concurrency and Computation: Practice
and Experience (http://www.cc-pe.net/journalinfo/issues/2018.html).
The extended versions must contain at least 30% of new materials and include
results related to the major
topics of interest.