Iot in Practice: Case Studies in Data Analytics, with Issues in Privacy and Security

The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. The advent of IoT applications is here: industry 4.0, connected industry, industry automation, smart cities, smart grids, energy efficiency, etc. All this IoT applications require advanced analysis of big data streams from sensors and small devices, while addressing security and privacy concerns. This tutorial is a gentle introduction to mining IoT big data streams. The first part introduces data stream learners for several learning tasks including distributed algorithms. The second part we present few applications for predictive maintenance, prediction for renewable energies, and social network analysis for telecommunications data streams. The last part dwells upon security concerns regarding IoT data streams containing sensitive and confidential data when predictive analytics is performed over a third-party cloud service. Link to tutorial: https://sites.google.com/site/kdd2017iot/