Hack PSU 2017 Capital One ATM Interface with facial recognition
##Inspiration Slide Master is a version of a web slide player that reads lecture slides from a JSON file. It is mainly composed of a single iframe, the slide viewer onto which content is injected and managed, a notes section that allows notes to be created for each slide, and a display section that displays the added notes. Slide Master has a very friendly user interface and includes features such as specialized notes for each individual slide, auto note saving feature, audio for each individual slide, and fullscreen mode.
Slide Master is primarly a collection of 4 sections the slide viewer, notes section, display section, and slide master buttons. The client side was built with bootstrap for great visuals and textillateJS for eye catching animations. The server side was built with NodeJS, ExpressJS, and a json file store. ExpressJS is used for the web application framework, and the JSON file store is used for data storage. AJAX was used for interaction between the client side and server side. A lecture object is being passed back and forth from the client and server and then saved onto a json file store.
ATM.go was built using facial recognition, java android app, a web server, android studio.
A challenge we ran into was the verification of identity utilizing the ATM cameras. This issue included difficulty haulting the tracker as well as transferring the picture to our server. Another challenge was unfamiliarity with the necessary systems and programs required to make this project perform properly, such as Android Studio and JavaScript. We were also unsure how to maintain appropriate security measures as we were removing the use of a debit/credit card.
We are proud of the fact we were able to solve a problem that affects a high number of people. Banking is already moving more towards the technology sector every day with online banking and e-checks. It only seems reasonable that this movement should not be stagnant in regards to withdrawals and deposits- which are a large part of the banking experience. Another accomplishment we are proud of is our ability to implement facial recognition into the system, which is a technology our group was not familiar with.
We learned to be adaptable when dealing with systems we are not familiar with. This includes the use of Android Studio, and also the use of facial recognition. Our application would not have been possible if group members were unwilling or unable to complete tasks that they did not have previous experience with.
The future for this app is to be provided inside of banks, which will also eliminate time spent in lines. The integrations of consoles within the banks that act similarly to ATMs will ease the process of banking. While tellers can still be available to answer questions and solve problems unable to be solved by the machine, the consoles can instead do many of the routine tasks that consume much of current teller's work days.
Capital One, JetBrains
- Android-studio
- Java
- Javascript
- NodeJS
- ExpressJS
- HTML
- CSS
- XML
- Cloud9
| Hozaifa Abdalla | Daniel Lopez | Brandon Bench | Manan Patel | Fernando Carrillo | Morgan Atterholt | Aidan Chaviatti |
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github.com/abdallahozaifa |
github.com/dalofeco |
github.com/BrandonBench |
github.com/MananPatel |
github.com/fernando |
github.com/MorganAtterholt |
github.com/AidanChaviatti |