Group Projects 2013. Group November: Cycle path mapping with a custom hardware platform.

Duration: 5 mins 16 secs

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Description:	Group Projects 2013. Group November: Cycle path mapping with a custom hardware platform.


Created:	2013-03-11 12:08
Collection:	1B Group projects 2013
Publisher:	University of Cambridge
Copyright:	B.D. Jones
Language:	eng (English)
Keywords:	Group Project; November; Cycle path; Mapping;


Abstract:	The aim of this project is to produce a highly accurate map of the Cambridge cycle network including information about inclines, one way roads, restricted access. Since this will require more data than can be gathered using a simple GPS device or smartphone this project will have a custom hardware element based around the .NET Gadgeteer platform. The first part of the project will build a device to capture data such as GPS, accelerometer, compass, cadence, wheel rotation, heart rate etc, to produce a sample dataset representative of the Cambridge cycle network, as well as providing the cyclist with relevant data. The second part of the project will process and visualise the sample dataset. This will include removing erroneous data, fusing data streams and maps to improve accuracy and inferring cycle features from the data whilst keeping an emphasis on data accuracy. This information could be used to recommend cycle routes or diversions in real time, assist with finding a bike rack, or perhaps the addition of new cycle lanes. The resulting dataset should be open and accessible.

Abstract:

The aim of this project is to produce a highly accurate map of the Cambridge cycle network including information about inclines, one way roads, restricted access.
Since this will require more data than can be gathered using a simple GPS device or smartphone this project will have a custom hardware element based around the .NET Gadgeteer platform.
The first part of the project will build a device to capture data such as GPS, accelerometer, compass, cadence, wheel rotation, heart rate etc, to produce a sample dataset representative of the Cambridge cycle network, as well as providing the cyclist with relevant data.
The second part of the project will process and visualise the sample dataset. This will include removing erroneous data, fusing data streams and maps to improve accuracy and inferring cycle features from the data whilst keeping an emphasis on data accuracy. This information could be used to recommend cycle routes or diversions in real time, assist with finding a bike rack, or perhaps the addition of new cycle lanes. The resulting dataset should be open and accessible.

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