Prototype - Landing Page
Prototype - Login Page
Prototype - Home Page
Prototype - Recommendation Page
Prototype - Requirement
Prototype - Request
Prototype - Status Request
Prototype - Success Page
App - Home Page
App - Profile Page
App - Request Page
App - Add New Requests
App - Supply Page
App - Dashboard
Interactions were introduced in the prototype.
Wireframes created based on the solution to the problem.
As we are quarantined in our homes, we decided why not contribute towards the social cause and help in fighting COVID-19. We came across HacktheCrisis and selected an interesting problem space we can tackle. The problem statement motivated us since, it was within our limit to contribute. Cases globally, are rising at an alarming rate over 6,00,000+(current affected), and we thought that this is the perfect situation where we can help all the labs and hospitals to exchange stockpiles in times of emergency.
This project was selected as one of the winners of HACK THE CRISIS- AUSTRIA
What it does:
Medilink, an application which serves as a radar for different labs and hospitals in any given geographic location to see and exchange stockpiles without disrupting the normal supply chain.
Why it is important:
Although many modern hospital or hospital systems have electronic inventory control and maybe a SAP / Ariba procurement, there is still no exchange of inventory outside of their own hospital systems.
How we built it:
Firstly, we took a close look about what was available out of the given resources. We found out that Glideapps provides us with an extremely easy way to create an app. But once, we start to build it, we wanted to customize it more, so we, started to add Python code to the backend to the customize it even further. The data was retrieved from the Google Sheets which we integrated in our app. For the click dummy purpose we used Adobe XD to create an interactive prototype.
Challenges we ran into:
There were lot of challenges we faced when we jumped into solving this problem. Firstly, starting of we had a lot of problems integrating maps and extracting the locations of all the hospitals in a nearby area. Once, we solved that, Inventory management become a problem because we had to write the logic for it in the backend within this time constraint.
Impact it can have:
- The application could lead to a single view platform of what supplies needed and which are already available.
- Obtaining supplies that is, matching requests and offers which could reduce procurement from days to (hopefully) hours.
- Suppliers or government procurement would also have a single view of what is needed. The effectiveness of our system depends on achieving that the largest hospitals/clinics within a region are connected for basic supplies.
Accomplishments we are proud of:
We actually got the project working! This was quite an endeavor for us as we ran into quite a few issues early on. Luckily we were able to power through two nights, fixing each issue along the way (thanks StackOverflow!). This was the first hackathon for most of our group, so having a tangible result is really cool. Plus this is something that we wouldn't mind working on some more after the hackathon to see how far we can take it.
What we learned:
We learned a lot during this Hackathon! None of us were very familiar with any of the technologies we implemented for our project. Some of us did not even know Python. When we were coming up with the idea and implementation, we all wanted to work on bettering our understanding with some of the platforms and tools we used. Over the past 48 hours, we've been able to get hands-on experience using Python, Google Colab, Figma, Glideapps and a variety of other languages and libraries. This project was very involved for us, and left us with some valuable experience we can build upon in the future.
What's next for Medilink
Down the line as more and more hospitals and labs sign up, we gather more data which will help us to build more powerful Recommendation systems leveraging the power of machine learning. Moreover, there is tons of data from Twitter or from Facebook groups which goes astray. Going forward what we decided to do is scrape those data to have better impact in times of emergency. We will also like to incorporate, Route optimization or Max flow algorithm which further optimizes our application.