Workshop 42: Deep Learning in the IoT
Title: Data Flow Analysis for New Informations

Keywords: Deep Learning, IoT big data, IoT streaming data, DL on the fog and cloud centers, IoT

Summary:
In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect and/or generate various sensory data over time for a wide range of fields and applications. Based on the nature of the application, these devices will result in big or fast/real-time data streams.Applying analytics over such data streams to discover new information,is a crucial process that makes IoT highly efficient, a worthy paradigm for businesses.This workshop calls for works demonstrating the most recent progress and contributions to Deep Learning in IoT. In particular, this workshop will focus on the follows (1)advanced machine learning techniques, namely Deep Learning (DL), to facilitate the analytics and learning in the IoT domain; (2)IoT data characteristicsfrom a machine learning perspective, namely IoT big data analytics and IoT streaming data analytics.(3)DL implementation approaches on the fog and cloud centers in support of IoT applications. This workshop especially encourages applications of emerging DL techniques for IoT data analytics and challenges, the smart IoT devices that have incorporated DL in their intelligence background.
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Chair: Dr. Pasquina Campanella
| University of Bari Aldo Moro
Pasquina Campanella received the Laurea degree (cum laude) and the Ph.D. degree in Computer Science from the University of Bari. She is an researcher of Computer Science at the University of Bari Aldo Moro, Italy. She is the author of papers published in international journals and conferences proceedings. She is a program committee member for national and international conferences and a reviewer of scientific papers, submitted to national and international journals, conferences, and workshops. Her scientific and research activity concerns web information systems, education engineering, e-learning supported by information technologies, pattern recognition, recommender systems,Artificial Intelligent Internet of Things (AIoT) and Mobile Internet of Things (MIoT),machine learning. She has been a Program Chair of different international and national conferences and workshops in the Educational Technology field. She is a member of ACM, IEEE and IEEE Computer Society.