The problem ExploreSphere - Your Ultimate Tour Guide solves

ExploreSphere: Key Features

• User Authentication: ExploreSphere uses Firebase Authentication for user registration and login. Your data is securely managed, and the authentication process is streamlined. The advantages of this authentication system are that it is efficient, secure, and doesn't require additional storage space for user data.

• Travel Planning: Users are prompted to input the month of their intended travel, their budget, and describe the destination they wish to visit.

• Destination Recommendations: Based on user input, the app leverages machine learning to recommend the top 3 destinations, complete with detailed descriptions.

Challenges we ran into

Challenges:
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The unavailability of a suitable dataset posed a unique challenge. and to overcome this, data scraping and preprocessing became essential. Data was scraped from various sources, as a suitable dataset wasn't readily available. This was a challenge due to varying data formats, sources, and data quality.

Backend-Frontend Integration: The major problem was integrating our ML model with our Kotlin Android App.
First we deployed our ML model on Flask and then hosted it on pythonAnywhere. Backend-Frontend Integration involved designing APIs, implementing data transfer, and ensuring the app's smooth operation. Extensive testing with tools like Postman was essential to verify the integration's correctness.

Web Hosting: Hosting the flask app online was one of the major challenges. Selecting a suitable web hosting service, configuring it, and ensuring the app's availability and performance were complex tasks.

Data Retrieval: When the user provides input for all three features (travel month, budget, and description), fetching and processing the relevant data from the backend and displaying it efficiently was a complex task that needed careful implementation.