GTNavi System Hyojoon Kim, Sang Min Shim, Kai Wang, Pingping He CS8803 AIA, Spring 2009

 Introduction  Previous / Related Work  New Features  Technology  Demo  Challenges  Evaluation  Future Work  Acknowledgement  Q & A Outline

 Do you know all existing buildings in Georgia Tech?  Do you memorize addresses of all of them?  Do you know all the exact locations, and how to get there?  What about visitors and guests to the campus? Introduction Lost in Campus..

 Navigation application within GT campus  Not driving directions, but walking directions  Mobility – developed in Android  Additional features  Special instructions at special nodes (intersection points)  Friend Finder  New shortest path algorithm, etc That’s why we need.. GTNavi System Introduction

 Static start point to end point  Driving direction only – tried walking, incomplete  Mostly need to know exact address Google Maps Driving Direction Service Previous and Related Work

 Web service – no mobility  Simple line from start to end point - no direction explanation  Not a real-time navigator GT walking path direction service Previous and Related Work

1. Mobility  Mobile, handheld navigation device  No connection needed – easy deployment, high usability  Install, and you’re ready to go! 2. Walking path  People walking around campus  Guest and visitors, as well as you! New Features

3. Flexibility  KML data – easy to update and deploy  Other campuses (it they have their own KML data) 4. Real-time Direction Service and More!  Left or right turn instructions  Images pops up as you approach New Features

5. Wiki Page  Wiki page – user shares data about path  contribute to the system! 6. Friend Finder  Get the geo. Location of friend by SMS  The location will be set as destination  Shows the direction path to get to your friend! New Features

1. KML data and Geo Points  KML file is a way of expressing geological points  XML style Technology

2. Drawing on Google map  Extends Overlay Class Technology

3. Database System  Data storage and management by SQLite Technology

4. Finding the shortest path  Dijkstra's algorithm  Floyd–Warshall algorithm  Complexity consideration Technology

5. Wiki page  Why do we need it?  How do we want it to be? Technology

1. Memory shortage  Android has limited memory  Dealing with memory efficiently 2. Runtime Finding path  Dijkstra O(|V|2+|E|)  Floyd O(length of the path) 3. Google Android G1  No sufficient document  Getting used to the development environment Challenges

 KML Geo. Point data  Android SDK, Android Emulator  Google Map API  MySQL-Lite database  PHP to construct wikipage  DDMS to debug Resource

Evaluation

Evaluation

1. Better wiki page  User picking intermediate nodes 2. Faster performance  especially when showing all paths and buildings 3. Scalability  Georgia Tech campus is relatively small Future Work

 Professor Ling Liu  Matt Weber  Myungcheol Doo (congrats!) Acknowledgements

Q & A