Human centric sensing by Android phones - IV
There are many mobile navigation applications on Google play and the Apple App Store that uses human centric sensing. These navigation apps are design for people that are more privileged than some others. It is estimated about eight to nine people in every 1000 people had an intellectual disability,...
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sg-ntu-dr.10356-592702023-03-03T20:26:24Z Human centric sensing by Android phones - IV Zhang, Ciping School of Computer Engineering Centre for Multimedia and Network Technology Luo Jun DRNTU::Engineering::Computer science and engineering There are many mobile navigation applications on Google play and the Apple App Store that uses human centric sensing. These navigation apps are design for people that are more privileged than some others. It is estimated about eight to nine people in every 1000 people had an intellectual disability, and there are more people who have mild intellectual disability (MID) than there are people with more severe disabilities. This project focuses on children suffering from MID with IQ level at the range of 50 to 70. They still go to work or school but with help provided. For those who travel alone, parents are often worrying for them and with proper training they could still lead a normal life. There is a need for an application to aid them in their daily life and ease the mind of their parents. EasyGo a mobile navigation application is specially created with MID student in mind. EasyGo focuses on the function design to aid MID student in their daily life preparing them for adulthood as well as easing their parents mind. In this project, Google play services library, Ajax, json are being used and 2 new algorithms where created. The first is for a proximity sensor detecting the user going out of range of the define route. The second is use to change the compass arrow to point to the destination instead of only north. SQLite and CSV are chosen to use for storing the route coordinates. The effectiveness of EasyGo is evaluated at the end of the development by Metta School Students who are suffering from MID. Bachelor of Engineering (Computer Science) 2014-04-28T09:29:11Z 2014-04-28T09:29:11Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59270 en Nanyang Technological University 41 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Zhang, Ciping Human centric sensing by Android phones - IV |
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There are many mobile navigation applications on Google play and the Apple App Store that uses human centric sensing. These navigation apps are design for people that are more privileged than some others. It is estimated about eight to nine people in every 1000 people had an intellectual disability, and there are more people who have mild intellectual disability (MID) than there are people with more severe disabilities.
This project focuses on children suffering from MID with IQ level at the range of 50 to 70. They still go to work or school but with help provided. For those who travel alone, parents are often worrying for them and with proper training they could still lead a normal life.
There is a need for an application to aid them in their daily life and ease the mind of their parents. EasyGo a mobile navigation application is specially created with MID student in mind. EasyGo focuses on the function design to aid MID student in their daily life preparing them for adulthood as well as easing their parents mind.
In this project, Google play services library, Ajax, json are being used and 2 new algorithms where created. The first is for a proximity sensor detecting the user going out of range of the define route. The second is use to change the compass arrow to point to the destination instead of only north. SQLite and CSV are chosen to use for storing the route coordinates.
The effectiveness of EasyGo is evaluated at the end of the development by Metta School Students who are suffering from MID. |
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School of Computer Engineering |
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School of Computer Engineering Zhang, Ciping |
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Zhang, Ciping |
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Human centric sensing by Android phones - IV |
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Human centric sensing by Android phones - IV |
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Human centric sensing by Android phones - IV |
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Human centric sensing by Android phones - IV |
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Human centric sensing by Android phones - IV |
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human centric sensing by android phones - iv |
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2014 |
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http://hdl.handle.net/10356/59270 |
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