Inspiration

We felt that this would be a valuable application to a board range of users. The problem that we are aiming to solve has only recently become feasible due to new advancements in technology such as artificial intelligence. Thanks to the innovative sponsors at this event, we were able to tackle a problem we have not yet seen a accessible solution to.

What it does

Our product monitors audience emotion in real time. We provide on-the-fly analytics of audience reactions of presentations, business meetings, entertainment events, and more. The product presents a recent histogram of the recorded reactions, as well as percentage-based values that represent 8 different dimensions of emotion. In addition, the product offers a post-presentation review of all data collected over the period of the presentation.

How we built it

We leveraged React as our development framework, integrated with multiple machine learning/artificial intelligence techniques provided by industry leaders. We also used D3.js to present customized visualization results.

Challenges we ran into

  • Our product is designed as a client-heavy web application. Seeing as our team was comprised of three backend developers and one full-stack developer, most of the skill sets that were used within our product were acquired quickly through lots of experimentation and iterations over our product.
  • Some specific products, without prior experience, posed unexpected pressure on our development schedules.

Accomplishments that we're proud of

  • The data that we collected and present to the user is extremely intuitive.
  • Executed a minimum viable product with an agile development procedure.
  • Each team member acquired new skills through building our product

What we learned

  • Scheduling tasks and timelines in order to implement features is extremely important in a fast-paced, prototype heavy environment
  • Utilizing the resources given through the hackathon organizers and sponsors to further our product
  • Defining scope and specifications early on in the project was beneficial to our team in order to maintain focus on vital product features

What's next for MORTE

  • Accessibility of the product (e.g. color-blind mode)
  • Option for the user to save local data that was recorded to be imported to our app later for further analysis
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