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SmartIoT 2018 Workhop: AI enhanced IoT data processing for Intelligent Applications

Description of the Smart IoT Workshop

Building intelligent applications for everyday use is the long-cherished aim of Artificial Intelligence (AI). With numerous devices deployed and used in day-to-day applications including mobile phones, tablets, wearable and other connected sensing and actuation devices, collectively referred to as the Internet of Things (IoT), there is an unprecedented opportunity to develop contextually intelligent applications with far-reaching societal implications. They can deliver fine-grained services in various areas such as healthcare, manufacturing, transportation and social good. These intelligent applications and services, however, could also pose privacy, security and trust issues and risks.

The purpose of the workshop is to discuss how AI techniques can help consume data from IoT to build intelligent applications. The workshop aims to bring together academic researchers and industry practioners who are interested in advancing the state-of-the-art not merely in their specific sub-fields of AI, but also in multi-disciplinary areas in order to solve problems with business as well as societal impacts.

Workshop Topics

By 2020, 50 billion Internet of Things (IoT) are expected to be deployed. That is, massive number of IoTs will be continuously or periodically make the data the generate available on the internet. This workshop will explore the possibilities of using Artificial Intelligence (AI) including machine learning, NLP, and semantic Web techniques to create new solutions that exploit the IoT generated data. The workshop will provide an opportunity to share new findings, exchange ideas, discuss research challenges, present demonstration of unique applications and report latest findings. The workshop will cover a range of topics including, but not limited to:

Semantic sensor (IoT) data

Information extraction from real-world data streams

Machine Learning, knowledge-enabled and spatio-temporal processing applied IoT data

AI techniques for intelligent IoT data fusion

Context-aware applications and services

Linked open IoT data, repositories of semantic IoT data

Semantic IoT data management

Chatbots using NLP and IoT data

Reasoning with IoT data, including semantic, cognitive and perceptual computing

Ethical and privacy issues with IoT data

Human computer interface (HCI) issues, Data visualization

Applications in smart city, healthcare, transportation, energy, public safety, disaster coordination and other areas

Important Dates

Workshop Paper Submission Due: 13 October 2017

Notification to authors: 8 November 2017

Camera Ready of authors’ papers: 21 November 2017

Workshop Date: 2nd or 3rd February 2018

Where: New Orleans, Lousiana, USA

Co-located with AAAI 2018 (32nd AAAI Conference on Artifiical Intelligence)

Submission

Number of pages: ?

Submission Web page on Easy Chair: https://easychair.org/conferences/?conf=smartiot2018

Papers must be formatted in AAAI two-column, camera-ready style AAAI style files: [1]

Regular research papers may be no longer than 7 pages, where page 7 must contain only references, and no other text whatsoever.

Short papers, which describe a position on the topic of the workshop or a demonstration/tool, may be no longer than 4 pages, references included.

Organisation

The workshop co-chairs:

Payam Barnaghi

Homepage: http://personal.ee.surrey.ac.uk/Personal/P.Barnaghi/

Institute: University of Surrey, UK

He is a Reader in Machine Intelligence at the Department of Electronic and Electrical Engineering and a member of the Institute for Communication Systems (ICS) at the University of Surrey. He is also an adjunct member of the Graduate Faculty at Wright State University.

Payam Barnaghi is a senior member of IEEE and a Fellow of the Higher Education Academy. He is technical lead of the Department of Health/NHS TIHM for Dementia project and he was co-ordinator and Principal Investigator of the EU FP7 CityPulse project on smart cities and large-scale data analytics. His recent activities include associate editor of the IEEE Internet of Things Journal and Elsevier Journal of Digital Communications and Networks (DCN), member of the editorial board of Elsevier Heliyon, guest editor of a special issue of IEEE Intelligent Systems on Web of Things, and a special issue of IEEE Internet Computing on Physical-Cyber-Social Computing. He is a member of the World Wide Web Consortium (W3C) Advisory Committee and the EPSRC Peer Review Associate College. He is the programme leader for Electronic Engineering for Medicine and Healthcare at the University of Surrey.

