We wanted to develop an application that can make an impact on local society, and in addition, both owners and renters can earn a bit of money at the same time.
What it is
PedalShare is a bike sharing application, similar to Uber in that it does not own the mode of transport being used. It links with a Smart Bike Lock, which utilises both Bluetooth and GPS technology, to allow for encrypted, wireless locking. It allows bike owners to get some extra level of security, as well as the ability to rent out their bikes in the local area, thus reducing the neighbourhood's carbon footprint. PedalShare also offers bike renters a cheap alternative to traditional transportation facilities, as well as the opportunity to get rewards for achievements.
The website, coded in HTML5, JQuery & CSS3, will enable renters to check for bikes in their immediate surroundings, and allows owners to check on the status of their bikes that they are renting or otherwise. It displays recent trips, specific KPIs, and even possible reward accumulations for both renters and owners. In addition to this, deep learning, was utilised in the backend to predict renter activity, coded in Python & R using Keras, Tensorflow.
The iOS application, coded in Swift, will find your location along with the distance to a pre-determined postcode, entered by the user. It will display the nearest available cycles in your area and can retrieve your stats, rewards and profile information. Core coding was done in Swift for iOS 11.3. Firebase DB_Services was used as the core DB, both for the website and the application. The ability to add in-app purchases, push notification and Core ML modelling has been integrated and will surface in a future version.
How we built it
An iOS application using swift - coded in Xcode and Adobe XD.
A website using html and css3 - Sublime Text.
Deep neural network modelling - RStudio and PyCharm.
Challenges we ran into
Working under time pressure. Some tasks took longer than they should have, including dinner to arrive. Coding when you feel sleepy causes human errors.
Accomplishments that we're proud of
We challenged ourselves to develop and to integrate machine learning into the backend of the applications
What we learned
Developing a webapp and an ios app in less than 24 hours was a very big deal, but with that we developed numerous skills on our part as a person and as a team. Being our first hackathon, we are positive and happy with what we accomplished during this time.
Precious things don't come easily, and we realised this with that efforts that we put in, along with a sleepless night. If this is the way of learning then we are more happy to enjoy many more sleepless nights in the future.
What's next for PedalShare
Obviously, we have invested our time in this, so we would definitely like to take it ahead from here. We are, if all goes well, thinking of making this into a reality and dive further in depth with this application.
This application was developed thinking about social, environmental and health perspectives, so we want to channel our efforts into creating ideas that benefit the local community, and can impact the global community.
With the skills we possess, we are highly motivated to take PedalShare to the next level.