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@Bin-Detective

Bin Detective

Bin Detective: “Kenali Jenis Sampahmu”

Empowering Minds: A Holistic Approach to Education and Personal Development

Meet's our team

This project come up with 6 members that consisting of 3 Machine learning 2 Cloud Computing and 1 Mobile Development,Before we explain our project lets meet our team first :

Team ID : C242-PS471 Team Member :

  • (ML) M296B4KX1782 – Hilda Desfianty Arifin – UPN “Veteran” Jawa Timur - Active
  • (ML) M296b4KX1239 – Eka Maurita – UPN “Veteran” Jawa Timur - Active
  • (ML) M296B4KY0800 – Bahiskara Ananda Arryanto – UPN “Veteran” Jawa Timur - Active
  • (CC) C296B4KY2940 – Muhammad Mega Nugraha – UPN “Veteran” Jawa Timur - Active
  • (CC) C296B4KY3685 – Rangga Agni Nalendra – UPN “Veteran” Jawa Timur - Active
  • (MD) A296B4KY0982 – Danendra Alvyn Anshari – UPN “Veteran” Jawa Timur - Active

Executive Summary / Abstract

Children and teenagers often lack an understanding of the different types of waste and the importance of proper waste segregation, leading to increased improperly managed waste and negative environmental impacts. To address this issue, Bin Detective was developed—a gamified mobile application designed to improve young people’s knowledge and practices in effective waste management.

Through engaging quizzes, educational content, and a reward-based system, Bin Detective seeks to:

  • Raise awareness of proper waste management.
  • Foster environmentally responsible habits among children and teenagers.
  • Contribute to a cleaner and healthier environment by promoting sustainable behaviors in a fun, interactive way.

This project aims to evaluate whether the Bin Detective app can positively influence waste management behaviors and assess its impact on fostering environmentally conscious habits in young users' communities.

How our team come up with Bin Detective

Our team came up with "Bin Detective" after noticing a significant gap in waste management awareness among children and teenagers, which has led to improper waste handling and its environmental impacts. We observed that traditional methods of educating young people about waste segregation were not engaging enough to create lasting habits. Recognizing the potential of gamified learning, we developed "Bin Detective" to make waste management education both fun and impactful. Through interactive quizzes, rewards, and educational content, we aim to empower young users to adopt sustainable practices that benefit their communities and the environment.

Technologies Used

  • Mobile Development: Kotlin
  • Backend Services: Express.js with Firebase
  • Machine Learning: TensorFlow, Keras
  • Cloud Infrastructure: Google Cloud Run and Firebase Storage

Our App's Cloud Infrastructure Architecture

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  1. bindetective-backend bindetective-backend Public

    This is the backend for the Bin Detective app, built with the Express framework. It provides functionalities such as user management, content management, machine learning-based waste image predicti…

    JavaScript 1

  2. bindetective-ml bindetective-ml Public

    This repository provides the machine learning models for the Bin Detective app, designed to classify waste into 10 categories. It includes model details, training documentation, and dataset informa…

    Jupyter Notebook

  3. bindetective-mobile bindetective-mobile Public

    This repository contains the Bin Detective mobile app, focused on delivering a user-friendly interface and implementing core functionalities for waste classification. Built with a clean and intuiti…

    Kotlin

  4. bindetective-ml-backend bindetective-ml-backend Public

    The Bindetective ML Service is a FastAPI-based backend for real-time waste image prediction in the Bin Detective app. It uses Robin, our custom ML model, to classify waste from image and is deploye…

    Python 1

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