Watts Up

A community-driven EV platform that optimizes charging with smart scheduling, dynamic pricing, voice commands, and QR-based bookings for an efficient, and accessible experience.

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Inspiration

The rapid rise of electric vehicles is transforming how we live in real time. However, access to charging remains an issue for EV cars, especially in residential areas. We saw communities with underutilised private chargers and overcrowded public stations, we realised that if there was a peer-to-peer sharing platform existed, it could revolutionise EV charging accessibility. Driven primarily by a passion for sustainable energy and community collaboration, our team set out to create a solution that would not only make the EV charging process as smooth as possible, but also allow users to share resources, reduce grid load, and promote renewable energy use. Our vision was to focus on driving sustainable change on a much needed issue with EV's with a community spirit.

What it does

Watts Up is a comprehensive community-driven EV charging network that connects EV owners with private and public charging stations all across the nation. it leverages smart scheduling, dynamic pricing features, voice detection, and AI-driven predictions to optimise charging time, reducing long wait times and enhancing user experience. Users can:

  • Search & Book Chargers: Find closest available chargers based on your location, vehicle model and battery needs.
  • Peer-to-Peer sharing: Rent out private EV charges to and from community members in your city.
  • Dynamic Pricing: Benefit from adaptive pricing that reflects real-time demand and supply.
  • Route Optimisation: Get guided directions with estimated arrival times using Google Maps API.
  • Voice Activation: Enjoy hands-free commands to book and change your booking while keeping you away from your phone while driving.
  • QR Scanning: Enjoy seamless on-site activation via QR codes, meaning no need for a wifi connection to charge your vehicle.
  • Predictive Queue Management: Experience reduced wait times with AI-predicted queue management and virtual waitlists .

How we built it

We designed a full-stack application, with a diverse tech stack. Our Backend:

  • We used Django and Express/Node.js to handle core logic, dynamic pricing algorithms, bookings and integrations with MongoDB for data storage. We integrated OpenAI's API for natural language processing, enabling voice-activated commands and intelligent interpretation of user requests. We utilised Google Maps API to allow for route optimisation features Our FrontEnd:
  • Using React and Next.js, we managed to create a responsive, intuitive UI that displays maps, booking details and dynamic pricing information all in your phone screen. Our Integration:
  • We connected various APIs (OpenAI for voice & dialogue, Google Maps for navigation) to build a seamless experience. A microservices approach allowed independent modules (like QR code scanning and voice recognition) to work together seamlessly. Our Voice & QR Code Features: We incorporated speech recognition (using Python libraries) and TTS for live interaction with OpenAI's APIs, plus QR code scanning for a secure activation at your station.

Challenges we ran into

Our biggest challenge was definitely coordinating between multiple languages and frameworks especially when merging our frontend and backend. Ensuring seamless communication between front and back as well as our APIs took most our time to perfect, especially during the later hours. Furthermore, one of the challenges that we ran into was that we always saw a new feature we could add and kept wanting to add new features due to the projects vast potential.

Accomplishments that we're proud of

We are particularly proud of our seamless user interaction, making it as easy as possible for EV owners to easily charge their car, with a cool twist of being able to rent out your private stations. We successfully implemented a voice-activated interface that interprets natural language, executes commands, and handles follow-up questions fluidly. Furthermore our AI-driven scheduling and dynamic pricing algorithms created a smarter and more efficient charging experience that adapts to users needs and grid demands. We combined multiple frameworks and APIs into a cohesive platform demonstrating our technical skills and collaborative mindset. Lastly one big thing that we are proud of is the ability that we are giving users to share their private chargers and benefit from a community-driven platform, which we personally believe is a huge significant step towards a sustainable, decentralised energy solutions

What we learned

In terms of full-stack, I believe we all got better and improved our understanding of how diverse technologies such as Python/Django, Node/Express, React/Next.js, and MongoDB can work together to create a seamless product like we have done. Furthermore, personally working on AI integration, I learnt a lot working with OpenAI's API, teaching me how to leverage NLP for real world applications, especially focusing on user interactions with voice recognition capabilities and quick decisions. Moreover, implementing dynamic pricing and predictive queue management highlighted to all of us the importance of data analysis and real time processing. Lastly we want to highlight how the project opened our eyes on how technology should serve people solving real-world problems with accessible solutions especially in underutilised residential areas to foster community, trust and adoption.

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