Transcript [Thomas Carson](slides)


More Accurate Bus Prediction
› Allows Passengers to find alternate forms of
transportation
Do this with energy efficiency in mind
 Don’t use any high level permissions

Microphone – Record Sound
 Cell Signal – Determine Location
 Accelerometer - Determine Bus or Train

Query User – Looks for Bus arrival time by
indicating bus route and stop
 Sharing User – Contributes mobile sensing
information to the backend server

› Information includes – a collected cell sequence
from nearby cell towers, sound and
accelerometer data to make sure the user is on
a bus

Backend Server – Processes data from
sharing users and give information to
querying users

Maintains a database of sequences for
cell tower IDs for the different Bus routes

Sound detection

Accelerometer Readings
Sequence Matching
 After running an
Algorithm the Server
determines which
route has the best
score and that determines what bus the
sharing user is on


After all data is uploaded
and each bus is
determined where it is
Any querying user will
be able to get data on
where the bus is and
approximate arrival time.

No Users on a Bus
› Causes bus times to be reported wrong

Overlapped Routes
› The Server will sometimes misinterpret a route