Dr. Hendrik F. Hamann is a Principal Research Staff Member and Research Manager in the Physical Sciences Department at the IBM T.J. Watson Research Center, Yorktown Heights, NY. He received his PhD from the University of Goettingen. In 1995 he joined JILA (Joint institute between the University of Colorado and NIST) as a Research Associate in Boulder, Colorado. Since 2001 he is leading the Physical Analytics program in IBM Research. His current research interest includes the combination of physical model, machine-learning and big data technologies, internet of things, sensor networks, and sensor-based physical modeling with applications to renewable energy, precision agriculture etc. He has authored more than 80 peer-reviewed scientific papers and holds over 90 patents. Dr. Hamann is an IBM Master Inventor, a member of the IBM Academy of Technology and has served on governmental committees such as the National Academy of Sciences, the National Science Foundation and as an industrial advisor to Universities. He is a member of the American Physical Society (APS), Optical Society of America (OSA), The Institute of Electrical and Electronics Engineers (IEEE) and the NY Academy of Sciences.
The realization of the Internet of Things (IoT) poses undoubtedly significant technical and engineering challenges (such as security, networks, protocols, communication, energy efficient hardware and software, data management etc), which is subject of a lot of current research. A less researched matter is whether new analytical methods have to be developed, which not only could help to overcome some of those challenges but also would provide the underlying intelligence for smarter and more complex IoT applications. In this presentation we first review relevant technical and business trends of IoT. Then a few selected use cases are being discussed which show the limitations of current approaches and demonstrates how existing data analytics can be substantially enhanced by combining them with physical or other industry models thereby overcoming some of the more intrinsic challenges of IoT.