Skip to content
@PlasticWise

PlasticWise

Turning Plastic Awareness into Action

PlasticWise

Turning Plastic Awareness into Action

Executive Summary

PlasticWise adalah inisiatif yang bertujuan untuk mengatasi krisis plastik di Indonesia melalui pendekatan teknologi. Aplikasi kami menyediakan peta fasilitas daur ulang plastik secara real-time, fitur pelacakan penggunaan plastik, dan kampanye edukatif untuk meningkatkan kesadaran masyarakat mengenai pengelolaan sampah plastik.

Table of Contents

Features

  • Real-time Recycling Map: Peta fasilitas daur ulang plastik yang membantu pengguna menemukan tempat daur ulang terdekat.
  • Usage Tracking: Fitur untuk melacak penggunaan plastik oleh individu dan bisnis guna meningkatkan akuntabilitas.
  • Educational Campaigns: Pusat edukasi dengan artikel yang mengangkat kesadaran publik tentang pengelolaan sampah plastik.

Project Scope & Deliverables

Week 1: Planning and Setup

  • Kick-off meeting, pembagian peran, dan setup lingkungan pengembangan.

Week 2: Development Phase 1

  • Pengembangan model machine learning dan setup infrastruktur cloud.

Week 3: Development Phase 2

  • Desain aplikasi mobile dan pengembangan backend API.

Week 4: Integration and Testing

  • Integrasi semua komponen sistem dan pengujian menyeluruh.

Week 5: Deployment and Testing

  • Deploy aplikasi ke lingkungan produksi dan dokumentasi lengkap.

Tech Stack

Mobile Development

  • Tools: Figma, Android Studio
  • Libraries: Android Jetpack, Retrofit, ConstraintLayout, RecycleView
  • Languages: Kotlin

Machine Learning

  • Tools: TensorFlow, OpenCV, Numpy, Pandas, Matplotlib, Google Colab
  • Languages: Python

Cloud Computing

  • Tools: Firebase Authentication, Cloud Endpoints, Cloud Functions, Cloud Storage, Cloud SQL, Compute Engine
  • Languages: NodeJS, ExpressJS

Installation

  1. Clone the repository:

    git clone https://github.com/PlasticWise/PlasticWise.git
    cd PlasticWise
  2. Set up the environment:

    • Follow the setup instructions for each component (Mobile Development, Machine Learning, Cloud Computing).

Usage

  • Mobile Application: Install the app on your Android device and start exploring the features.
  • Backend API: Run the server using NodeJS and ensure all endpoints are accessible.
  • Machine Learning Model: Train and deploy the model using TensorFlow and integrate it with the app.

Contributing

We welcome contributions from everyone. Please read our Contributing Guidelines for more information on how to get started.

Team Members

  1. Ra'idah Rasyid – Universitas Brawijaya
  2. Javier Janeti Suprantiyo – Institut Teknologi Sepuluh Nopember
  3. Wardiansyah Fauzi Abdillah – Universitas Gunadarma
  4. Khalisha Dzakira Hidayat – Institut Teknologi Sepuluh Nopember
  5. Mohammad Fierza Heikkal Firdaus – Universitas Gunadarma
  6. Zhaqian Ro'uf Alfauzi – Politeknik Negeri Jember
  7. Haikal Abizar – Universitas Gunadarma

Popular repositories Loading

  1. MobileDev MobileDev Public

    Java

  2. plasticwise-be plasticwise-be Public

    PlasticWise API build on top Hapi JS and integrating to GCP Services (GCS, Cloud SQL, Firebase, Cloud Run)

    JavaScript

  3. PlasticWise-ML PlasticWise-ML Public

    This is Repository for developing ML Model

    Jupyter Notebook

  4. .github .github Public

Repositories

Showing 4 of 4 repositories
  • MobileDev Public
    PlasticWise/MobileDev’s past year of commit activity
    Java 0 0 0 0 Updated Jun 21, 2024
  • plasticwise-be Public

    PlasticWise API build on top Hapi JS and integrating to GCP Services (GCS, Cloud SQL, Firebase, Cloud Run)

    PlasticWise/plasticwise-be’s past year of commit activity
    JavaScript 0 0 0 0 Updated Jun 20, 2024
  • PlasticWise-ML Public

    This is Repository for developing ML Model

    PlasticWise/PlasticWise-ML’s past year of commit activity
    Jupyter Notebook 0 0 0 0 Updated Jun 10, 2024
  • .github Public
    PlasticWise/.github’s past year of commit activity
    0 0 0 0 Updated Jun 3, 2024

Top languages

Loading…

Most used topics

Loading…