1. 8/20/2013 Peer Consulting Group 1
CIO Roundtable
August 8, 2013
Jim Sutter - PeerGroup

2. The Internet of Things refers to uniquely identifiable
objects and their virtual representation in an Internet-
like structure.
‘The Internet of Things’ is a concept originally coined and
introduced by MIT, Auto-ID Center and intimately linked to
RFID and electronic product code (EPC).
If all objects and people in daily life were equipped with
identifiers, they could be managed and inventoried by
computers. Tagging of things may be achieved through
such technologies as near field communication, barcodes,
QR codes and digital watermarking.
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4.  "A billion people interacting with a million e-
businesses, with a trillion intelligent devices
interconnected“ (Lou Gerstner, CEO IBM, 1995)
 By 2015 there will be 1 trillion sensors linking
the physical and digital worlds merging to
become an “Internet of Things”
 list of applications is limited only by our imagination
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7. Internet of Things - at its most basic
level…
Interrogator /
Gate way
device
Interrogator /
Gate way
device
Host
Information
Management
System
Host
Information
Management
System
Actuators
Actuators
Wider area
communications
and Networks
Application commands
and responses
Physical
Interface Zone
Internet +
Passive RFID data
carriers and UID
Sensors
Sensors
Limit
Switches
Actuators
Communications
Zone
Display, Monitor,
Initiation Zone

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i.e., IP6

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Figure 2.

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14.  Passive UHF
 CPG Supply Chain Apps
 EPC Global Gen 2
 ISO 96 bits
 SGTIN vs. UPC 14
 1SYNC
 NFC investments
 Improved Antenna technology
 Connected via IP to the WWW (IOT)
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Figure 5.

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Surveillance applications, alarms,
object / people tracking [14]
Fleet management, emission control, toll payment,
road safety [95]
e-Health, and personal security
Smart Metering and Grid [34]
such as oil, water, electricity, heat, and others
Production chain monitoring and automation
Example Verticals
[Millions of objects by 2014 – Indicative example]

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Freight supply and distribution monitoring,
Vending Machines
Home / building / campus automation
Example Verticals
Multitude of new M2M applications based on
standardized Service Capabilities and APIs
[Ericsson CEO vision of 50 Billion
Connected Objects by 2020]
…

18. © Yacht Watchman International 2008
We monitor boats
while owners are
away!
The average boat owner uses their vessel only
17 times per year.

19. © Yacht Watchman International 2008
 Boat owners Love their Boats
 Many suffer from Narcolepsy
 80% of Boats that sink......... sink at the
dock!

20. © Yacht Watchman International 2008
Home Alone
Can you safely leave your boat unattended?
“Boats have a way of sinking
when no one is watching.
One way to beat this fear is
to hire a boat-sitter”
Yachting magazine, November, 1998
JAY COYLE

21. © Yacht Watchman International 2008
Boaters’ Concerns
• Water
• Electrical
• Smoke
• Intrusion
• Location

22. © Yacht Watchman International 2008
Around the Clock Monitoring
All Wireless Technology
Local or Worldwide Coverage
You are in Control 24/7
Geofence and Route Control

23. © Yacht Watchman International 2008

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28.  Alerts – Boat example, process industry,
security -
 Avoid significant, costly incidents
 Predictive Maintenance – smarter intervals -
 Save wear and tear, optimize consumables
 Monitoring – agricultural aps, production
sequencing -
 Better yields, fewer outages
 Analysis – confirm or improve maintenance
intervals, lead times, dosages, recipes, etc.
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29.  IOT or M2M solutions today collect all kinds of
information, from the temperature and GPS
coordinates of a refrigerated container to the
vital data of a herd of cows, and data quantities
are growing constantly as the technology
becomes increasingly widespread. So M2M is
one of the drivers of the global increase in data
quantities – the Big Data trend.
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So far, data retrieval by M2M applications has for the most part been limited to
individual values.
Doctors, for example, monitor patients’ blood glucose levels that are measured,
relayed by mobile telephony and archived, but extensive information can only be
gained from analyzing many different parameters.
Which data is analyzed is one question; the other is when it is analyzed.
Retrospective data analysis is often insufficient to identify relevant patterns early
enough.
To do that, you need to look at data streams in real time,
and that is where the real potential lies. Equipped with
machine learning algorithms, M2M applications of this kind
can even look into the future. They recognize problems in
production processes before they even arise.

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Thanks for Listening…..
www.peergroup.net