TRAP@NCI

RFBase: Technical Report

Quinn, Niall (2017) RFBase: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.

[img]
Preview
PDF (Bachelor of Science)
Download (2MB) | Preview

Abstract

The aim of this project is to produce a highly functional marketing platform for racing drivers. The platform provides valuable functionality to the customer, and act as a catalyst to grow their social media following. The project will be provided using modern languages, frameworks and tooling. This platform includes a custom theme engine, which will allow the mobile application’s look and feel to be configured from the backend platform. The platform employs multi-tenancy on the backend - data is segmented by customer and surfaced to the customer’s personal mobile applications on the front end. The platform will be developed with security in mind. The data will be kept safe and confidential, and there will be no overspill of data between tenants.

RFBase is a marketing platform for modern race drivers. Gaining the marketing edge is more important than ever, with drivers fighting for sponsorship and race drives, getting the word out is a top priority. RFBase gives them a platform to deliver News, Driver Bio, Race Calendar, Social Streams and Push Notifications to their fanbase. I achieve this by supplying the driver with a login to the platform where they can generate all of their content. They will also get two white-labeled mobile applications, deployed to the iOS App Store and the Google Play Store. Drivers can take residency on the home screens of their most loyal fans, and use RFBase to deliver quality,
exclusive content.

Upon evaluation I found that this product does address the needs of many racing drivers. Drivers are very excited at the prospect of having their own app in the app store, and see a benefit to having this personal stream to broadcast to their fanbase. The theming engine was a big hit among all users - the ability to customise the look and feel of the applications on the fly being identified as a big selling point.

Item Type: Thesis (Undergraduate)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Bachelor of Science (Honours) in Computing
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 01 Nov 2017 14:46
Last Modified: 01 Nov 2017 14:46
URI: http://trap.ncirl.ie/id/eprint/2716

Actions (login required)

View Item View Item