Smart receipt system - front-end development of cross-platform mobile application
Financial planning is an essential skill to have, nevertheless, it is not an easy skill to master. With the aim of aiding users in their financial planning and tracking their physical receipts, the Smart Receipt System (SRS) was developed. The SRS comprises of several subsystems, including a me...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/73902 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Financial planning is an essential skill to have, nevertheless, it is not an easy skill to master.
With the aim of aiding users in their financial planning and tracking their physical receipts,
the Smart Receipt System (SRS) was developed.
The SRS comprises of several subsystems, including a merchant web application
dashboard, front-end and back-end development of a cross-platform mobile application
that works on iOS and Android operating systems.
This project was a sub-system of the SRS and it involved the front-end development of
the SRS mobile application and the back-end development of incorporating data analytics
into the SRS mobile application.
The purpose of this project was to provide a user-friendly interface to users regardless
whether the application will be used on iOS or Android platform. Additionally, to provide
a means for user to visualize their spending through the mobile dashboard and thus
improve their financial planning.
The SRS mobile application was created using a relatively new, yet popular framework
developed by Facebook—React Native. The application involved 3 types of data
analytics—descriptive, diagnostic and predictive analytics. The data processing for these
analytics was done using the Python language. Additionally, the Markov Chaining Model
was used for predictive analytics in this project.
The SRS mobile application was deployed and tested within NTU premises, and survey
results were collected from students. The survey showed positive results that proved the
completion and success of the project.
Ostensibly, further improvements could be made to this project. These include the
incorporation of perspective cropping and prescriptive analytics.
This project was divided into five main phases: Planning, Requirements Analysis, Design,
Implementation and Testing and the documentations involved in each phase was included
in this report. |
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