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Real Time Location Systems
Automatic Identification and Tracking
© Jeffrey Dungen 2016
Purpose
© Jeffrey Dungen 2016
Is RTLS beneficial for my application?
What choices do I have among RTLS?
How do the different RTLS work?
What should I reasonably expect?
My Background
© Jeffrey Dungen 2016
Computer Engineer
RTLS, Geolocation & IoT startups since 2004
Applications from baggage to bike races...
DISCLOSURE
I’m currently co-founder and CEO of reelyActive, an IoT/RTLS/M2M startup
Motivation
© Jeffrey Dungen 2016
Dots on a Map
© Jeffrey Dungen 2016
Is this what I expect?
Is this what I need?
Is this even what James Bond needs?
He/She/It is
exactly here
RTLS for Humans
© Jeffrey Dungen 2016
“The nearest IV pump is in room 123A”
➔ Can the nurse find room 123A?
➔ Can the nurse find an IV pump in a room?
How should your RTLS effectively
assist humans?
RTLS for Computers
© Jeffrey Dungen 2016
“RFID and sensor technology enable computers to
observe, identify and understand the world—without
the limitations of human-entered data.” — Kevin Ashton
How do computers understand
identification & location?
Tech-First Approach
© Jeffrey Dungen 2016
1. What is technically feasible/appropriate?
2. Can my problem technically be solved with RTLS?
3. How do I deliver a solution?
In my experience, this is currently the approach which most
reliably leads to real solutions. Of course, I’m an engineer...
Technology
© Jeffrey Dungen 2016
A Typical RTLS
© Jeffrey Dungen 2016
Middleware
Sensor Sensor Sensor
Tag TagTag Tag TagTag Tag TagTag Mobile
Fixed
Infrastructure
Hosted
On-site
Identification
© Jeffrey Dungen 2016
Sensor
Tag
Passive RFID
Sensor
Tag
Active RFID
UHF
Infrared*
SHF
UHF
Ultrasound*
Energy sourced
from sensor
Energy sourced
from tag
*Not RF
*Generalisation
10m*
Frequency Band
© Jeffrey Dungen 2016
TagSensor Sensor
Water Wall
Absorption Reflection
2.45GHz is used by WiFi,
Bluetooth and to heat food...
Higher frequencies
reflect more → Multipath
Narrow vs. Ultra-wide
© Jeffrey Dungen 2016
Transmission
Duration
Bandwidth
Narrowband
Ultra-wideband
(UWB)
UWB transmissions are so short,
they overcome reflections that
affect the direct signal path.
Narrowband suffers what is
called “multipath fading”.
RSSI
© Jeffrey Dungen 2016
Received Signal Strength Indication
➔ Estimate distance to tag based on signal strength
➔ Ubiquitous sensor support
➔ Significantly affected by absorption and reflection
Tag Sensor
Distance
AoA
© Jeffrey Dungen 2016
Angle of Arrival
➔ Estimate angle to tag based on phase shift on antennae
➔ Requires multiple antennae per sensor
➔ May require specific tag transmission sequence
Tag
Sensor
Angle
TDoA
© Jeffrey Dungen 2016
Time (Difference) of Arrival
➔ Estimate (relative) distance to tag based on arrival time
➔ Requires multiple time-synchronised sensors
➔ May require significant computing in middleware
Tag SensorSensor
t1
t2
t2
- t1
= 10ns = Δ10ft
Fingerprinting
© Jeffrey Dungen 2016
Leverage what you actually get
➔ Calibrate based on actual sensor values (RSSI, etc.)
➔ Granularity based on number of points observed
➔ Changes in environment strongly impact results!!!
Sensor A
RSSI
A = 150
B = 100
RSSI
A = 120
B = 130
RSSI
A = 110
B = 160
Sensor B
Zone 1 Zone 2 Zone 3
Tech Summary
© Jeffrey Dungen 2016
1. Active RFID and UHF Passive RFID support RTLS
2. Frequency and environment affect performance
3. Various location techniques with tradeoffs
Configurations
© Jeffrey Dungen 2016
Checkpoint
© Jeffrey Dungen 2016
Sensors detect tags only
through checkpoints.
