Mobile EV charging Infrastructure does'nt have to be a hurdle for EV adoption if there is enough smart way to let users know which charging option is optimal for their current requirement. Currently in the market there are EV apps by the OEM which provide OBD which are focused on optimizing the energy usage of the EV and Apps to show consumer the nearest charging stations. There is a gap in the market for a true consumer experience where the EV owner is not left guessing what the best charging location is
What it does
Use Data analytics to combine EV OBD data (Soc, Avg Full recharge times, Temperature of the battery), Location Information, Charging Stations data ( Available Slots, Wait Times , Time to locations etc) we will provide optimal charging option(cheapest&Fastest) for the EV owners.
How we built it
The App prototype was built using Thunkable. The proposed platform architecture includes IoT integration with existing resources, API for getting Location , maps etc, AWS for data storage , python for Analytics.
Challenges we ran into
Mocking up the datasets as close to real life scenario with minimum IoT knowledge.
Accomplishments that we're proud of
A strong prototype Workable Algorithm Pseudocode Diversity of the team and the knowledge exchanged
What we learned
Non Programmers in the team were introduced to Thunkable to build the mobile App Programmers collaborated with the Energy experts to gain more insights into Practical EV Adoption challenges
What's next for BOOST
Data Collection Partnerships with OEM and Charging Stations Crowdsourcing for Information Improving the algorithm Upgrading the look and feel of the app