EcoCycle: A Deep Learning-Based Waste Categorization and Management System for Sustainable Smart Cities

Journal Title: International Journal of Current Science Research and Review - Year 2025, Vol 8, Issue 03

Abstract

Waste management is a critical environmental and economic issue worldwide. Existing waste segregation ac- tivities are inefficient, resulting in high landfill contributions and environmental contamination. In this paper, an artificial intelligence-based waste categorization and management system, EcoCycle, is proposed that utilizes deep learning models like VGG16, ResNet50, and DenseNet121 for automatic classification of waste materials. EcoCycle is equipped with a gamification system based on mobile, a marketplace for recyclables supported by blockchain, and an IoT-based network of intelligent bins for real-time monitoring. Experimental results show 92.36% classification accuracy with DenseNet121, which is improved compared to other implementation results. User survey with 500 users shows a 98% positive effect on user experience and increased awareness about sus- tainability issues. The proposed system contributes significantly towards processes related to circular economies and the goals of smart city initiatives, and it has high global applicability potential for urban waste management systems.

Authors and Affiliations

Dr. Madhumitha K, Tuhina Tripathi, Akanksha Rathore,

Keywords

Related Articles

Analysis of The Preparedness of Public Accounting Firm in Implementing Quality Management Standar 1 (QMS 1) Based on IAPI Guidelines (Case study KAP Nexia KPS)

Quality Management Standard 1 (QMS 1) is a standard established by the Indonesian Institute of Certified Public Accountants (IAPI) to serve as a framework ensuring that Public Accounting Firms (KAP) deliver services in c...

The Impacts of Youtube Videos on EFL Juniors’ Listening Skill at Nguyen Tat Thanh University

Using YouTube videos in English learning has become popular in recent years. This study investigates the impact of YouTube videos on EFL juniors’ listening skill at Nguyen Tat Thanh University, Vietnam. It contributes to...

Implementation of End-to-End Circular Economy in Dairy Farming: A Case Study of KOP SAE Pujon, Indonesia

This study was conducted at KOP SAE, Pujon District, Malang Regency, East Java Province, with the aim of identifying the application of the 5R principles (Reduce, Reuse, Recycle, Refurbish, and Renew) in the circular eco...

Fetal Cystic Hygroma in Pregnancy

Cystic hygroma is a congenital disorder characterized by benign cysts that form due to malformation of the lymphatic system, accounting for about 6% of all benign lesions of infancy or early childhood. This case report p...

Effect of the Addition Red Beetroot Powder (Beta vulgaris L. Var. Rubra L) as a Feed Additive in Feed on Production Performance, Egg Yolk Cholesterol and Blood Profile of Laying Hens

The aim of this research was to evaluate the effect of addition red beetroot powder (Beta vulgaris L. Var. Rubra L) as a feed additive in feed on production performance, egg yolk cholesterol and blood profile of laying h...

Download PDF file
  • EP ID EP761379
  • DOI 10.47191/ijcsrr/V8-i3-30
  • Views 56
  • Downloads 0

How To Cite

Dr. Madhumitha K, Tuhina Tripathi, Akanksha Rathore, (2025). EcoCycle: A Deep Learning-Based Waste Categorization and Management System for Sustainable Smart Cities. International Journal of Current Science Research and Review, 8(03), -. https://europub.co.uk/articles/-A-761379