Analytycs fot iot_hen_we_tv1

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)


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


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

Data



Data

model / method

learns from data



Data

model / method

learns from data

measurement forquality of our model / method



Data

model / method

learns from data

measurement forquality of our model / method

The machine is training!


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


Historical Data

Create a collection of historical data.

Typical IoT Architecture for Analytics


Historical Data

model

learns from data

Typical IoT Architecture for Analytics


Current Architecture

Welding Robot

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events Raw events

Raw events

Aggregated values

OperatorDashboard

Node-REDapplication


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


Historical Datamodel

learns from data

Cloudant

geo-spatial!

BigSQL!

Real real-time!

Data Scientists!

Bluemix & DSXData Science Experience


Use-Case RAMLAB Welding Robot


Current Architecture

Welding Robot

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events Raw events

Raw events

Aggregated values

OperatorDashboard

Node-REDapplication


Enhanced Architecture

Watson IOTPlatform

CloudantDatastore

StreamingAnalytics

AnalyticsDashboard

Raw events

Raw events

Aggregated values

OperatorDashboard

Other sources

Feedback loop(predicted errors, control)

Data Science Experience


DEMO

Analytycs fot iot_hen_we_tv1

Data & Analytics

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