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?

?