vishalmadle13 / smrr

This project aimed to revolutionize restroom hygiene by developing a system that assessed cleanliness in real-time through odour detection and used machine learning for air quality analysis. The technologies employed included Python for scripting, Django for web development, Rest APIs for data communication, and Bootstrap for frontend design.

Smart Restroom Hygiene System

Overview

The Smart Restroom Hygiene System is an innovative IoT-driven solution designed to revolutionize restroom cleanliness monitoring. Utilizing real-time odour detection and advanced machine learning algorithms for air quality analysis, this system offers a comprehensive approach to maintaining high hygiene standards.

Technologies Used

• Python: For scripting and backend logic.
• Django: For web application development.
• Rest APIs: For seamless data communication between components.
• Bootstrap: For responsive and user-friendly frontend design.

Key Features

• IoT Sensors: Real-time odour detection to assess restroom cleanliness.
• Machine Learning: Advanced algorithms to analyze air quality and predict hygiene levels.
• Web Interface: Intuitive dashboard for real-time monitoring and alerts.

Screenshots

Source Code

Installation

Local Setup

To set up and run the Smart Restroom Hygiene System locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/vishalmadle13/smrr.git
   cd smrr

2. Create a Virtual Environment:

python -m venv smrrVenv
source venv/bin/activate
# On Windows, use `venv\Scripts\activate`

3. Install Dependencies:

pip install -r requirements.txt

4. Set Up the Database:

python manage.py migrate

5.Run the Development Server:

python manage.py runserver

6.Access the Web Interface: Open your web browser and navigate to http://127.0.0.1:8000/.

1.Docker Setup To build and run the Smart Restroom Hygiene System using Docker, follow these steps:

2.Build the Docker Image:

docker-compose build

3.Run the Docker Container:

docker-compose up -d  

4.Stop the contained:

docker-compose down 

5.Access the Web Interface: Open your web browser and navigate to http://localhost:8000/.