chimpiriudaykiran / AmusementParkFlask

This is a website for an amusement park that features a virtual queue system and utilizes machine learning for predicting wait times. The website provides an enhanced experience for park visitors by allowing them to reserve their spot in line virtually and receive accurate predictions for ride wait times.

Amusement Park Website with Virtual Queue and Wait Time Prediction

This is a website for an amusement park that features a virtual queue system and utilizes machine learning for predicting wait times. The website provides an enhanced experience for park visitors by allowing them to reserve their spot in line virtually and receive accurate predictions for ride wait times.

Features

• Virtual Queue: Visitors can reserve their place in line for attractions through the website, reducing the need to physically wait in queues.

• Wait Time Prediction: The website utilizes machine learning algorithms to predict wait times for rides based on various factors such as historical data, current park attendance, weather conditions, and special events.

• Interactive Map: An interactive map of the park is available on the website, allowing visitors to explore attractions, dining options, and facilities.

• Real-time Updates: Wait times and queue status are updated in real-time, providing visitors with accurate information throughout their park visit.

Technologies Used

• Python Flask: Flask is used for server-side scripting, handling requests, and integrating the machine learning models for wait time prediction.

• HTML/CSS: The frontend interface is built using HTML for structure and CSS for styling, providing an intuitive and visually appealing user experience.

• JavaScript: JavaScript is utilized for interactive features such as the virtual queue interface and dynamic updates on the wait time predictions.

• Machine Learning: Various machine learning algorithms are employed to analyze historical data and predict wait times for attractions.

Installation

To run the website locally, follow these steps:

1. Clone the repository to your local machine.

   git clone https://github.com/chimpiriudaykiran/AmusementParkFlask.git
   

2. Navigate to the project directory.

   cd amusement-park-website
   

3. Install dependencies using pip.

   pip install -r requirements.txt
   

4. Run the Flask application.

   python app.py
   

5. Access the website in your web browser at http://localhost:5000.

Usage

• Visitors can navigate the website to view attractions, check wait times, and reserve spots in the virtual queue for desired rides.

• The machine learning-based wait time prediction feature provides visitors with estimates on how long they may need to wait for each attraction, helping them plan their day effectively.

• Real-time updates ensure that visitors are informed about any changes in wait times or queue status throughout their visit to the park.

Contact

For questions or inquiries, please contact [e-mail].