Watch talk ➟ http://bit.ly/1NJNJX9 As more and more devices are internet enabled, creating the so called “Internet of Things” (IoT), our ability to understand the nature and state of our environment becomes both more powerful, and more resilient. Much of the early focus on IoT has been on the new capabilities that connected devices can bring. However, much of the power and promise of IoT comes from the combined view that multiple, disparate, connected devices can provide. We will discuss the increased analytical potential of systems that incorporate multiple, overlapping observations of operations or behaviors. We will work through some examples that demonstrate how to benefit from the coming ubiquitous visibility. We will also describe how IoT will help build more resilient systems that degrade gracefully, rather than failing outright. This resilience will be critical as we become more dependent on the successful collaboration and coordination of disparate, connected devices.

1. DATA
SCIENCE
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For the Internet of Things,
the More Things the Merrier
John Akred
Founder & CTO, Silicon Valley Data Science
BigDataAnalysis

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SCIENCE
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#datapopupaustin
April 13, 2016
Galvanize, Austin Campus

4. FOR THE INTERNET OF THINGS, THE MORE THINGS
THE MERRIER
Data Science Pop-up in Austin
John Akred, CTO
13 April 2016

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@SVDataScience5
Silicon Valley Data Science transforms
business through data science and
engineering.

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OUR TEAM

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more=better?
https://pixabay.com/static/uploads/photo/2015/05/25/05/27/network-782707_960_720.png

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The Internet of Things (IoT) is the
network of physical objects—
devices, vehicles, buildings and
other items—embedded with
• electronics,
• software,
• sensors, and
• network connectivity
that enables these objects to
collect and exchange data.
WHAT MAKES A THING
AN IOT THING?
Source:
https://en.wikipedia.org/wiki/Internet_of_Things
"Internet of Things Global Standards Initiative". ITU. Retrieved 26 June2015.

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A connected thing
can do useful stuff for
us, sometimes really
useful.
http://arstechnica.com/science/2016/04/er-docs-get-heart-rate-info-
from-fitbit-save-patients-life/

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An ecosystem of
connected things
can do useful stuff
for us too.
https://jawbone.com/blog/napa-
earthquake-effect-on-sleep/

11. @SVDataScience11
Value of
Connected Devices
Single Device
$100s/year
Device Network
50% aggregate
demand

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Hard Failure: If the data source is
broken, so is the app.
Stovepipe: One-to-one
relationship from data source to
product.
Multi-sourced: Redundancy of
overlapping data sources makes
your products more resilient.
Graceful Degradation: If a data
source breaks, there is
a backup and your app
continues to function.
Production data services
abstract the probabilistic
integration of overlapping data
sources. We call this model a
Data Mesh.
Why more = better? DATA RESILIENCY

13. @SVDataScience

14. @SVDataScience14
• Commuter rail between San Francisco and San Mateo and
Santa Clara counties ~30 stations
• 118 passenger cars
• 60% >=30 years old
• 2014 weekday ridership is 52,019 people daily
• On-time performance is about 92%
• No reliable real-time status information
• API outage between April 5th and June 2nd

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@SVDataScience16
HOW DO WE KNOW IF THE TRAIN IS ON
TIME?

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@SVDataScience17
MISSING DATA?
The departure data:
• mostly “on time”
• when significant delays
occur, they often appear
suddenly
• often missing >10% per day
• ~1 minute resolution

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@SVDataScience18
AUDIO

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@SVDataScience19
VIDEO DETECTION - FRAME ANALYSIS
No Train Detected Train Detected
RawImage
(+ROIs)
Relative
Motion
(+ROIs)

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@SVDataScience20
VIDEO

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@SVDataScience21
SOCIAL MEDIA AS SENSOR
Baseline

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@SVDataScience22
CALAMITY DETECTION IS ACCURATE

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@SVDataScience23
20
THE MOST IMPORTANT SIGNAL
Where is
the train
right now?

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@SVDataScience24
PREDICTION MODEL: NEURAL NETWORK
neural network
prediction residuals
previous delay
residuals

25. THANK YOU
Yes, we’re hiring!
info@svds.com
John Akred
@BigDataAnalysis

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