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Cloud Options for
Wearable Data Analysis
Gene Leybzon, November 2015
Data
Collection
Mobile
Device or
Hub
Delivery to
Cloud
Analysis
Notifications
“Traditional“ Wearable Data Stream
Data
Collection
Mobile
Device or
Hub
Delivery to
Cloud
Analysis
Notifications
Wearable Data Stream
with partner API
Partner Cloud
Wearable Data Stream with Machine
Learning
Data
Collection
R/T Data
Analysis based
on ML model
Local
Notification
Analysis ML model
tweaking Notifications
Updated ML params
Why Cloud?
• Scale (50 billion connected devices
by 2020)
• Connectivity options
• Make sense of data takes
computing power
• Reliable customer experience
 Wide range options to connect (both message-
based and streaming data)
 Fast and global network
 Big Data storage and real-time analysis
 99.99% (or better) uptime and availability
 Security and authentication
IoT developers expectations from
the Cloud
Viable Cloud Options
AWS
AWA IoT message-basedc
ommunicaton
AWS IoT connection-oriented
communication
AWS Cloud-based data processing
AWS IoT Landscape
AWS IoT Features
Connect
devices to
AWS Cloud
Connect
between
devices
Secure data
and
interactions
Process data
in the cloud
Message-based (offline)
communication
Google Cloud Platform
Google for IoT
 Google backbone network
 BigQuery (Big data database)
 Cloud dataflow (data streaming)
 Cloud pub/sub (messaging infrastructure )
 Brillo OS and Weave coming soon
Google Brillo OS
Google Weave
Easy setup
Direct
connectivity
Interpretability
Google Weave Hub
Google Nest Weave
VMware
VMware
 Managing devices: AirWatch
 Stream data: vRealize Log
 Cloud: vCloud Air or Hybrid Cloud
VMware vCloudAir
Microsoft Azure IoT Suite
 Remote
monitoring
 Predictive
mantanace
Microsoft Azure Cloud Services
Virtual
Machines
Mobile
Push
SQL
Database
Media
Streaming
Websites
Active
Directory
Hadoop
Questions?

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Cloud Options for Wearable Data Analysis

Editor's Notes

  1. Data collection and processing path
  2. Example: FitBit
  3. Data collection and processing path
  4. Data collection and processing path
  5. Data collection and processing path
  6. https://aws.amazon.com/iot/how-it-works/#shadows
  7. https://aws.amazon.com/iot/how-it-works/#shadows
  8. http://googledevelopers.blogspot.com/2015/10/building-brillo-iant-devices-with-weave_27.html?linkId=18294025
  9. http://googledevelopers.blogspot.com/2015/10/building-brillo-iant-devices-with-weave_27.html?linkId=18294025