Inspiration

According to the survey from Hong Kong Publishing Professional Society in 2016, people preferred to borrow the printed books rather than to buy printed books or e-books. However, there is no such service provided online in Hong Kong.

Objective

To fully utilitize the books and encourage reading in HK

What it does

  • Book Lending and Borrowing*
    • The lenders upload details of the book including the lending cost and the borrowers can view and accept the offer when they are satisfied with that
  • Bookcrossing
    • Everything can give out their books for booking crossing. People can view the details of the book on the app in advance, which makes it better than the usual physical bookcrossing
  • Book Donation
    • People can add their unwanted books to the database in BookEverFlow. Voluntary organisations can briefly know the number of unwanted books and arrange the book collection truck in an more effective way

How we built it

  • For the cross-platfrom ability and quick development process, we selected the web-based application
  • The major language used in our project is Python
  • We selected Flask to be the framework and used Docker to help deploy our project on azure cloud web service

Challenges we ran into

  • Many programming techniques that we haven't learnt before are required when doing this project. Therefore, we need to investigate on how to solve those problems, like oauth
  • Next, we need to find out how to deploy our application to azure. All examples provided use the visual studio and templates. Howeever, those examples are quite different from our case, and therefore we learnt to use docker in order to let BookEverFlow use the cloud service provided by azure platform.

Accomplishments that we're proud of

  • Have this mature and unique idea
  • Complete a runnable application within 24 hours
  • Successfully learn and apply new skills quickly

What we learnt

  • How to build a product quickly
  • How to pitch an idea
  • How to develop an effective business plan
  • Azure

What's next for BookEverFlow

  • Better user interface

  • Add map function

    • Allow tracking on bookcrossing path
    • Show differences in reading habits for people living in different areas
  • Data analysis

    • All records from users are useful. We can apply machine learning technique after collecting enough data
    • Find out information that may improve our business model or benefit the society
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