Watson / Presentation Title / Date1 #BeBold

2017 Sales Academy#BeBold

Analytics for IoTWillem Hendriks

Arjen van der Wetering

Watson / Analytics for IoT / 27 Feb 20172 #BeBold

1. Machine Learning Demystified (a small intro)

2. Typical IoT Architecture for Analytics

3. How DSX & IoT Platform support the Typical Architecture

4. Use-Case (RAMLAB Welding Robot)

Watson / Analytics for IoT / 27 Feb 20173 #BeBold

Task we want the computer to take over. Examples:- Classification- Regression

“What activity am I doing, based on my measurements?”

walking / driving / sleeping / working / change diapers

“What is the probability, the machine will fail in the next 60 minutes?”

a number from 0% to 100%

Machine Learning Demystified

Watson / Analytics for IoT / 27 Feb 20174 #BeBold

Task we want the computer take over:- Classification- Regression

Data

Watson / Analytics for IoT / 27 Feb 20175 #BeBold

Task we want the computer take over:- Classification- Regression

Data

model / method

learns from data

Watson / Analytics for IoT / 27 Feb 20176 #BeBold

Task we want the computer take over:- Classification- Regression

Data

model / method

learns from data

measurement forquality of our model / method

Watson / Analytics for IoT / 27 Feb 20177 #BeBold

Task we want the computer take over:- Classification- Regression

Data

model / method

learns from data

measurement forquality of our model / method

The machine is training!

Watson / Analytics for IoT / 27 Feb 20178 #BeBold

Data

model

learns from datameasurement forquality of our model

We call columns in our data “features”

We call transforming the columns to help the model learn“feature engineering”

example: speed = distance/time,will possible help the model learn,to classify my activity:

low speed : high chance sleepinghigh speed: high chance driving

Example model for classification:loglogistic regression

Example model for regression:linear model

many many more, tree's, random forests, deeplearning, SVM

Spark, SPSS, python, are tools to train models from data.

DSX is a cloud environment, where many tools are available for analysts.

To evaluate practical usage of our trained model, we want metrics of the learning

“95% of activities correctly classified”

95% can cause deaths, or make you a millionaire in 24 hours

Watson / Analytics for IoT / 27 Feb 20179 #BeBold

Historical Data

Create a collection of historical data.

Typical IoT Architecture for Analytics

Watson / Analytics for IoT / 27 Feb 201710 #BeBold

Historical Data

model

learns from data

Typical IoT Architecture for Analytics

Watson / Analytics for IoT / 27 Feb 201711 #BeBold

Current Architecture

Welding Robot

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events Raw events

Raw events

Aggregated values

OperatorDashboard

Node-REDapplication

Watson / Analytics for IoT / 27 Feb 201712 #BeBold

Historical Data

model

learns from data

When we are happy about the performance, we can implement the model, and benefit in the IoT world.

Analytical Components in IBM Bluemix

Watson / Analytics for IoT / 27 Feb 201714 #BeBold

Historical Datamodel

learns from data

Cloudant

geo-spatial!

BigSQL!

Real real-time!

Data Scientists!

Bluemix & DSXData Science Experience

Watson / Analytics for IoT / 27 Feb 201716 #BeBold

Use-Case RAMLAB Welding Robot

Watson / Analytics for IoT / 27 Feb 201717 #BeBold

Current Architecture

Welding Robot

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events Raw events

Raw events

Aggregated values

OperatorDashboard

Node-REDapplication

Watson / Analytics for IoT / 27 Feb 201718 #BeBold

Enhanced Architecture

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events

Raw events

Aggregated values

OperatorDashboard

Other sources

Feedback loop(predicted errors, control)

Data Science Experience

Watson / Analytics for IoT / 27 Feb 201719 #BeBold

DEMO