Competitor Location Prediction for Real

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Dean of Postgraduate Research
Vice-Chancellor’s Office
Extension: 7285
Email:
[email protected]
Summer Research Scholarship Scheme
2015-2016
Project Application Form
Please complete and submit the application form as a WORD document and send to
[email protected]
The Project
Title of Project (max 30 words):
Competitor Location Prediction for Real-time Satellite Tracking of Outdoor Sport Events
Project Leader(s):
Michael Plank
Host Department/Organization:
School of Mathematics and Statistics
Other persons involved in this topic/activity:
(List other significant members involved along with their affiliation to the research project.)
Name
Elena Moltchnova
Shane Davidson
Affiliation to project
Co-supervisor
Contact at sponsoring organisation Maprogress
Brief outline of project
Describe the proposed research project – maximum of 400 words (box will expand as you type).
Note that this information will be published on the web in order to attract student applicants and therefore be
mindful of any Intellectual Property issues
Maprogress provides real-time satellite tracking to outdoor sport events like the Coast to Coast.
Each personal tracker worn by a competitor, with a clear view of the sky, sends its position and time
to a satellite overhead every few minutes. That signal bounces around ending up as a marker on a
Google Map alongside other competitors’ markers. Customers expect markers to move
continuously. If an event is travelling along a pre-defined route, we have the opportunity to predict
where they are now. For new events we can use a very basic average speed only prediction model
(for an example of this in action click on "Predicted Mode" at http://coast-to-coast1
demo.maprogress.com). For previously tracked events, we would like to use the past data to
determine current locations more accurately, but also to predict where competitors will be at a
future point in time. This project will be about developing a model for predicting current and future
positions using this past data.
If the project involves work away from the University campus (e.g., at fieldwork sites) please detail all locations.
N/A
If the student be required to work outside of normal university hours (8am-5pm) please provide details
N/A
Benefits student will gain from involvement in the project
Describe the research experience and skills that the student will acquire through involvement in this research project –
maximum of 100 words.
The student will gain experience in applying the mathematical and statistical methods that they have studied
to a industry-led problem and working with real data sets. This will give them a wider appreciation of the
context of their field of study. They will gain marketable skills in communicating their ideas and results, both
verbally and in writing. They will also learn how to work and communicate effectively with industry partners.
Specific student requirements
Please provide details of all requirements you have for the student to work on this project – for example, if specific
courses/experience are necessary.
This project will suit a student with an interest in handling spatial data sets. Good programming
skills (e.g. in Matlab or R) are essential. Knowledge of data mining and multivariate modelling
methods (e.g. STAT315, STAT318, STAT319) is desirable though prior study of these courses in
not essential.
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