In the next few posts, we will describe the journey of collecting (tagged) data, experimenting with potential classification models, and then finally implementing these models. It was revealing to experience the challenges of implementing truly reliable and near real-time analysis system in a world of unerliable networks and users who cannot tolerate interruptions.
We ended up performing principal component analysis on a type II DCT of the sensor data we receive: this then formed basis for the training set of a support vector machine. We have done the modelling in R, then exported the
libsvm settings, and loaded this code in Scala, where we perform the classification on the incoming stream of data.