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Papers
61,005 resultsShowing papers similar to The Project of an Autonomous Microboat with a Laser Device for Estimation of Water Area Pollution by Microplastic
ClearDesign and Implementation of a Microplastic Detection and Classification System Supported by Deep Learning Algorithm
Researchers designed and implemented a low-budget deep learning system for autonomous microplastic detection and classification in water, using three dual-wavelength lasers at 405 nm, 655 nm, and 534-807 nm to classify microplastics by size and type in real time.
Improvement and Empirical Testing of a Novel Autonomous Microplastics-Collecting Semisubmersible
Researchers improved an autonomous microplastic-collecting robot, testing design modifications that enhanced sampling efficiency and navigation in surface water environments, moving toward practical automated monitoring of plastic pollution.
Design and Validation of an Eco-Compatible Autonomous Drone for Microplastic Monitoring in Port Environments
Researchers designed and tested an autonomous drone system for monitoring microplastic pollution in port environments, where plastic tends to accumulate in semi-enclosed waters. The drone collected water surface samples and transmitted data in real time, demonstrating a practical tool for high-frequency environmental monitoring in busy maritime settings.
Exploring the Potential of Autonomous Underwater Vehicles for Microplastic Detection in Marine Environments: A Review
This review explores how autonomous underwater vehicles equipped with sensors could detect microplastics directly in the ocean, rather than relying on labor-intensive water sampling. Current detection methods are slow and expensive, making real-time monitoring difficult. Advances in onboard sensing technology could dramatically improve our understanding of where microplastics concentrate in marine environments.
A prototype of a portable optical sensor for the detection of transparent and translucent microplastics in freshwater
Researchers developed a portable prototype optical sensor capable of detecting transparent and translucent microplastics in freshwater by simultaneously measuring specular laser light reflection and transmission, offering a feasibility pathway for field-deployable microplastic monitoring.
Laser beam scattering for the detection of flat, curved, smooth, and rough microplastics in water
Researchers demonstrated that laser beam scattering using a low-cost prototype sensor can detect microplastic particles of varying shapes — flat, curved, smooth, and rough — in water, offering a potential foundation for affordable in-situ optical monitoring tools. The study advances understanding of light-microplastic interactions needed to design practical field detection systems.
Optical System for In-situ Detection of Microplastics
Researchers developed a portable optical system capable of detecting, identifying, continuously monitoring, and quantifying microplastics in situ at natural water bodies. The system uses optical techniques to observe the temporal behavior of microplastic concentrations at fixed locations, enabling real-time environmental monitoring without sample collection and laboratory processing.
Quantitative Detection of Microplastics in Water through Fluorescence Signal Analysis
Researchers developed an automatic, portable fluorescence-based system for quantitative detection of microplastics in water, using dye-stained particles flowing through a laser beam to enable fast and objective counting without manual microscopy.
Exploring the Potential of Autonomous Underwater Vehicles for Microplastic Detection in Marine Environments: A Systematic Review
This systematic review explores how autonomous underwater vehicles (AUVs) could be used to detect microplastics in the ocean in real time, replacing slower traditional sampling methods. While promising, the technology is still developing and faces challenges with sensor accuracy and deep-water operation. Better detection tools like these could help scientists understand how widespread microplastic contamination really is in marine environments.
MantaRay: A novel autonomous sampling instrument for in situ measurements of environmental microplastic particle concentrations
Engineers developed MantaRay, an autonomous instrument that can measure microplastic particle concentrations in the ocean in real time without requiring a research ship or human operator. Automated monitoring devices like this could make large-scale, cost-effective mapping of microplastic distribution across the ocean much more feasible.
ANTIPARA (Analysis of Tiny Particles in Aquatic Environment): A Water Scanning Device for Microplastics
This article describes ANTIPARA, a water scanning device designed for in-situ analysis of small microplastics in aquatic environments. The tool aims to automate microplastic detection in the field, addressing the time and cost limitations of current laboratory-based methods.
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.
