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Architecting IoT systems with
Machine Learning
Rudradeb Mitra | https://www.linkedin.com/in/mitrar/
Data Science Summer Conference
The vision of IoT by Intel https://www.youtube.com/watch?v=rnDey89wp_M&t=31s
How many of you live in this home?
Architecting IoT with Machine Learning
What do I want talk about?
• How to build consumer adopted IoT products?
• Through stories of my experiences
• Some problems you can solve!
My 15 years on and off affair with IoT
connecting the dots...
2003, Bremen, Germany
RoboCup Japan
2003, Bremen, Germany
To solar adoption through satellite images
The story of IoT from 2003-2018
IoT
So what went wrong...
Consumer IoT systems
Database
View data
What are the problems?
• Viewing past data has almost no value
• Most IoT startups ended up just collecting big data
• Very few killer applications which creates x5-x10 value
Hidden cost of IoT
Relational Data Time series 'Big' Data
(activity, time)(name, address)
Relational legacy
data
Big data (eg time-series data)
Database
eg. Postgres
Database
eg. Mongo,
Casandra
Application logic (to split and combine data into
relational / non-relational part)
User Query
SQL query Time series
data query
Database architecture of IoT
@copyright: Rudradeb Mitra
Data Volume and Speed
@copyright: Rudradeb Mitra
For adoption technology needs to cross
the chasm
• You have to solve a real problem for them.
Build painkillers, not vitamins!
So how to cross the chasm?
Let me tell you a story...story from one of my startup
Driver’s app
Record a trip Trip feedback
Goals &
challenges
Rewards
Results
Over 4Mkm driving data
IoT Architecture
Database
Engagement
Add a switch to turn off/onView Trip
• Incentivizing

• Nudging 

• Not forced
What is missing?
Do you think majority will adopt?
Architecting IoT with Machine Learning
When there is nothing else, Machine Learning comes to rescue!
What is Machine Learning?
• "learn patterns from data without explicitly being programmed"
Why is Machine Learning useful?
Architecting IoT with Machine Learning
IoT Architecture with Machine Learning
Database
Gamification
Social Engagement
Add a switch to turn off/onView Trip
Predictive +
Analytics
Machine Learning
Algo
@copyright: Rudradeb Mitra
What are the values?
• Find risky drivers and adjust their premiums so that majoity pay less
• Predict short and long term future to make roads safer by changing
behaviors
Lets see using Machine Learning (esp. Neural Nets)
1. Can we find patterns of risky drivers?
Patterns of risky drivers - Clustering
Picture taken from: http://www.ai-junkie.com/ann/som/som1.html
Find patterns in data
Self Organizing Maps (Clustering)
0.1
0.3
- Euclidean Distance between
training vector and weights
- The best match node is selected
- Adjust weights of neighboring nodes
to match this weight
0.55
0.15
0.31
0.49
Training
Data
0.6
0.9
0.8
@copyright: Rudradeb Mitra
Picture taken from http://www.ai-junkie.com/ann/som/som1.html
Most risky drivers
Most safe drivers
For the driving example
And how is that helpful?
• Premiums can be adjusted according to driving behavior and thus
majority will end up paying less
2. Can we go further and predict short term future?
word2vec- Predicting next word
word2vec
- Does not understand words or
grammar
How
Feeling
You
Are
Today
Input words
embeddings
Predicted next word
Hidden
Layer
Output word
embedding
Word2vec Word embeddings
X.WI.WO
Example
word xi
N= 2
0
0
0
1
0 0.3 0 0.7 0 ... 0
0.1
0.77
0.39
.
.
0 0.29 0 0.55 0 ...0.3
0.5
0
Wi =
Wo =
Word embedding for Xi = X. Wi . Wo
Word embedding Xi = [0.33 ... 0.64 ]
0
0
0
1
X =
word2vec - 2d space
- Output matrix to 2
dimension using Principal
component Analysis
Picture taken from https://www.lucypark.kr/courses/2015-ba/text-mining.html
Germany - France + Paris
= Berlin
Prediction for drivers
score acceleration on Friday
score braking on Friday
word2vec
- Using the semantic association
between orders
(Product ID)
(Predicted score on
Sunday)
score braking on Saturday
score speed on Saturday
And how is that helpful?
• Advance short term warnings making roads safer and saving lifes
3. And what about long term future?
RNN
Y0
X0
RNN
Y1
X1
RNN
Y2
X2
RNN
Y3
X3
RNN
Y4
X4
Long Short Term Memory
Cell state
Picture taken from http://colah.github.io/posts/2015-08-Understanding-LSTMs/
NN NN NN
f
NN
Forget
gate
Input
gate
Output
gate
New information
Forget an old
information
Updated
information
added
@copyright: Rudradeb Mitra
LSTM
cell
LSTM
cell
LSTM
cell
Score Score Score
Driving history
Time 1 Time 2 Time 3
@copyright: Rudradeb Mitra
And how is that helpful?
• Provide nudging techniques to change behaviors
To summarize
• Roads safer
• Adjust premiums saving money
• Incentive to good behaviors
Who will benefit
• Majority of people like you and me, who are GOOD drivers!
What other applications are out there?
03/06/2010
2010, Prague, Czech Republic
What can we achieve?
• Machine Learning can predict your future consumption (short term,
long term).
• If I know how much I will consume, I can save money and save
electricity!
Who will benefit
to people who have been left behind...
Decentralized solar energy
Output
Fully
connected
pooled
feature maps
pooled
feature maps
feature
maps
feature
maps
Input
image
32x32
Convolutions
6@28x28
Subsampling Convolutions Subsampling
6@14x14 16@10x10 16@5x5
Convolutional Neural Networks
Who will benefit
to people who have been left behind...
Healthcare
Database
Gamification
Add a switch to turn off
Not to punish, social encouragement
Learning Algorithm
@copyright: Rudradeb Mitra
What can we achieve?
• If I know advance health warning, I can save lives!
• Medical cost can do down
Retail
Future
@copyright: Rudradeb Mitra
IoT needs Machine Learning
for adoption
Feel free to contact:

https://www.linkedin.com/in/mitrar/

mitra.rudradeb@gmail.com

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