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

Romeo Kienzler

IBM Watson IoT, Switzerland

: Int J Sens 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 specialization 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 large-scale machine learning on resilient cloud infrastructures in addition to the application of Deep Learning technologies on time series data. Romeo Kienzler is a Member of the IBM Academy of Technology, the IBM Technical Expert Council and the IBM Big Data Black Belts team.

Email: romeo.kienzler@ch.ibm.com