NoQ

An optimised time-scheduling application to prebook TSA slots to enable airlines & airports deliver travelers a no-hassle, Covid-safe, flying experience

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NoQ Terminal5 Transportation Team #5

Overview

Recent pandemic has impacted the air transportation business and traveling is perceived as a risk-factor.

The security clearance processes at airports are tedious, confusing, and generally have long wait times during peak hours. The goal of this project is to provide an effective solution addressing this issue.

"NoQ" allows users to pre-book and reserve their security slots online. It eliminates security queue times and eases the overall process for both the passengers and the TSA agents.

Partnering with airports & airlines establishes a solid go-to market strategy which provides passengers a smooth, hassle-free on-boarding process.

Team Members

Ashik Devakumar (Project Manager, Graduate Mechanical@ PFW) Ashik was responsible for scheduling all internal and external meetings. He created memos of each meeting and ran weekly planning sessions where the team agreed on a set of tasks for the week. Ashik also contributed to building revenue and business models and collaborated with the rest of the team to create this document.

Michael Hall (Business Development, Junior Mechanical @Rose-Hulman ) Michael put together our online go-to-market strategy with some help from our GoSquad coach. Michael ran our customer discovery process, conducting interviews with potential customers in the last 2 weeks. He also helped with the environmental analysis, business models, and revenue models.

RaviTeja Jorigay (UX Designer, Graduate Human-Computer Interaction @ IUPUI) RaviTeja helped in understanding the customer segment and created the persons, Empathy Maps, and Business models. He collectively worked with his squad members to develop a 3-year Revenue projection model. Ravi also helped the Pro squad by contributing his knowledge in prototyping and designed the UI’s of the screens.

Sumadhuri Damerla (Software Developer, Graduate Computer Science @ PFW) developed the database architecture and build the backend of our product. She was responsible for integrating the frontend and backend of the application as well as maintaining the git repository, deploying the app on Heroku server. She also worked on making the product demo presentation

Merouane Baoch (Software Engineer, Sophomore @ Ivy Tech College ) Merouane helped in developing the frontend, CSS and worked on the schematic representation of the application. He also contributed project planning ideas to the GoSquad.

Dhruvin Patel (Software Engineer, Senior Computer Science @ IUPUI) Developed front end architecture as well as an integrated front end and back end codes of the application. He Created UI design using React.js, and Bootstrap. Maintain the data flow using react-redux.

How did we decide on this customer segment, problem, and solution?

Observational Research

We studied the different problems at Indianapolis airport due to COVID-19.

Interviews

We interviewed TSA personnel to understand their hardships they are facing to maintain and regulate social distancing in long queues at the airport. We then interviewed air travel passengers to discover their pain points and turned them into insights.

System models

We organized this information into different process maps to better understand the pains/gains.

Opportunities

With the long queues at security processes being a potential space for COVID risks, it is difficult for both the staff and the passengers to manage and maintain a standard social distancing protocol.

Under the given constraints, we cannot change the TSA rules and procedures but we could focus on a component of the system. We introduced a slot-booking concept for the TSA security lines which would make the process smoother, quicker, and minimize COVID exposure (a win-win solution).

Who will benefit from our project?

Airports, Airlines, and Passengers

How did our team build and iterate on the solution?

Research & Brainstorming sessions

1.Identified problems that passengers are currently facing at the airport

2.Created customer personas based on the interviews and other research

Prototyping

  1. Developed a prototype with a UI model to assist in application build

Development

  1. Build the application

Business models

  1. With the application, we identified a reliable revenue model and generated a 3-year forecasted business model.

  2. Based on the multiple feedback received after using our application, we reiterated a few functionalities and refined it.

Key Metrics

Revenue Growth

With the calculated regional expansion strategy, NoQ could obtain a profit of 2.3M$ at the end of 3 years

Product Testing

Tested with 35 different users

Wait time Reduced Per Passenger

An average of 20 - 45 minutes reduced on a crowded day

An average of 10 - 20 minutes reduced on a less crowded day

Technical Details and Diagrams

Prototype

NoQ Prototype - Adobe XD

Information Architecture

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User flow Diagram alt text

Database Diagram alt text

Business Logic Diagram alt text

Web application

 MERN Stack - Mern is an open-source Javascript software stack for building dynamic web-applications. We choose this because it supports quick build iterations.


 Server - Mongo DB Atlas 


 Client - React frontend with redux state management

Tools and libraries

 React-Router - It is used to manage the transition between components.

 React-Bootstrap - Most comprehensive single library with the bootstrap functionality  

 Webpack - We used webpack to modularize and build the client-side code into a bundle to deliver to the browser.


 Check out the file on GitHub for a full list of libraries we used.

If we had another 5 weeks to work on this, what would we do next?

Our web application enables users to travel from Indianapolis airport to pre-book their TSA slots. Probable phases

  1. Enabling NoQ for airports in and around the state of Indiana

  2. Admin page for the airport staff to enable customization ( e.g. flight information, slot entry time, number of slots, unavailability of slots etc.)

  3. Mobile web support

  4. Managing multiple user accounts

  5. Email and Text notifications

  6. A detailed 10-year revenue generation forecast

  7. Generate a potential model for advertisement revenue at retail outlets in Airports

  8. Focus on market expansion to other states

Revenue Model

Based on the statistical data gathered from the Bureau of Transportation statistics, we have calculated the revenue and projected a potential three-year forecast.

Please follow the attached link for the detailed 3-year revenue generation forecast

Checklist of Completed Items

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Link to our slides!

Presentation Slides

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