An Artificial Intelligence based Optical Sensor for Microplastic Detection in Seawater
Researchers developed an AI-based optical sensor system combining an optical detection subsystem and an image acquisition subsystem to detect and identify microplastic particles in seawater, distinguishing them from naturally occurring marine particles. The device applies AI algorithms to analyze consecutive image frames and classify particles as microplastic or non-microplastic, with the full system housed in two portable cases.
Detection and Recognition of Ocean Garbage Using DIY ROV-Mounted DNN-Based Classification of Laser Images
Researchers designed a low-cost DIY underwater robot equipped with a laser imaging system and deep learning classifier to detect and categorize underwater garbage from microplastics to large debris. A custom-trained convolutional neural network achieved 91% classification accuracy, outperforming transfer learning approaches.
Unmanned Vehicle and Hyperspectral Imager for a More Rapid Microplastics Sampling and Analysis
Researchers tested a combination of an autonomous surface vehicle and a near-infrared hyperspectral imager to rapidly sample and identify microplastics on the Norwegian coast. Results compared favorably with standard FTIR analysis and demonstrated a repeatable method for assessing spatially variable microplastic concentrations in the marine environment.
Mini Uav-based Litter Detection on River Banks
Researchers developed a drone-based litter detection system combining high-resolution mapping, deep learning object detection, and vision-based localization that locates riverbank litter with decimeter-level accuracy, enabling automated monitoring of plastic pollution in urban waterway areas.
Use of an uncrewed surface vehicle and near infrared hyperspectral imaging for sampling and analysis of aquatic microplastics
Researchers combined an uncrewed surface vehicle with near-infrared hyperspectral imaging to sample and analyze aquatic microplastics larger than 300 micrometers. The approach demonstrated improved scalability and repeatability compared to traditional trawling methods, offering a more efficient way to monitor microplastic contamination in coastal waters.
“WAVECLEAN” – An Innovation in Autonomous Vessel Driving Using Object Tracking and Collection of Floating Debris
Researchers designed an autonomous vessel called WAVECLEAN that uses object-tracking technology to identify and collect floating marine debris, including plastics. The system combines camera-based detection with machine learning to navigate waterways and gather waste without human operation. The study demonstrates a technology-driven approach to addressing plastic pollution in harbors, rivers, and coastal areas.
Towards an IOT Based System for Detection and Monitoring of Microplastics in Aquatic Environments
This paper proposes using Internet of Things (IoT) sensors to build a real-time monitoring network for microplastics in aquatic environments. Automated, continuous monitoring systems could provide much better spatial and temporal coverage than current sampling-based approaches.
Towards Underwater Macroplastic Monitoring Using Echo Sounding
Researchers investigated using echo sounding (sonar) technology to detect and monitor underwater macroplastics in rivers and coastal environments, presenting this acoustic approach as a promising tool for measuring submerged plastic loads that surface trawling misses.
A novel autonomous microplastics surveying robot for beach environments
Researchers developed a novel autonomous robotic platform for detecting and chemically analyzing microplastics on beach surfaces, using a camera mounted on a robotic arm end effector to scan areas and identify particles smaller than 5 mm. The mobile manipulator system automatically locates and chemically characterizes microplastics in situ, addressing the challenge of large-scale environmental monitoring in coastal environments.
Use of Mobile Autonomous Systems for Pollution Control of Inland Water Bodies
Researchers examined the use of mobile autonomous aerial and floating systems for monitoring and controlling pollution in inland water bodies, including detection of illegally dumped construction and household waste that contributes to microplastic and groundwater contamination. The study analyzes existing practices and proposes improvements for using drones and autonomous surface vehicles to enable early detection of unregulated dumping with minimal resources.
Cleaning up the world’s oceans with underwater laser imaging
Researchers proposed using underwater LiDAR (Light Detection and Ranging) technology to detect and map submerged plastic debris in the oceans, arguing this approach offers higher resolution and greater safety for marine life compared to sonar, and could enable targeted cleanup of the estimated 70% of ocean plastic that lies below the surface.
Portable On-Site Optical Detection and Quantification of Microplastics
Researchers built a portable, on-site optical device to detect and quantify microplastics in water. The device addresses the challenge of detecting small, often translucent particles without a laboratory setting. Portable microplastic detection tools could enable real-time monitoring in the field, supporting faster environmental assessments.