IOT, timeseries et prediction avec Android, Cassandra et Spark par Amira Lakhal

Amira Lakhal, membre active de Duchess France, va proposer un talk sur IOT, timeseries et prediction avec Android, Cassandra et Spark, tout d’abord au Lyon JUG le 20 octobre, puis à Devoxx Morocco et Devoxx Be en novembre.

IOT a un énorme potentiel et son impact dans notre vie quotidienne est important.
Dans sa présentation, Amira va montrer un exemple d’utilisation d’un objet connecté, analyser ses données et prédire l’activité avec Spark. Allons lui poser queqlues questions pour nous donner envie d’aller plus loin et de voir son talk.

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Predict your activity using your Android, Cassandra and Spark

Lately, I started a new sport activity: running. When you run, you get really curious about the acceleration, the distance, the elevation and other metrics you can analyse when you practice this kind of sport. As a runner, I started using phone application (runkeeper) and recently I bought a Garmin Watch so I can get more information about my running sessions.
But how this kind of application analyse data and compute all this metrics?
Let’s focus on one metrics: proper acceleration.

What is proper acceleration?

Proper acceleration or physical acceleration is the acceleration it experiences relative to freefall and is …

Analyze accelerometer data with Apache Spark and MLlib

The past months I grew some interest in Apache Spark, Machine Learning and Time Series, and I thought of playing around with it.

In this post I will explain how to predict user’s physical activity (like walking, jogging, sitting…) using Spark, the Spark-Cassandra connector and MLlib.

The entire code and data sets are available on my github account.

This post is inspired from the WISDM Lab’s study and data (not cleaned) come from here.

A FEW WORD ABOUT APACHE SPARK & CASSANDRA

Apache Spark started as a research project at the University of California, Berkeley in 2009 …