Our presentation for ruSMART-2013. Many of modern location-based services are often based on an area or place as opposed to an accurate determination of the precise location. Geo-fencing approach is based on the observation that users move from one place to another and then stay at that place for a while. These places can be, for example, commercial properties, homes, office centers and so on. As per geo-fencing approach they could be described (defined) as some geographic areas bounded by polygons. It assumes users simply move from fence to fence and stay inside fences for a while. In this article we replace geo-based boundaries with network proximity rules. This new approach let us effectively deploy indoor location based services and provide a significant energy saving for mobile devices comparing with the traditional methods.

1. Geofence and Network
Proximity
Dmitry Namiot Lomonosov Moscow State University
dnamiot@gmail.com
Manfred Sneps-Sneppe ZNIIS, M2M Competence Center
manfreds.sneps@gmail.com
RUSMART 2013

2. • Many of modern location-based services are often
based on an area or place as opposed to an
accurate determination of the precise location.
• Geo-fencing approach is based on the observation
that users move from one place to another and then
stay at that place for a while.
• As per geo-fencing approach they could be
described (defined) as some geographic areas
bounded by polygons.
• In this article we replace geo-based boundaries
with network proximity rules.
About

3. Contents
Introduction
Passive Wi-Fi monitoring
Cloud Messaging
Local area messaging mashup
Conclusion

4. Passive Wi-Fi monitoring
• Wi-Fi probe request
• Client (even not
connected) can send
requests to AP
• AP can analyze
requests
• We can collect MAC-
addresses for clients

5. Advantages and disadvantages
for passive monitoring
• It does not require special mobile applications
• For mobile users it works automatically and
transparently
• It is anonymous monitoring. MAC address is
used for re-identification only. It could be
replaced with some hash-code (privacy)
• It is not 100% reliable. There is no warranty
that Wi-Fi client will send probe request. Our
own experiments and references show 70%-80%
detection rate.

6. Passive monitoring examples
Navizon

7. Passive monitoring examples.
Cisco MSE

8. Passive monitoring examples.
Libelium

9. Examples: visits per hour

10. Examples: devices

11. Cloud Messaging
• Cloud infrastructure
from vendor
• Google, Apple,
Microsoft, Nokia –
own cloud based
infrastructures for
notifications
• Google message: 4
Kb payload delivery

12. Google Cloud Messages

13. Key moments for Cloud Messaging
• Application registers with Cloud Messaging
• Application provides a key from Cloud
Messaging server (subscribes) to the particular
application (Sender)
• Sender saves keys and uses them later for
delivering notifications
• Key moment – subscription is activated from the
mobile application on the particular phone.

14. Spotique mashup
• Let us extend the subscription process
• Mobile application (mobile phone, actually)
will provide a key for notification and MAC-
address for identification
• Sender can compare saved MAC-
addresses with the MAC-addresses,
collected by the passive monitoring
• Key idea: get subscribers who are nearby
at this moment

15. Spotique mashup - 2
• Server-side based schema for our SpotEx
model
• Sender can deliver notifications to those,
who are nearby only.
• It is real-time detection
• MAC-address is used for the re-
identification only. So, it could be replaced
with some hash-code (privacy)

16. Use cases
• Proximity marketing
• Deliver local area messages in retail
• Hyper-local news delivery in campuses.
Tested in Lomonosov Moscow State
University
• Smart Cities information delivery

17. Conclusion
• A new mashup based on passive Wi-Fi monitoring forA new mashup based on passive Wi-Fi monitoring for
mobile devices and cloud based notifications.mobile devices and cloud based notifications.
• Passive monitoring uses probe requests from Wi-FiPassive monitoring uses probe requests from Wi-Fi
specifications for detecting nearby clients.specifications for detecting nearby clients.
• Notification module uses cloud messaging (pushNotification module uses cloud messaging (push
notifications) from mobile operational systems.notifications) from mobile operational systems.
• This application does not publish location info in theThis application does not publish location info in the
social network (it is not a check-in).social network (it is not a check-in).
• Custom messages will target online subscribers inCustom messages will target online subscribers in
the nearby area only.the nearby area only.

18. About us
International team: Russia - LatviaInternational team: Russia - Latvia ((Moscow –Moscow –
Riga – VentspilsRiga – Ventspils).). Big history of developingBig history of developing
innovative telecom and software services,innovative telecom and software services,
international contests awardsinternational contests awards
Research areas are:Research areas are:
open API for telecom,open API for telecom,
web access for telecom data,web access for telecom data,
Smart Cities,Smart Cities,
M2M applications, context-aware computingM2M applications, context-aware computing..