Big Data Analytics and Internet of Things Workshop

December 11, 2017
Boston, MA

Connected objects and devices embedded in smart homes, transportation, and industrial equipment are digitizing the physical world and open unique opportunities to control and understand complex physical systems much better than ever before. However, a new set of models and analytical methods will be required when dealing with such systems, which greatly depart from traditional analytical, data-driven only methods used in common big data applications (e.g., on transactional or social data). Currently, less than 5% of the total produced data is analyzed due to data accessibility, complexity in handling heterogeneous data, and lack of scalable analytics. Communication bandwidth limitations require development of solutions where analytics/computation is distributed from the point of IoT device measurement up to clouds; possible solutions are edge computing, compressed sensing, and contextual computation. Emerging examples in environmental monitoring, smart grid and autonomous cars combine data-driven approaches with physical or other first-principle models to improve safety, security, and operational efficiency.

What data is worth to save, how to distil data to retain the essential content, and what new data layers are required for analytics is an ongoing discussion that require a multi-disciplinary approach to envision new applications based on massive amount of IoT data. The purpose of this workshop is to provide a new venue for researchers in this emerging field at the forefront of exploiting Internet of Things (IoT) data to discuss algorithms, new techniques, and approaches which deal with these specific challenges.

Invited speakers

  • Gregory Dobler, Center for Urban Science + Progress, New York University, USA
  • Matt Nielsen, Principal Scientist, General Electric, USA
  • Distinguished Panel Speakers

  • William Chappel, Office Director, Darpa, USA
  • Hon Pak, Chief Medical Officer, 3M, USA
  • Workshop topics of interest

    Topics of interest include, but not limited to:

    I. Industry specific big data analytics for IoT

  • Application of IoT in Insurance, Agriculture, Healthcare, and Smart grid
  • Connected cars, mobile IoT platforms, and real time system optimization
  • Energy efficiency and smart homes
  • Natural resource monitoring using satellite data
  • Big data for social goods to eliminate famine and mitigate poverty
  • II. Scalable data analytics and Data Fusion

  • Combining physical models with statistical analysis
  • Efficient data curation and indexing for data discovery
  • Risk and liability for autonomous systems driven by IoT devices/sensors
  • Data compression for bandwidth constrained communications
  • Emerging standards for communication protocols and data exchange
  • Securing IoT devices and communication channels to preserve privacy and cyber-security
  • III. Edge computing and Edge Data Informatics

  • Computing on the frontier
  • Optimization for the edge. Optimal and dynamic sensor placement
  • Distributed “Digital twins”
  • Distributed Asynchronous algorithms for edge computing
  • Making the edge devices self-aware, self-healing, self-simulation
  • Exploration/Exploitation trade-off on the edge
  • Avoiding over treating, over sensing, over testing, and over fitting in the edge
  • Calculus for the Edge, like Time Scale Calculus
  • Call for papers

    The workshop considers manuscripts that describe original and state-of-the-art research with emphasis on practical applications at the intersection of the Big Data, Internet of Things and applied engineering and physics knowledge domains. Description of analytical methods and tools which combines traditional data-driven approaches with physical modeling and methods to discover interpretable models from data as well as the characterization of the computational requirements for these analytical methods.Each submission will be peer reviewed by 3 Technical Community members.

    • Oct 15, 2017: Due date for full workshop papers submission
    • Nov 15, 2017: Camera-ready of accepted papers
    • Nov 1, 2017: Notification of paper acceptance to authors
    • Dec 11-14 2017: Workshop
    • Paper Submission Please submit a full-length paper (up to 10 pages IEEE 2-column format) through the online submission system.

      All papers accepted for this workshop will be included in the Workshop Proceedings published by the IEEE Computer Society Press.

      Paper Formatting Instructions

      Templates Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines.

      Use the templates shown below.

    • 8.5" x 11" Word template downloadable from here.
    • 8.5" x 11" Word template (PDF) downloadable from here.
    • LATEX formatting macros downloadable from here.

    Organizing committee

  • Levente Klein, IBM Research, USA
  • Albert Boulanger, Columbia University
  • Hendrik Hamann, IBM Research, USA
  • G.P. Li, University of California, Irvine, USA
  • Mirko Presser, Aarhus University
  • Mohammad Al Faruque, University of California, Irvine, USA
  • Jurij Paraszczak, IBM Research/NYU USA
  • Sergio Bermudez, OSRAM Research, USA
  • Alexandru Niculescu-Mizil, NEC Laboratories America, USA
  • Conrad Albrecht, IBM Research, USA
  • Big Data Analytics and Internet of Things (BDA-IoT)

    This workshop targets the emerging multidisciplinary field at the intersection of internet of things (sensors and networks), big data technology (Spark, Hadoop), and domain specific analytics where a combination of the tools and methods is needed to yield transformational solutions for industries, government, and society.