Amelie Gyrard

Homepage: http://sensormeasurement.appspot.com/?p=AmelieGyrard

Institute: Univ Lyon, MINES Saint-Etienne, CNRS, Laboratoire Hubert Curien, Saint-Etienne, France

Amelie Gyrard is a post-doc researcher at Ecole des Mines de Saint-Etienne, France, working within the Connected Intelligence - Knowledge Representation and Reasoning team. Previously, she was a post-doc at Insight Center for Data Analytics, National University of Galway and actively working in the scientific development and coordination of the FIESTA-IoT (Federated Interoperable Semantic IoT/Cloud Testbeds and Applications) EU H2020 project. Her research interests are on Software engineering for Semantic Web of Things and Internet of Things (IoT), semantic web best practices and methodologies, ontology engineering, reasoning and interoperability of IoT data. She holds a Ph.D. from Eurecom since 2015 where she designed and implemented the Machine-to-Machine Measurement (M3) framework. The title of her dissertation is ``Designing Cross-Domain Semantic Web of Things Applications. She also disseminated her work in standardizations such as ETSI M2M, oneM2M, and W3C Web of Things.

Amit Sheth

Homepage: http://knoesis.org/amit/

Institute: Kno.e.sis, Wright State University, USA

Amit Sheth is an educator, researcher, and entrepreneur. He is the LexisNexis Ohio Eminent Scholar, an IEEE Fellow, and the executive director of Kno.e.sis—the Ohio Center of Excellence in Knowledge-enabled Computing. Kno.e.sis' faculty and researchers are computer scientists, cognitive scientists, biomedical researchers, and clinicians. It has the largest US academic research group in the area of Semantic Web and maintains a very high publication impact. Prof. Sheth is one of the 100 top computer sciences based on publication impact (h-index = 95). He has founded three companies by licensing his university research outcomes. He has organized over 75 international events (as General/Organization Committee/Steering Committee/Program Chair) and given over 35 tutorials. Examples of his relevant activities includes (a) initiating and co-chairing W3C Semantic Sensor Networking group, whose outcomes serve as the defacto international standard, and (b) serving as the IoT department editor for IEEE Intelligent Systems.

Biplav Srivastava

Homepage: http://researcher.watson.ibm.com/researcher/view.php?person=us-biplavs

Institute: IBM, USA

Biplav Srivastava is a Research Staff Member \& Master Inventor at IBM Research and an ACM Distinguished Scientist and Distinguished Speaker. With over two decades of research experience in Artificial Intelligence, Services Computing and Sustainability, Biplav's current focus is on promoting goal-oriented human-machine collaboration for contextual applications using domain and user models, learning and planning. Biplav's work has lead to many science firsts and high-impact commercial innovations (up to \$B\Plus), 100\Plus papers and 40\Plus US patents issued. He co-organized the workshop track at IJCAI 2016, has co-organized over 30 workshops and given 5 tutorials at leading AI conferences.

PC:

The following is a tentative list of technical programme committe members:

Manfred Hauswirth, Technical University of Berlin/Fraunhofer FOKUS

Monika Solanki, University of Oxford, UK

Septimiu Nechifor, Siemens, Romania

Andreas Emrich, DFKI/University of Saarbrucken, Germany

Maria Bermudez, University of Granada, Spain

Frieder Ganz, Adobe, Germany

Cory Henson, Bosch Research \& Technology, USA

Paolo Bellavista, University of Bologna, Italy

Ajit Joakar, City of London, UK

Edith Ngai, Uppsala University, Sweden

Fangming Liu, Huazhong University of Science and Technology, China

Yasmin Fathy, University of Surrey, UK

Danh Le Phuoc, TU Berlin, Germany

Josiane Xavier Parreira, SIEMENS AG, Austria

Maria Esther Vidal, Universidad Simon Bolivar, Venezuela

Simon Mayer, Siemens, USA

Pankesh Patel, Fraunhofer, USA

Ali Intizar, Insight-NUIG, Ireland

Gyu Myoung Lee, Liverpool John Moores University, UK

Emil Lupu, Imperial College London, UK

Bin Guo, Northwestern Polytechnical University, China

Koji Zettsu, NICT, Japan

Kerry Taylor, The Australian National University, Australia

Axel Ngonga, University of Leipzig, Germany

Xiang Su, University of Oulu, Finland

Philippe Gautier, Pierre and Marie Curie University, France

Program

Program will appeal later.