What if a tag enters/leaves via
another passage?
Detect passage
through here
Visibility
Detect presence
throughout
Sensors detect tags
throughout the facility.
Coverage overlaps.
Can coverage extend too far?
© Jeffrey Dungen 2016
Zone Location
© Jeffrey Dungen 2016
Tags are located to the
nearest zone.
Zone definitions must take into
account the technology
and sensor placement.
The tag is in
this zone
Precise Location
© Jeffrey Dungen 2016
Tags are located to
precise coordinates.
Requires AoA or TDoA for the
precision to meet reasonable
expectations.
The tag is
exactly here
Config Summary
© Jeffrey Dungen 2016
1. Checkpoints only? Or visibility throughout?
2. Zone location good enough? Precision required?
3. A combination of all of these may be ideal!
Practicalities
© Jeffrey Dungen 2016
Tags
© Jeffrey Dungen 2016
Options limited by budget and config.
➔ Passive may be only cost-effective high-volume option!
➔ Active RFID performance vs. battery life
➔ Proprietary Active RFID performance vs. vendor lock-in
➔ Flexibility of Bluetooth/WiFi BYOD vs. performance
➔ Radio compliance for the target geography?
Sensors
© Jeffrey Dungen 2016
Sensors need power & connectivity
➔ PoE offers both on a single cable
➔ Possible to get cable drops to the optimal locations?
➔ WiFi/Mesh backhaul offers convenience over reliability
➔ Is there a mains outlet at each optimal location?
➔ Intentional or unintentional tampering?
Middleware
© Jeffrey Dungen 2016
Last but definitely not least!
➔ Proprietary or open source?
➔ Vendor lock-in or alternatives?
➔ Who maintains and operates?
➔ Runs on-site and/or in the cloud?
➔ Total cost of ownership?
Practicalities Summary
© Jeffrey Dungen 2016
1. Tag selection may dictate the deployment!
2. Can I deploy the sensors as my needs dictate?
3. After all that, is there a middleware that fits the bill?
Examples
© Jeffrey Dungen 2016
Retail Inventory
© Jeffrey Dungen 2016
Back Store
Store
(Visibility)
Receiving
Fitting Rooms
➔ Every article of clothing has
UHF Passive RFID tag
➔ Visibility coverage in store
ensures articles on display
➔ Fitting rooms zone location
(requires radio shielding)
➔ Various middleware options
Hospital Staff & Equipment
© Jeffrey Dungen 2016
Room
(Zone)
➔ Every equipment has an
integrated BLE tag
➔ Staff use mobile app (BLE)
➔ AoA sensors for precision
tracking in Triage Ward
➔ Cost-effective BLE sensors
for visibility & room zones
➔ Bespoke middleware
Room
(Zone)
Room
(Zone)
Room
(Zone)
Room
(Zone)
Room
(Zone)
Triage
(Precision)
Courtyard
(Visibility)
WIP Tracking
© Jeffrey Dungen 2016
Machine
➔ Every employee has Active
RFID tag
➔ Every WIP job clipboard has
Active RFID tag
➔ Every machine has sensor
➔ Open source middleware
Machine
Machine
Who’s applying which process
to which job right now?
Examples Summary
© Jeffrey Dungen 2016
1. There’s no “one-size-fits-all” solution!
2. Each requires system integration and at least some
custom application development.
3. None of these required “dots on a map”!
Conclusions
© Jeffrey Dungen 2016
Review of Purpose
© Jeffrey Dungen 2016
Is RTLS beneficial for my application?
What choices do I have among RTLS?
How do the different RTLS work?
What should I reasonably expect?
Managing Expectations
© Jeffrey Dungen 2016
It’ll likely take longer than you think, especially if
process or behavioural changes are required!
