Tiny Sensors, Big Data: Extracting Meaning with Wireless Sensor Networks and the Cloud

Tiny Sensors, Big Data
Using the Cloud to Extract Meaningful Information
from Wireless Sensor Networks

Jake Galbreath, VP Wireless Systems
jhgalbreath@microstrain.com
Presented at Sensors in Design, March 28, 2012

Little Sensors. Big Ideas.®

Internet of
Things (IoT)
InfoGraphic
by Cisco

© Copyright 2012 All Rights Reserved

MicroStrain, Inc
• Based right outside of Burlington, VT
• Developer and manufacturer of small,
durable, smart sensors
• SensorCloud Platform for Data Visualization,
Storage, Collaboration, and Analysis
www.SensorCloud.com


Core Product Groups

Inertial Sensors Wireless Sensors Displacement Sensors

Energy Harvesting Cloud Platform


Industries


Wireless Gateway


mXRS Wireless Sensors
• Scalable wireless network
(100’s of nodes simultaneously)

• Time synchronized
(+/- 32 microseconds)

• Extended range (up to 2 km)

• Advanced power management
(eliminate battery replacement)

• Wide range of sampling rates
(from once per hour up to 4kHz continuous, or up to 100 KHz bursts)


High speed .. Low power?
Node type and sample rate RF comm. Distance RF comm. Distance
(70 m) (2 Km)

SG-Link-mXRS 8 Hz 0.68 mA 0.85 mA
(w/ 1000 Ohm strain gauge)
SG-Link-mXRS 128 Hz 4.00 mA 5.85 mA
(w/ 1000 Ohm strain gauge)
G-Link-mXRS 8 Hz 0.37 mA 0.45 mA

G-Link-mXRS 128 Hz 2.10 mA 2.89 mA

• Energy harvesting compatible
• Further power optimizations achievable (see talk tomorrow,
example: 250 uA for 128 Hz energy harvesting strain node)


How much data
is really needed?

•Different applications, different paradigms.
•Data InformationKnowledgeWisdom
•Data InformationAction
•Data.


Whenever possible, reduce data
• Reduces RF communications
• Reduces energy consumption
• Reduces battery and harvester size
• Reduces size and weight of nodes
• Reduces connectivity cost
• Reduces storage cost
• Reduces overall energy footprint


But sometimes it isn’t practical.

• Complex Systems
• Inter-channel dependencies
• Computationally expensive analysis and
algorithms
• Raw data monitoring and archiving to support
future analysis and research
• Physical models and algorithms evolve


Use the Cloud when needed!


The real value of cloud

• Inexpensive, on-demand, elastically scalable
storage

• Inexpensive, on-demand, elastically scalable
processing


Popular Cloud Platforms

• Amazon AWS
• Microsoft Azure
• RackSpace OpenStack


www.sensorcloud.com

Try it out for free

SensorCloud Specs
• Built on Amazon AWS • All API transactions
• Elastically scalable secured via HTTPS/SSL
architecture • Unlimited Data Storage
• Each input channel can • Availability: 2 hours of
handle up to 5000 data downtime last year
points per second
• Triple-redundant S3
data storage with
99.999999999%
durability


SensorCloud Features


OpenData API
• Secure data upload and download using HTTPS &
SSL
• Fully REST compliant API
• Example code for common languages and
platforms (python, Java, C#, C++, Labview,
iPhone, Android)
• 64-bit UTC timestamp with nano-second
resolution
• Data download currently supports CSV and XDR
file formats


WSN + Cloud
Data Usage Examples


200MB per Cow-Year

Internet of Things (IoT)
InfoGraphic
by Cisco


Vineyard Data:
A few Gigabytes per year, per site.


Nasa Shuttle Acoustic Shock Testing:
A few gigabytes per launch.


Bridge Data:
Gigabyte per day, per bridge.


Vehicle Health Monitoring:
Up to a Gigabyte per vehicle hour.

NAVAIR ARMY NASA
MH-60S UH-60A UH-60
RASCAL
Pitch-
Link
SG-Link
Mil
G-Link
Mil
HS-Link

WSDA-
Mil
RFID


Demo: Terabyte of time series data


Analytics in the cloud

•Access to low cost, elastically scalable
processing
•Process big data sets in place, avoid bulk data
transfer
•Easy to collaborate and share results


MathEngine™

• SensorCloud’s data analysis platform
• Create, edit, upload, execute and schedule
python and octave apps
• Built on Amazon EC2


MathEngine™ Demo


MathEngine

• Data processing and analytics
• Create new derived and virtual channels, feed
them back into SC data store
• Use python to scrape data from any web
connected source
• Fully-customizable, event-driven and scheduled
reporting using python for email and octave for
embedded plots


Future Directions for SensorCloud

• R Language Support in MathEngine
• Mapping support
• Improved mobile experience


Sensing the Future
• Sensors, in the billions, will become more
integrated into structures, machines & the
environment
• New capabilities forecast failures before they
occur, provide timely alerts and offer
information to improve operations &
maintenance


Extra Slides


mXRS Synchronized Network Capacity


mXRS Synchronized Network Capacity
(Burst Mode)


Experience
• Product sales in over 60 countries
• Major customers including Caterpillar, GE,
Ford, Intel, Bell Helicopter, Pratt & Whitney,
Alcoa, Apple, NASA, US Navy and US Army
• Serve multiple horizontal markets: condition
based maintenance, structural health
monitoring, environmental monitoring and
test & measurement

High Value Asset Tracking System

Shock-Link
Monitors shock, temp, RH
Non-Volatile Display

WSDA-T100 Gateway
with GPS & SATCOM


The cloud makes it easier for users to
quickly connect with their data


Reducing out-of-the-box time and
improving user experience


Tiny Sensors, Big Data: Extracting Meaning with Wireless Sensor Networks and the Cloud

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (20)

Destaque

Destaque (20)

Semelhante a Tiny Sensors, Big Data: Extracting Meaning with Wireless Sensor Networks and the Cloud

Semelhante a Tiny Sensors, Big Data: Extracting Meaning with Wireless Sensor Networks and the Cloud (20)

Tiny Sensors, Big Data: Extracting Meaning with Wireless Sensor Networks and the Cloud