Download - Cloud Options for Wearable Data Analysis
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 Machine
sMobile Push
SQL Databas
eMedia
Streaming
Websites
Active Director
y
Hadoop
Questions?
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