The pitchdeck can be found here: Link
We are a team of four engineers from ETHZ and TUM. With our education and our current jobs, it is very hard to support the population directly but we still wanted to do our part which is why we decided to join the Hackathon.
While Zeeshan is a software engineer, the other three are mainly working with hardware - but robots and sensors are not developed over one weekend so we decided to go for a fast implementable solution. We all love going into small shops and discover hidden treasures, which is why we want to support these businesses.
What it does
Smooth Transition is a tool for both the customer and the shop owner. The shop owner can register his company and offer a certain amount of spots, which is depending on the available square meters and the requirements given by the state. The shop owner has also the possibility to report users which don't show up or maliciously reserve the whole calendar. We also included an analysis tool so the shop owner can see how many appointments the company got.
The customer has to open an account as well. The user is able to search for a specific name or just a general topic (i.e. workshop, bakery, music store, ...) and combined with the location we suggest shops from our database. [As we have currently no registered shops we just suggest all shops] They then can book an offered timeslot and get instant feedback. They can cancel an appointment 12 hours before it happens without restrictions - booking multiple times and not showing up will result in a temporary ban.
How we built it
There are two authorisation roles, customer and shop owner. For Customer: Frontend is built up on Bootstrap framework, Google Maps Geometry, Visualization, Places API's are used to search for nearby locations, rendering, and finding the most suitable match resolving specified constraints. Backend is developed in Python Flask and is communicating over REST API with jQuery with frontend. This web app is deployed on Microsoft Azure web apps. While for the shop owner, frontend is built on top of Bootstrap and the initial open source framework SB Admin 2 (https://startbootstrap.com/themes/sb-admin-2/) is tailored for smoothTransition. It is deployed on Azure blob storage as a static website. Because of shortage of time, there exists two servers (one for customer while one for shop owner). Moving forward they will be merged into single centralised platform. Calendly is used for booking appointments.
Challenges we ran into
Our main challenge was finding an issue which has not yet been solved. We got 3 different ideas, which all have been tackled in former Hackathons. But this also allowed us to refine our idea and find a specific problem which nobody tried to solve yet. Our team started bigger but soon we had some dropouts, which is mainly a problem of virtual Hackathons, as people feel less connected to the project. But it was easily doable with four people and probably an ideal size for a team.
Accomplishments that we are proud of
We got a working prototype online, we have worked really well together as a team and we even got our first simulations (which still need to be backed up by research papers). We asked ~10 people (flatmates, mentors, etc.) about their opportunity and the feedback was fortunately very positive. The need for reopened shops is for sure there. Furthermore we had a lot of fun during the hackathon!
What We learned
We learned a lot about remote teamwork. It was an interesting experience to work in a team all online and connected but not physically connected. We also individually learned a lot of skills as we (like in any hackathon) jumped into roles and onto tasks were previously not familiar with.
What's next for Smooth Transition
The protopye still needs some polishing but the main focus is getting feedback from shop owners and the government. If the legislation allows shops operating under hard requirements (like Supermarkets with the 10 m^2 per person) we could do first tests with a shop owner who is willing to participate.
A second path of action is looking for more hard data to show the difference between people standing in a queue and people showing up for an appointment. Having quantifiable data could help to convince lawmakers.
Try It out