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61,005 resultsShowing papers similar to Exploring the Potential of Autonomous Underwater Vehicles for Microplastic Detection in Marine Environments: A Review
ClearExploring 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.
A Review of Recent Advances in Microplastic Research and ROVs to Aid the Development of an Integrated Solution for Microplastic Pollution
This review examines recent advances in microplastic detection and filtration research alongside remotely operated vehicle (ROV) technology, with the goal of developing integrated solutions for microplastic pollution in aquatic environments. Researchers found that combining advanced detection methods with underwater robotic platforms offers a promising pathway for real-world microplastic monitoring and removal, particularly in deep or inaccessible marine and freshwater systems.
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.
PENGUIN
PENGUIN is a proposed autonomous underwater vehicle system designed to detect and classify plastic pollution at high spatial resolution beneath the ocean surface. Current methods for finding underwater plastics are too slow, limited, or impractical for large-scale monitoring.
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.
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.
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.
In-situ detection of microplastics in the aquatic environment: A systematic literature review
This systematic review evaluates emerging technologies for detecting microplastics directly in water environments without needing to collect samples and bring them to a lab. Developing reliable in-situ detection methods is important because current lab-based approaches are slow and expensive, making it difficult to track where microplastics are concentrated in the water systems that supply drinking water and seafood.
Marine Intelligent Technology as a Strategic Tool for Sustainable Development: A Five-Year Systematic Analysis
This review surveys marine intelligent technology—including autonomous underwater vehicles, sensor networks, and AI-based monitoring systems—as strategic tools for sustainable ocean management, including microplastic detection and marine pollution surveillance.
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.
Oceanography in the Age of Intelligent Robots and a Changing Climate
Researchers reviewed how robotic and artificial intelligence technologies are transforming ocean exploration, including monitoring of marine pollution such as microplastics. The study highlights how autonomous systems are enabling unprecedented data collection on marine chemistry, physics, geology, and biology, supporting long-term environmental monitoring efforts.
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.
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.
The Project of an Autonomous Microboat with a Laser Device for Estimation of Water Area Pollution by Microplastic
This paper describes the design of an autonomous microboat equipped with a laser device for real-time detection and mapping of microplastic pollution in water bodies. Autonomous sensor platforms that can survey large water areas for microplastics could significantly improve environmental monitoring capabilities.
Addressing Microplastic Environmental Data Gaps Through Undergraduate Research
This study proposes using underwater vehicles and standardized sampling protocols to fill data gaps on microplastic distribution in undersampled aquatic environments. The approach aims to improve spatial coverage and consistency in global microplastic monitoring datasets.
State of the Art Offshore In Situ Monitoring of Microplastic
This review examines state-of-the-art technologies for in situ offshore monitoring and detection of microplastics in seawater, addressing the cost and time inefficiencies of conventional manta net sampling followed by laboratory analysis. The review assesses emerging sensor-based and optical systems capable of real-time microplastic detection in coastal and open ocean environments.
Marine Robots: From Laboratories to the Real Underwater Adventure [From the Guest Editors]
This paper is not about microplastics. It is an editorial introduction to a special issue on marine robotics, discussing advances in autonomous underwater vehicles, biomimetic technology, and artificial intelligence for ocean exploration. The study focuses on marine robot technology rather than plastic pollution or environmental contamination.
Unmanned Vehicles System Utilizing Waste Tracking Data to Tackle Plastic Marine Littering on Tourist Islands
This paper proposes using unmanned vehicles guided by waste tracking data to collect plastic marine litter around tourist islands. Autonomous cleanup technology could help remove plastic debris before it breaks down into microplastics and enters the food chain.
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.
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.
“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.
Artificial intelligence for modeling and reducing microplastic in marine environments: A review of current evidence
This review examines how artificial intelligence is being applied to address marine microplastic pollution, including modeling accumulation zones, developing real-time detection systems using remote sensing and robotics, and creating AI-based filtration technologies. The study suggests that while AI holds significant promise for predicting microplastic flows and supporting targeted cleanup efforts, challenges remain around data availability, model refinement, and international collaboration.
Understanding and mitigating global change with aquatic sensors: current challenges and future prospects
This paper is not about microplastics. It reviews the use of autonomous in-water sensors for environmental monitoring, discussing challenges like sensor calibration, fouling, drift, and data quality in the context of tracking global change impacts on aquatic ecosystems. While sensors could potentially be applied to monitor microplastic pollution, the paper focuses broadly on sensor technology for water quality parameters rather than on microplastics specifically.