We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Papers
61,005 resultsShowing papers similar to Indonesian Waste Database: Smart Mechatronics System
ClearA Smart Garbage Classification based on Deep Learning
Researchers developed an AI-powered garbage classification system using deep learning to automatically sort waste categories. Accurate automated waste sorting could improve plastic recycling rates, reducing the amount of plastic that eventually breaks down into environmental microplastics.
Design and Development of Smart Beach Debris Collection and Segregation System
Researchers designed and built a smart automated system for collecting and segregating beach debris, using sensors and robotics to identify and sort plastic waste from natural material on shorelines. The system demonstrated effective separation of plastic debris in field tests.
Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials
This paper describes an AI-based robotic arm system that uses a customized deep learning model to classify and sort waste materials including plastics and cartons by material type for automated recycling. The integrated system combines gripping, motion control, and AI-driven material classification into a full-automation architecture for waste recovery.
Application of AI-Enabled Computer Vision Technology for Segregation of Industrial Plastic Wastes
Researchers developed an AI-powered computer vision system to segregate mixed industrial plastic wastes by polymer type, addressing a key barrier to effective plastic recycling. The system achieved high classification accuracy across common plastic categories, demonstrating that machine vision can improve sorting efficiency and recycled plastic quality.
Mechatronic system to classify plastic and metal bottles using capacitive and inductive sensors
This study designed a mechatronic system using capacitive and inductive sensors to classify plastic and metal bottles, developing an automated sorting approach that achieves high classification accuracy relevant to recycling operations.
An Automatic Garbage Classification System Based on Deep Learning
Researchers developed an automated garbage classification system using a deep learning algorithm based on ResNet-34, achieving 99% classification accuracy with a processing time of under one second per item. Automated waste sorting technology like this could improve the efficiency of plastic waste recovery and reduce mismanaged plastic that eventually becomes environmental pollution.
A Machine Arm to Assist in Trash Sorting using machine Learning and Object Detection
Not relevant to microplastics — this paper describes a robotic arm system that uses machine learning and computer vision to sort recyclable waste materials, focused on automation of waste sorting processes.
Sensor-based and Robot Sorting Processes and their Role in Achieving European Recycling Goals - A Review
This review covers sensor-based and robotic sorting technologies for waste management, assessing how they can help achieve European recycling targets. Improved sorting is critical for increasing plastic recycling rates and reducing the amount of plastic that enters the environment as pollution.
Design and Fabrication of Material Separation Machine for Sustainable Development
This paper is not relevant to microplastics research — it describes the design and fabrication of a robotic material separation machine intended to sort recyclable waste more efficiently using AI-inspired engineering principles.
Enhancing Waste Management with a Deep Learning-based Automatic Garbage Classifier
This paper is not about microplastics; it presents a deep learning convolutional neural network system for automatically classifying garbage by material type to improve waste sorting efficiency and reduce the labor burden of manual waste management.
Autonomous Waste Classification Using Multi-Agent Systems and Blockchain: A Low-Cost Intelligent Approach
This study developed and tested a prototype smart waste bin using multi-agent systems and blockchain to automatically sort waste (organic, plastic, paper) in real time, demonstrating a low-cost approach for intelligent municipal waste management.
Artificial intelligence for waste management in smart cities: a review
Researchers reviewed how artificial intelligence (AI) is being applied to nearly every aspect of waste management, from sorting recyclables with up to 99.95% accuracy to cutting transportation costs by over 36%. Their findings show AI could dramatically improve how cities handle plastic and other waste, reducing pollution and public health burdens.
Advancing Plastic Waste Classification and Recycling Efficiency: Integrating Image Sensors and Deep Learning Algorithms
Researchers developed a deep learning approach combined with image sensors to improve plastic waste classification and recycling efficiency. The study demonstrates that this method can distinguish between chemically similar plastics like PET and PET-G that conventional near-infrared spectroscopy struggles to differentiate, potentially improving automated sorting systems.
Development of Garbage Collecting Robot for Marine Microplastics
Researchers developed a garbage-collecting robot designed to remove plastic debris from coastal areas before it degrades into microplastics, addressing the logistical challenge of cleaning extensive shorelines with minimal human labor and resources.
Automated Plastic Waste Detection Using Advanced Deep Learning Frameworks
Researchers developed a deep learning system using advanced neural network frameworks for automated detection and classification of plastic waste from images, achieving high accuracy in identifying multiple plastic types to support environmental monitoring and waste sorting.
Development of Garbage Collecting Robot for Marine Microplastics
Researchers designed and developed an autonomous cleaning robot for collecting marine microplastics scattered on beaches, using a conveyor belt and tray system to mechanically gather and retain small plastic particles. The study addresses the practical difficulty of manually collecting dispersed microplastics and demonstrates the robot's configuration and operational concept for beach remediation.
An Overview of Plastic Waste Recycling in the Urban Areas of Java Island in Indonesia
This overview examines plastic waste recycling management in urban areas across Java Island, Indonesia, one of the highest plastic-polluting regions in the world. It identifies barriers to improved recycling rates and proposes strategies to shift toward more sustainable production and consumption patterns.
A Reliable and Robust Deep Learning Model for Effective Recyclable Waste Classification
Researchers developed a deep learning computer model that can sort waste into six categories, including plastic, with 95% accuracy. While this is a waste management technology rather than a health study, better automated waste sorting could help keep more plastics out of the environment where they break down into microplastics. Improved recycling through AI-powered sorting is one practical step toward reducing the microplastic pollution that eventually reaches people.
Deep transfer learning benchmark for plastic waste classification
Researchers benchmarked six deep transfer learning models for classifying plastic waste types, achieving high accuracy in automated sorting that could help address plastic pollution by improving recycling efficiency.
Smart Ocean Cleanup: An AI-Integrated Autonomous System for Marine Waste Management
This paper presents an AI-powered autonomous boat system designed to detect and collect marine pollution — including plastics, oil spills, and microplastics — using deep learning image classification, IoT sensors, and robotic collection mechanisms. The system demonstrated over 94% accuracy for pollutant detection and classification across several AI models. While focused more broadly on ocean cleanup technology than on microplastic science specifically, it demonstrates how AI-integrated robotics could help address the practical challenge of removing plastic waste from ocean surfaces before it breaks down further.
Challenges to Increase Plastic Sorting Efficiency
This paper reviews the current challenges and future opportunities for improving plastic sorting rates in waste management systems. Higher sorting rates are essential for increasing plastic recycling and reducing the amount of plastic that ends up fragmented into microplastics in the environment.
Potential Utilization Analysis of River Waste in Jakarta, Indonesia
This study analyzed the composition and potential recyclability of river waste in Jakarta, Indonesia, where poor waste management leads to significant plastic debris entering waterways. Better waste sorting and utilization strategies could reduce the amount of plastic that breaks down into microplastics in urban rivers.
Comparative Study of Chemometric Approaches and Machine Learning for Miniaturized Near-infrared (micronir) Spectroscopy in Plasticwaste Sorting
This study tested a miniaturized near-infrared (NIR) spectroscopy device combined with chemometric and machine learning methods to sort different types of plastic waste. The approach accurately identified polymer types, supporting more efficient plastic recycling operations that could reduce microplastic generation.
Automatic Beach Cleaning Robot
Researchers designed a portable automatic beach cleaning robot for collecting plastic debris from sandy beaches to reduce marine pollution and protect aquatic ecosystems.