This Python-based Web App provides live hourly crowd data of different places and can predict future crowds. It also finds nearby places and helps people to avoid crowded public places.
Title: Python-Django-based Public Places Crowd Informing Web App with Crowd Prediction System
Programming Language Used: Python 3.8
Important Libraries: NumPy, Pandas, scikit-learn, Matplotlib, etc.
This Python and Django-based project help people to see the daily hourly crowd count of public places and use the same data for predicting crowd in the future and past. This will help people to choose a perfect time to visit the places. Data from places is collected through the means of API and stored in the database. The same stored data is used to train models of places used to predict crowds in the future. This data is visible to the web app user he/she can view that data in a visualized form and may help people to plan a visit to public places.
If you want to create a virtual environment then it's a better idea that won't damage internal python.
Install packages given in the readme file.
Start virtual Environment by "venv/Scripts/activate" in command prompt being in Project directory.
This project needs a MySQL database server because data will be collected in a large amount. You will need to create only database 'mydatabase' and run migrations that will create all the needed tables in the database.
"python manage.py makemigrations"
"python manage.py migrate"
Then Change the Directory by the "cd " command.
Admin Django: niranjantamhane
The system works on Windows, Linux, and Android systems if required python environment is available. Avoid the use of android where setting up a database is hectic work. Install given required packages in the readme.txt file.
1. Users are of 3 types
b. Customer user
2. Owner can also be a Customer. The owner is a user that registers his/her places where he/she will update the hourly crowd data through their systems using an API call.
3. API is secured by using the API key and place ID. API key is generated randomly and can be changed whenever needed.
4. User can see nearby places which are registered in the database by their owners using GPS coordinates.
5. Dynamic Pages.
6. Random Forest-based Prediction with 88% accuracy.
The Reason behind the Project:
The covid-19 situation is a motivation for this project. Public places are not safe and lockdown will continue till the infection rate decreases. The infection spreads through the touching and taking and giving of things. People will get tired and will come out for financial survival. Therefore, we need to create a web app that will help people to avoid crowded places.
Favorite Places of the User View:
Owners Login Page
Owner Register page:
Owner Place Detail Panel The owner can edit the place details page:
Owner Place Add New Place View:
Submitted by Niranjan Tamhane (niranjant9595)
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