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TechHelper: Technical Report

Butler, Michael (2023) TechHelper: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.

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The TechHelper app uses image-recognition software such as Teachable Machine and TensorFlow Lite to identify and classify everyday household technology items for users that are unfamiliar with them. The user can then add these items into a shopping list and search for nearby technology stores using the GoogleMaps API integrated in the app.

This application is directly tailored towards those who are not familiar with any household technology items such as the different types of USBs or an ethernet cable. As the app is for these types of people, ease-of-use is paramount as it is unlikely they will be able to navigate a complicated app if they cannot recognise common tech items.

As the industry is constantly evolving and new household technology is being introduced it is important that the items that the app can recognise can also be updated. This can easily be done by updating the TensorFlowLite model.

In summary, TechHelper uses innovative technology that can aid those in need, such as older people who are living alone, to replace faulty cables. As an example, the application would be a valuable investment for a grandparent living alone.

This report will cover the function, requirements, resources used and designing of said app.

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
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: School of Computing > Bachelor of Science (Honours) in Computing
Depositing User: Tamara Malone
Date Deposited: 23 Aug 2023 14:05
Last Modified: 23 Aug 2023 14:05

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