How to capture, analyse and react on IoT generated sensor data in real time

2^nd International Conference and Business Expo on Wireless & Telecommunication

April 21-22, 2016 Dubai, UAE

Romeo Kienzler

IBM Watson IoT, Switzerland

Keynote: Sensor Netw Data Commun

Abstract :

In this hands-on tutorial session you will learn how to connect various IoT devices (exemplified using a Raspberry Pi) to a MQTT broker, ingest data in real-time in a NoSQL database (for historic data processing), train a machine learning model (e.g. Neural Net, ..) on this historic data and then - using this model - react on live-data using this model. Finally the result will be translated into an action and sent back to the IoT device.

Biography :

Romeo Kienzler holds a Master Degree in Information Systems with specialisation in Applied Statistics and Bioinformatics from the Swiss Federal Institute of Technology. He works for IBM Watson IoT as a Chief Data Scientist. His current research focus is on largescale machine learning on resilient cloud infrastructures in addition to the application of DeepLearning technologies on time series data. Romeo Kienzler is a Member of the IBM Academy of Technology, the IBM Technical Expert Council and the IBM BigData BlackBelts team.

Email: romeo.kienzler@ch.ibm.com