Final Year Project LYU0301

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Final Year ProjectLYU0301

• Location-Based Services Using GSM Cell
  Information over Symbian OS

Mok Ming Fai CEG mfmok1_at_cse Lee Kwok Chau CEG
leekc1_at_cse
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Agenda

• Symbian OS
• Location-based services (LBS)
• Current GSM Positioning Methods
• Using GSM cell information in 2D space and 1D
  path
• MTR Travaller
• Future Work

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The Symbian OS

• Standard operating system for data-enabled mobile
  devices
• 32-bit, little-endian operating system working
  with ARM architecture chips with v4 instruction
  set or higher

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Location-Based Services (LBS)

• Services are provided based on users location
  under different wireless networks
• LBS is applicable in various fields
• Different issues have to be considered
• Each of them requires different accuracy and
  latency

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GSM Positioning Methods

• Region-based
• Cell Information (CI)
• Point-based
• Time of Arrival (TOA)
• Angle of Arrival (AOA)
• Enhanced Observed Time Difference (E-OTD)
• Assisted GPS (A-GPS)

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Point-based GSM Positioning Methods

• TOA (200m - 10km)
• E-OTD (50m - 100m)

• AOA (gtgt150m)
• A-GPS (10m - 50m)

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Motivation

• Advanced positioning methods require
• extra cost to existing network / synchronization
  between base stations
• special hardware to end users
• telco-dependent
• Not all LBSs need very accurate location
  information
• GSM cell information (e.g. cell ID) is available
  in ordinary GSM handset
• Symbian phone offers programming capability for
  general developers
• Location estimation by GSM cell ID is adopted in
  our project

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Overview of GSM Cell ID Location Estimation

• Each base station has unique location ID and cell
  ID
• Main idea each base station can somehow provide
  certain information about a particular location
• Advantages
• simple implementation, only current registered
  cell is required
• applicable on ordinary GSM phone
• without any support from telco

Location 50 Cell ID 4
Location 50 Cell ID 2
Location 50 Cell ID 3
Location 50 Cell ID 1
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GSM Cell Change Event

• Received signal strength from current registered
  cell is weaker than another, so cell change
  occurs
• Consequences
• More information provided
• More reliable in detecting boundary

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Location-based Services in 2D Space

• Initiatives
• To locate the approximate location of a mobile
  phone using a program that run on Symbian OS
• Principle
• Determining GSM cells coverage and their
  distribution
• Plot a cell ID-to-location map
• Locate current position of a mobile device

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Data Collection Method

• Collected location ID and cell ID pairs for two
  telcos in the CU campus.
• Data Collection method
• Static Method for SmarTone
• Cell Change Method for Peoples

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Principle of the Two Data Collection Methods

• Static Method
• Wait for a sufficiently long period of time at a
  specific point in the 2D map to see the strength
  and stability of a cell strength.
• Determine the location ID and cell ID of that
  specific location after observing for a period of
  time

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Principle of the Two Data Collection Methods

• Cell Change Method
• Walk around the campus and find the boundaries
  of different cells
• When cell change occurs we note down the change
  and try to find out the boundaries of the cells

location where cell change event is detected
Cell boundaries
Cell C
B-gtC
A-gtB
Cell A
Cell B
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Advantages and Disadvantages of the Two Methods
Static Method Cell Change Method
Advantages Results very accurate at those selected points Can figure out the boundaries of different cells in the area
Advantages Experiments only done on those selected points Fast, no need to wait for a long time to get the result
Disadvantages Takes a longer time Boundaries detected are regions instead of sharp lines
Disadvantages Cannot figure out the distribution of cells clearly without dense selected points Have to walk through the whole area several times
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Experimental Results
For Peoples
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Experimental Results
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Experimental Results
For SmarTone
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Experimental Results
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Conclusion of the Experiment

• Potential difficulties in 2D Space
• ID-to-location map drawn not accurate enough
• Cannot locate the location of a mobile device to
  an acceptable accuracy owing to the large size of
  cells
• Hierarchy of cells make it even harder to locate
  our current position

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Using GSM Cell IDs in 1D Space

• A set of multiple cell change events can indicate
  a path

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Problem of Using GSM Cell IDs in 1D Space

• The mapping of cell change event set and path is
  one-to-many
• Apply this method on fixed path

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MTR Traveller for Stations in Subway

• Apply on traffic route
• MTR Traveller detect station arrival
• Initial observation
• Between two stations in subway, there is exactly
  one cell change
• This event can tell user that he / she is going
  from one station to another station

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MTR Traveller for Stations in Open Area

• KCR stations in open area
• Many cells are involved in between two stations
• A station platform may also be covered by
  multiple cells
• Group the cells into station cells (pure cell
  ID) and transition pairs (cell changes)

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Operation of MTR Traveller

• Transition pair gt on the way between S1 and S2
• Station cell gt in the station platform

Cell ID O S1, O gt in Station 1
Cell ID O?B S1, B gt in Station 1
Cell ID B?P S1, S2, B, P gt on the way of S1?S2
Cell ID P?G S1, S2, P, G gt on the way of S1?S2
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MTR Cell ID Data

• Peoples

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MTR Cell ID Data

• SmarTone

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MTR Cell ID Data

• Sunday

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KCR Cell ID Data

• Peoples

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KCR Cell ID Data

• SmarTone

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Estimating the Accuracy of Proposed Method

• Record the time difference at which the cell
  change occurs and at the moment that the train
  actually arrives the destination station
• Convert the error range in time to distance by
  assuming constant velocity in that range
• Result 30m - 300m, comparable to E-OTD

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Demonstration

• Videos in actual stations

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Evolution of Our Positioning Methods
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Automatic Cell Data Collection

• Collection of cell data was done manually in the
  past
• Automatic cell data collection tool is required
  for regular update
• Cell Snap

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Contribution of Work

• Enhancing pure cell ID location estimation by
  considering cell change events
• MTR Traveller provides different application
  opportunities, such as
• Notification
• Information providing
• Cell Snap allows automatic cell data collection

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Future Work

• Improvement on MTR Traveller
• Personalization
• Informative
• User interface
• Distributed intelligence (SMS / GPRS)
• Generic middleware / library for developers
• Other applications
• Bus / tram route
• Detection of car speed detectors

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Conclusion

• GSM cell provides location-related information,
  but not accurate and reliable enough
• Those information can be obtained through Symbian
  phone
• The method was enhanced by using cell change
  events
• Difficulties were encountered in 2D space
• The proposed method was also applied to 1D path
  MTR Traveller
• Automatic cell data collection by Cell Snap

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QA Section

• Thank you very much!