BUT, a well-implemented RTLS will create
efficiencies, streamline operations and provide a
sustainable competitive advantage.
Thanks!
© Jeffrey Dungen 2016

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Real Time Location Systems (RTLS)

  • 1. Real Time Location Systems Automatic Identification and Tracking © Jeffrey Dungen 2016
  • 2. Purpose © Jeffrey Dungen 2016 Is RTLS beneficial for my application? What choices do I have among RTLS? How do the different RTLS work? What should I reasonably expect?
  • 3. My Background © Jeffrey Dungen 2016 Computer Engineer RTLS, Geolocation & IoT startups since 2004 Applications from baggage to bike races... DISCLOSURE I’m currently co-founder and CEO of reelyActive, an IoT/RTLS/M2M startup
  • 5. Dots on a Map © Jeffrey Dungen 2016 Is this what I expect? Is this what I need? Is this even what James Bond needs? He/She/It is exactly here
  • 6. RTLS for Humans © Jeffrey Dungen 2016 “The nearest IV pump is in room 123A” ➔ Can the nurse find room 123A? ➔ Can the nurse find an IV pump in a room? How should your RTLS effectively assist humans?
  • 7. RTLS for Computers © Jeffrey Dungen 2016 “RFID and sensor technology enable computers to observe, identify and understand the world—without the limitations of human-entered data.” — Kevin Ashton How do computers understand identification & location?
  • 8. Tech-First Approach © Jeffrey Dungen 2016 1. What is technically feasible/appropriate? 2. Can my problem technically be solved with RTLS? 3. How do I deliver a solution? In my experience, this is currently the approach which most reliably leads to real solutions. Of course, I’m an engineer...
  • 10. A Typical RTLS © Jeffrey Dungen 2016 Middleware Sensor Sensor Sensor Tag TagTag Tag TagTag Tag TagTag Mobile Fixed Infrastructure Hosted On-site
  • 11. Identification © Jeffrey Dungen 2016 Sensor Tag Passive RFID Sensor Tag Active RFID UHF Infrared* SHF UHF Ultrasound* Energy sourced from sensor Energy sourced from tag *Not RF *Generalisation 10m*
  • 12. Frequency Band © Jeffrey Dungen 2016 TagSensor Sensor Water Wall Absorption Reflection 2.45GHz is used by WiFi, Bluetooth and to heat food... Higher frequencies reflect more → Multipath
  • 13. Narrow vs. Ultra-wide © Jeffrey Dungen 2016 Transmission Duration Bandwidth Narrowband Ultra-wideband (UWB) UWB transmissions are so short, they overcome reflections that affect the direct signal path. Narrowband suffers what is called “multipath fading”.
  • 14. RSSI © Jeffrey Dungen 2016 Received Signal Strength Indication ➔ Estimate distance to tag based on signal strength ➔ Ubiquitous sensor support ➔ Significantly affected by absorption and reflection Tag Sensor Distance
  • 15. AoA © Jeffrey Dungen 2016 Angle of Arrival ➔ Estimate angle to tag based on phase shift on antennae ➔ Requires multiple antennae per sensor ➔ May require specific tag transmission sequence Tag Sensor Angle
  • 16. TDoA © Jeffrey Dungen 2016 Time (Difference) of Arrival ➔ Estimate (relative) distance to tag based on arrival time ➔ Requires multiple time-synchronised sensors ➔ May require significant computing in middleware Tag SensorSensor t1 t2 t2 - t1 = 10ns = Δ10ft
  • 17. Fingerprinting © Jeffrey Dungen 2016 Leverage what you actually get ➔ Calibrate based on actual sensor values (RSSI, etc.) ➔ Granularity based on number of points observed ➔ Changes in environment strongly impact results!!! Sensor A RSSI A = 150 B = 100 RSSI A = 120 B = 130 RSSI A = 110 B = 160 Sensor B Zone 1 Zone 2 Zone 3
  • 18. Tech Summary © Jeffrey Dungen 2016 1. Active RFID and UHF Passive RFID support RTLS 2. Frequency and environment affect performance 3. Various location techniques with tradeoffs
  • 20. Checkpoint © Jeffrey Dungen 2016 Sensors detect tags only through checkpoints. What if a tag enters/leaves via another passage? Detect passage through here
  • 21. Visibility Detect presence throughout Sensors detect tags throughout the facility. Coverage overlaps. Can coverage extend too far? © Jeffrey Dungen 2016
  • 22. Zone Location © Jeffrey Dungen 2016 Tags are located to the nearest zone. Zone definitions must take into account the technology and sensor placement. The tag is in this zone
  • 23. Precise Location © Jeffrey Dungen 2016 Tags are located to precise coordinates. Requires AoA or TDoA for the precision to meet reasonable expectations. The tag is exactly here
  • 24. Config Summary © Jeffrey Dungen 2016 1. Checkpoints only? Or visibility throughout? 2. Zone location good enough? Precision required? 3. A combination of all of these may be ideal!
