Shared Plates

Inspirations

Our team has frequently encountered a common challenge when dining out: the experience can often feel a bit lonely, and the options are limited by portion sizes and the cost of dishes. These pain points led us to brainstorm a solution that could address both the social and economic aspects of dining. This inspired the creation of SharedPlates, a platform designed to connect food enthusiasts who share a love for great meals and meaningful connections. With SharedPlates, users can find dining partners to share both the experience and the cost, making every meal more enjoyable and affordable.

What It Does

Solution

Our platform offers a two-fold solution:

Find Food Partners: Users can connect with others who are interested in dining together. The platform matches users based on their food preferences, dietary restrictions, and location, creating opportunities for shared meals and new social connections.
Save Money: By coordinating group dining orders, users can take advantage of bulk pricing, special offers, and shared portions, leading to significant cost savings. Restaurants benefit from increased patronage, and users enjoy high-quality meals at reduced prices.

Features

Restaurant Search and Recommendations: Users can search for restaurants by cuisine, location, and price range. The platform also offers personalized recommendations based on user preferences and location.
Menu Viewing and Order Customization: Users can browse restaurant menus, customize their orders, and see which items are popular among other diners.
Group Dining Coordination: Users can start or join group dining orders. The platform manages group logistics, including order coordination, payment, and deposit management.
Payment Integration: Secure payment processing, including holding deposits until orders are finalized.
Social Features: User profiles, chat functionality, and dining history to help build a community of food lovers.

How we built it

Challenges we ran into

Data Acquisition Difficulties: Gathering relevant data, such as user preferences, dining habits, and location, is often complex and expensive. Additionally, purchasing data from third-party sources adds to the costs.
Complex Recommendation System Demand: Building a dining match-up system need an efficient recommendation system. However, our limited experience restricts us to basic collaborative filtering and content-based recommendation systems. It is difficult for us to build an efficient hybrid recommendation system.
Users Participation: For the system to succeed, active user participation and feedback are essential. However, in the initial stages, users might be reluctant to invest time and effort to provide the necessary data or feedback, which could affect the quality of the recommendations.
Data collection and privacy issues: To recommend suitable dining companions and locations, it's necessary to collect user information such as personal preferences, eating habits, and location data. This data collection can raise privacy concerns, making it crucial to ensure the security and compliance of user data.

Accomplishments that we're proud of

Our team comprises mostly first-year students, including members coming from different backgrounds with no coding experience. Despite having little to no prior experience in software development, we embraced this hackathon as an opportunity to dive into unfamiliar territory. Throughout this journey, we learned how to take an idea from concept to launch, explored new areas of interest, and identified key gaps in our knowledge. While the learning curve was steep, we are proud of how much we’ve grown as a team. Most importantly, we had a lot of fun along the way!

What we learned

We try to create a website in Python. The first thing we learn is how to use the Flask extension to create our website. After we made it, the website was not a published website which means only the person who made this website can access the website, to make it published, we bought a machine engine from Google Cloud. We made everything in a virtual machine, downloading the Nginx,python3-pip,python3-venv, creating the SSH and the license to ensure the web's safety. learn how to import the data from the Excel to the database. We also learn tkinter which is helpful to make the python code as a visible app.

What's next for Shared Plates

From a technical perspective, there are several areas where SharedPlates can be improved to enhance performance, user experience, and scalability:

**Enhanced Recommendation Engine: We plan to implement a more sophisticated recommendation system powered by machine learning. By analyzing user behavior, dining history, and preferences, the platform can provide more accurate and personalized restaurant suggestions, improving user satisfaction.
**Scalability and Performance Optimization: As the platform grows, it’s essential to ensure that it can handle increasing numbers of users and transactions. We aim to optimize our back-end architecture, focusing on database indexing, load balancing, and microservices deployment to improve performance and ensure scalability.
**Improved Real-time Features: Enhancing our real-time features such as group dining coordination and chat functionality will require upgrading our WebSocket and server infrastructure. This will ensure smooth and reliable communication, even during peak usage times.
**Advanced Security Measures: As our platform involves handling sensitive user data and payment information, we plan to further strengthen our security protocols. Implementing advanced encryption methods, multi-factor authentication, and continuous monitoring will help protect our users and build trust.
**Cross-platform Integration: To reach a wider audience, we aim to develop native mobile applications for iOS and Android. These apps will offer seamless integration with the web platform, allowing users to switch between devices without losing functionality or data.

From a business perspective, we plan to expand SharedPlates to more cities, enhancing our restaurant network and providing users with even more dining options. We aim to introduce personalized recommendations powered by AI, as well as premium features like exclusive dining events and VIP access to popular restaurants. We are also exploring partnerships with food delivery services to offer shared meal delivery options, further broadening the ways users can connect and save through SharedPlates.