Smart Waste Management and Classification Systems Using Cutting Edge Approach

Abstract

With a rapid increase in population, many problems arise in relation to waste dumps. These emits hazardous gases, which have negative effects on human health. The main issue is the domestic solid waste collection, management, and classification. According to studies, in America, nearly 75% of waste can be recycled, but there is a lack of a proper real-time waste-segregating mechanism, due to which only 30% of waste is being recycled at present. To maintain a clean and green environment, we need a smart waste management and classification system. To tackle the above-highlighted issue, we propose a real-time smart waste management and classification mechanism using a cutting-edge approach (SWMACM-CA). It uses the Internet of Things (IoT), deep learning (DL), and cutting-edge techniques to classify and segregate waste items in a dump area. Moreover, we propose a waste grid segmentation mechanism, which maps the pile at the waste yard into grid-like segments. A camera captures the waste yard image and sends it to an edge node to create a waste grid. The grid cell image segments act as a test image for trained deep learning, which can make a particular waste item prediction. The deep-learning algorithm used for this specific project is Visual Geometry Group with 16 layers (VGG16). The model is trained on a cloud server deployed at the edge node to minimize overall latency. By adopting hybrid and decentralized computing models, we can reduce the delay factor and efficiently use computational resources. The overall accuracy of the trained algorithm is over 90%, which is quite effective. Therefore, our proposed (SWMACM-CA) system provides more accurate results than existing state-of-the-art solutions, which is the core objective of this work.

Smart Waste Management System for Smart & Sustainable City of Indonesia’s New State Capital: A Literature Review

“…This model effectively distinguishes six types of waste, including cardboard, glass, metal, paper, plastic, and other trash [33,34]. Despite the use of smart bins, this camera technology with sensors and artificial intelligence can also be used for garbage collection and classification in remotely accessible or waste disposal areas [9,29].…”

Global Models of Smart Cities and Potential IoT Applications: A Review

“…IoT applications leverage the power of the Internet of Things (IoT) to enhance waste management systems, making them more efficient, cost-effective, and environmentally friendly [78]. These applications utilize various IoT technologies to monitor, collect, analyze, and manage waste in real time [79]. Overall, smart waste management IoT applications offer a holistic approach to handling waste, promoting sustainability, reducing operational costs, and contributing to a cleaner environment.…”

Comparative Study of Indonesia and Denmark in Creating a Smart Environment

“…Jambeck in [5] states that Indonesia is the second country in the world to produce plastic waste in its waters. This condition is increasingly inflamed, along with the low quality and infrastructure of waste management and smart waste management systems [6,7]. However, the government's focus on highlighting environmental sustainability is still limited [8,9].…”