For the video, we had bad technical difficulties and weren't able to get a video without echo
The inspiration for this project was from the health issues that arise for small businesses as well as customers. We wanted to create a project that would help our businesses but would also ensure safety for all potential customers. We wanted to help eliminate the risk that workers encounter when working in small businesses as well as the risk of going out to a store. When brainstorming ideas, one idea stood out from the rest with the potential to make an impact on our community. Spero was born!
What it does
Spero is a dynamic website which contains a database, Polynomial Regression ML model, as well as a personalized survey. Through research as developing, we have come up with a product that can serve as a dashboard for small/medium businesses as they navigate through this time of uncertainty. The main issue to solve was preventing the spread of COVID-19. To do this we developed a database that would allow businesses to put out slots with defined maximums and a client side where customers could sign up. This would prevent any overcrowding and would allow the business to plan in terms of resources. We took this a step further and created a Polynomial Regression ML model that would allow businesses to use past customer data to predict the influx of new customers. Lastly, we created a *personalized survey that would be perfect for small businesses across the country. * It contains the most recent data from government sites about employee and health regulations so all businesses could stay on top of things! With Spero, businesses can explore more resources, commonly asked questions, and more.
How we built it
We built this project using many languages. These include:
HTML/CSS/JS for the main website Templated for the CSS template Repl.it for the compiler MySQL and PHP myAdmin and Apache for the database Numpy/MatplotLib/SciKitLearn/Python for the ML model JS for the personalized survey JS for maximum occupancy
Challenges we ran into
We ran into some challenges that had to do with the MySQL/PHP database as well as the integration with the ML model. With the database, we had trouble trying to increment the number of people per appointment due to the connection within the two data pieces. For the integration with Python, we ended up switching to using Repl.it, an online compiler, to embed the ML model within the website as well as linking it to the page. This allowed the user to run it through the website as well as check out the code. Since we didn't have much experience with the coding languages and the time limit, we worked together and figured out our own strengths and weaknesses to pull together a final product
Accomplishments that we're proud of
What we learned
What's next for Spero
Spero hopes to be a crucial tool in keeping business workers and customers safe. We would like to also integrate more features that include using a database to find suppliers based on location as well as service. We would also like to add a more user friendly main dashboard equipped with graphs to promote a user friendly experience.