  • 26. Tags © Jeffrey Dungen 2016 Options limited by budget and config. ➔ Passive may be only cost-effective high-volume option! ➔ Active RFID performance vs. battery life ➔ Proprietary Active RFID performance vs. vendor lock-in ➔ Flexibility of Bluetooth/WiFi BYOD vs. performance ➔ Radio compliance for the target geography?
  • 27. Sensors © Jeffrey Dungen 2016 Sensors need power & connectivity ➔ PoE offers both on a single cable ➔ Possible to get cable drops to the optimal locations? ➔ WiFi/Mesh backhaul offers convenience over reliability ➔ Is there a mains outlet at each optimal location? ➔ Intentional or unintentional tampering?
  • 28. Middleware © Jeffrey Dungen 2016 Last but definitely not least! ➔ Proprietary or open source? ➔ Vendor lock-in or alternatives? ➔ Who maintains and operates? ➔ Runs on-site and/or in the cloud? ➔ Total cost of ownership?
  • 29. Practicalities Summary © Jeffrey Dungen 2016 1. Tag selection may dictate the deployment! 2. Can I deploy the sensors as my needs dictate? 3. After all that, is there a middleware that fits the bill?
  • 31. Retail Inventory © Jeffrey Dungen 2016 Back Store Store (Visibility) Receiving Fitting Rooms ➔ Every article of clothing has UHF Passive RFID tag ➔ Visibility coverage in store ensures articles on display ➔ Fitting rooms zone location (requires radio shielding) ➔ Various middleware options
  • 32. Hospital Staff & Equipment © Jeffrey Dungen 2016 Room (Zone) ➔ Every equipment has an integrated BLE tag ➔ Staff use mobile app (BLE) ➔ AoA sensors for precision tracking in Triage Ward ➔ Cost-effective BLE sensors for visibility & room zones ➔ Bespoke middleware Room (Zone) Room (Zone) Room (Zone) Room (Zone) Room (Zone) Triage (Precision) Courtyard (Visibility)
  • 33. WIP Tracking © Jeffrey Dungen 2016 Machine ➔ Every employee has Active RFID tag ➔ Every WIP job clipboard has Active RFID tag ➔ Every machine has sensor ➔ Open source middleware Machine Machine Who’s applying which process to which job right now?
  • 34. Examples Summary © Jeffrey Dungen 2016 1. There’s no “one-size-fits-all” solution! 2. Each requires system integration and at least some custom application development. 3. None of these required “dots on a map”!
  • 36. Review of Purpose © Jeffrey Dungen 2016 Is RTLS beneficial for my application? What choices do I have among RTLS? How do the different RTLS work? What should I reasonably expect?
  • 37. Managing Expectations © Jeffrey Dungen 2016 It’ll likely take longer than you think, especially if process or behavioural changes are required! BUT, a well-implemented RTLS will create efficiencies, streamline operations and provide a sustainable competitive advantage.