HackStack

Project Info

Park-Eazy

Devpost

Inspiration

The inspiration for Park-Eazy came from the frustration of finding parking in busy urban areas, especially among students and daily commuters. With parking prices soaring and availability dwindling, we sought to create a platform that not only connects drivers with available parking spots but also helps space owners monetize their unused spaces.

What it does

Park-Eazy is an innovative platform designed to streamline the parking rental process. Users can easily browse available parking spaces in their vicinity, making it easier for them to secure affordable parking. The platform empowers space owners to list their unused spots, allowing them to earn extra income while helping drivers find convenient parking solutions.

How we built it

We built the frontend of Park-Eazy using React, ensuring a smooth and engaging user experience. The backend is powered by Python, which handles the application logic and connects to the database. We utilized Fetch.ai to create intelligent agents that fetch and display available parking spots dynamically. Additionally, we integrated a VAPI voice bot for customer care, allowing users to get assistance through voice commands.

Challenges we ran into

One of the primary challenges was ensuring seamless communication between the frontend and backend, particularly in managing API calls and responses. Integrating the AI functionalities from Fetch.ai required meticulous planning to ensure efficient performance. Moreover, building an intuitive and responsive user interface was crucial to enhance user engagement. Handling customer queries effectively through the VAPI voice bot added another layer of complexity.

Accomplishments we're proud of

We are proud to have developed a functional prototype of Park-Eazy that successfully connects users with available parking spaces. The platform has undergone extensive testing and has received positive feedback, confirming its usability and effectiveness. Our integration of voice bot technology has also set us apart, making customer support more accessible.

What we learned

Through the development of Park-Eazy, we gained a deeper understanding of full-stack application development, from designing user interfaces to managing backend processes. We learned how to integrate AI technologies effectively and the importance of user-centered design. Gathering and incorporating user feedback played a vital role in refining our platform and enhancing its features.

What's next

Looking ahead, we plan to introduce advanced AI capabilities to provide personalized parking recommendations based on user behavior and preferences. We aim to expand our service to additional cities, addressing a broader audience. Additionally, we will work on improving the voice bot's capabilities, enhancing its interactivity and customer support functions. We are committed to creating a comprehensive solution that meets the evolving needs of urban parking.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • FirebaseIn code
  • HTMLIn code
  • JavaScriptIn code
  • PythonIn code
  • ReactIn code
  • MongoDBClaimed

6 of 7 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

66 KB

Source files

39

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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