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61,005 resultsShowing papers similar to Unmanned Vehicles System Utilizing Waste Tracking Data to Tackle Plastic Marine Littering on Tourist Islands
ClearA Proposed Technology Solution for Preventing Marine Littering Based on Uavs and Iot Cloud-based Data Analytics
This paper proposes a technological solution using unmanned aerial vehicles and automated collection systems to prevent marine littering at coastal hotspots. The approach aims to intercept plastic waste before it enters the ocean and breaks down into microplastics.
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.
“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.
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.
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.
Particle Swarm Optimization Based Efficient Path Planning in Autonomous Marine Trash Collection
Researchers developed a marine trash-collecting robot guided by Particle Swarm Optimization (PSO) and GPS, which uses a conveyor-based collection mechanism and sensor input to navigate waterways and efficiently collect floating plastic debris.
Beach Cleaning Robots a Comprehensive Survey of Technologies Challenges, and Future Directions
This paper is not relevant to microplastics; it is a survey of robotic technologies and methodologies for automated beach cleaning and litter removal.
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.
How to Deal With Seafloor Marine Litter: An Overview of the State-of-the-Art and Future Perspectives
This review examined the state of the art for detecting and removing marine litter from the seafloor, finding that while surface and beach litter has received substantial attention, seafloor litter remains understudied and that emerging technologies including underwater robotics offer promising future cleanup pathways.
Use of UAVs and Deep Learning for Beach Litter Monitoring
Researchers developed an autonomous beach litter monitoring pipeline using UAV drone surveys combined with a YOLOv5 deep learning object detection algorithm trained on footage from Malta, Gozo, and the Red Sea coast. The system achieved a mean average precision (mAP50-95) of 0.252 across all litter classes and incorporated geolocation and digital elevation model data to support future autonomous retrieval robots.
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.
UAV Approach for Detecting Plastic Marine Debris on the Beach: A Case Study in the Po River Delta (Italy)
UAV imaging was used to detect and map anthropogenic marine debris on beaches in the Po River Delta, Italy, testing different image processing strategies and demonstrating that centimeter-scale spatial resolution UAV surveys can efficiently locate macroplastics before they degrade into harder-to-remove 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.
A Novel Multi-Robot Task Allocation Model in Marine Plastics Cleaning Based on Replicator Dynamics
This paper proposes an algorithm for coordinating multiple autonomous underwater vehicles (AUVs) to clean up marine plastic pollution more efficiently. Better robotic systems for ocean plastic collection could help address the vast amounts of plastic debris accumulating in marine environments.
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.
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.
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.
Detection and assessment of marine litter in an uninhabited island, Arabian Gulf: A case study with conventional and machine learning approaches
Researchers surveyed marine litter on a remote Arabian Gulf island after a large cleanup, then trained a YOLO-v5 deep learning model on 10,400 beach images to automatically detect debris, achieving 90% detection accuracy and demonstrating that windward shores accumulate significantly more litter from neighboring countries.
Towards Accessible Aquatic Cleanup: A Low-Cost Solution for Floating Waste Extraction
Researchers designed and tested a low-cost autonomous floating waste extractor using a conveyor mechanism to capture lightweight surface pollutants including microplastics, demonstrating high efficiency in capturing debris and offering an affordable solution for resource-constrained settings.
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.
Designing Unmanned Aerial Survey Monitoring Program to Assess Floating Litter Contamination
Researchers tested drone-based aerial surveys with high-resolution cameras as a cost-effective method for monitoring floating litter contamination in coastal waters, comparing manual counting, automated detection, and modeling approaches to optimize survey design.
Object Detection of Macroplastic Waste Using Unmanned Aerial Vehicles in Urban Canal
Researchers developed and tested an unmanned aerial vehicle-based system for detecting macroplastic waste along riverbanks and beaches using object detection algorithms. The system achieved reliable detection performance and offers a scalable tool for large-area plastic litter surveys.
A Spiral-Propulsion Amphibious Intelligent Robot for Land Garbage Cleaning and Sea Garbage Cleaning
Not relevant to microplastics research; this paper presents the design and testing of an amphibious robot capable of collecting garbage from beaches, tidal flats, and the ocean surface, but does not analyze microplastic pollution specifically.
Mapping of marine litter on the seafloor using WASSP S3 multibeam echo sounder and Chasing M2 ROV
Researchers tested multibeam sonar and a remotely operated underwater vehicle (ROV) to map marine litter on the seafloor of a Croatian channel, finding the ROV effective for shallow-water debris detection but limited without proper navigation aids. This work advances techniques for locating plastic debris hotspots on the seabed, which is important because seafloor litter — including microplastic precursors — is largely invisible and understudied.