WASTIFY

An end-to-end recyclable waste management website.

Problem Statement

Waste management is a critical global challenge, and proper segregation of waste is crucial for effective recycling. The challenge is to develop an Object Recognition Application that uses computer vision to identify and segregate waste items into recyclable and non-recyclable categories. This application aims to streamline the waste management process, promoting environmental sustainability.

Objectives

The primary goal of this challenge is to design and implement an Object Recognition Application that utilizes computer vision to accurately identify and segregate waste items into recyclable and non-recyclable categories. The application should enhance the efficiency of waste management processes and promote sustainable practices.

• To bridge the gap between various stake holders of the Recyclable Waste ecosystem.
• Facilitate a dynamic website to users with a personalized experience to each one.
• Help the user to schedule pickup according to their convenience.

Functional Requirements

1. Image Recognition Algorithm: ○ Implement a robust image recognition algorithm capable of identifying various waste items with high accuracy.
2. Recyclable and Non-recyclable Classification: ○ Develop classification models that can differentiate waste items into recyclable and non-recyclable categories based on the recognized images.
3. Real-time Processing: ○ Ensure the application can process images in real-time, making it practical for use in waste processing facilities or even in mobile applications for individuals.
4. Integration with Robotics: ○ Explore the possibility of integrating the application with robotic systems for automated waste segregation in large-scale facilities.

Integration with Robotics

The Arduino project for waste segregation employs ultrasonic and soil sensors to efficiently categorize different types of waste. The ultrasonic sensor measures waste levels in bins, while the soil sensor detects moisture in organic waste. The Arduino code processes sensor data, triggering the segregation mechanism based on predefined thresholds. This mechanism can involve moving bins to designated areas or activating alerts for manual segregation. A feedback system, integrating LEDs or displays, communicates the segregation status. Rigorous testing and calibration ensure accuracy, and optional integration with external systems enhances functionality. Documenting the project and deploying it completes the process, promoting effective waste management.

TechStack Used

• HTML
• CSS
• JavaScript
• NodeJS
• MongoDB
• ExpressJS
• ReactJS
• Python
• Flask
• Neural Networks
• TensorFlow

Tools Used

• Figma
• Arduino UNO
• Pytorch
• FC-28 (Soil Sensor)
• HC-SR04 (Ultrasonic Sensor)

Contributors

Profile	Name	GithubID	EmailID	LinkedIN
	Kartik Sharma	@Kartik Sharma	sharma.kartik22a@gmail.com	kartik-Sharma
	Utkarsh Sharma	@Utkarsh-Sharma	utkatsh7424sharma@gmail.com	Utkarsh Sharma
	Dhruv Khandelwal	@DHRUVKHANDELWAL))	khandelwaldhruv2003@gmail.com	dhruvkhandelwal

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