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61,005 resultsShowing papers similar to An IoT Based Low-Cost Optical System for Early Detection of Microplastics in Water Sources
ClearAn IoT Based Low-Cost Optical System for Early Detection of Microplastics in Water Sources
Researchers developed a low-cost device that can detect tiny plastic particles (microplastics) in drinking water using simple LED lights and sensors, which could make testing much cheaper and easier than current lab methods. This matters because microplastics are found in water supplies worldwide and may pose health risks, but expensive testing equipment has made it hard to monitor water quality regularly. The study shows this simpler technology could work, potentially helping communities better track plastic pollution in their water sources.
Survey on IoT Based Microplastic Detection
This research review summarizes new technology that uses internet-connected sensors to detect tiny plastic particles (microplastics) in water in real-time, rather than relying on slow lab tests. Microplastics are a growing health concern because they can get into our drinking water and food chain, potentially harming human health. Better detection methods could help protect our water supplies by catching pollution problems faster.
Real-time detection of microplastics in aquatic environments using emerging technologies
Researchers proposed a real-time microplastic detection system combining AI-enhanced optical sensors and IoT devices, capable of automatically classifying microplastics in ocean water without the time-consuming manual steps required by spectroscopy or microscopy.
IoT-Driven Image Recognition for Microplastic Analysis in Water Systems using Convolutional Neural Networks
Researchers developed an IoT-based system using artificial intelligence to automatically detect and count microplastics in water samples through image recognition. The system uses cameras at distributed sensor points to continuously monitor waterways and can identify microplastics of different sizes, shapes, and colors. This technology could improve environmental monitoring of microplastic pollution in real time, helping communities and agencies respond faster to contamination threats in drinking water sources.
Tracking microplastic pathways: Real-time IoT monitoring for water quality and public health
Researchers developed a low-cost, IoT-enabled system called TEMPT for real-time microplastic detection in water using turbidity sensors. The accompanying algorithm achieved 91.47 percent accuracy in identifying microplastic contamination, outperforming conventional methods. The study demonstrates how affordable sensor technology could enable large-scale monitoring of microplastic pollution in diverse water bodies.
Development of an Iot-Integrated AI System for Microplastic Detection in Water Samples
Researchers developed an IoT-integrated AI system using high-resolution microscopy, a Raspberry Pi platform, and machine learning to detect and classify microplastic particles in water samples in real time via MQTT, achieving detection accuracy exceeding 95% in simulated dataset validation.
Microplastics Detection in Soil and Water: Leveraging IoT Technologies for Environmental Sustainability
Researchers explored the integration of IoT sensor technologies for detecting and monitoring microplastics in soil and water environments, proposing a connected sensing framework for real-time environmental surveillance. The system enables automated data collection and remote monitoring of microplastic contamination.
Zero-plastic: AI-assisted sensing for microplastic assessment
Scientists developed a new device that uses artificial intelligence and microscopy to detect tiny plastic particles (called microplastics) in water. The prototype can spot plastic pieces as small as 3 micrometers - much smaller than the width of a human hair - which could help us better monitor plastic pollution in our water sources. This matters because microplastics are everywhere in our environment and may pose health risks, but until now they've been very difficult to measure accurately.
IoT-Integrated Image Recognition System for Microplastic Detection and Classification
Researchers developed an IoT-based system that combines a microscopic camera with a YOLOv8 deep learning model to detect and classify microplastics in real time, including types like LDPE, PE, PHA, and PS. The system achieves high accuracy across diverse environmental conditions and visualizes data through a cloud-based dashboard. This scalable approach offers a practical tool for monitoring microplastic pollution, with potential for future integration on marine vessels.
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.
Optofluidic light-droplet interaction for rapidly assessing the presence of plastic microspheres within aqueous suspensions
Scientists developed a new device that can quickly detect tiny plastic particles (called microplastics) in water by shining light through water droplets and measuring how much light gets blocked. The device can spot extremely small amounts of plastic pollution - even particles smaller than the width of a human hair. This technology could help us better monitor plastic contamination in drinking water and the environment, which is important since these tiny plastics can harm both ecosystems and human health.
Optofluidic light-droplet interaction for rapidly assessing the presence of plastic microspheres within aqueous suspensions
Scientists created a new device that can quickly detect tiny plastic particles (called microplastics) in water by shining light through water droplets and measuring changes in brightness. The device can spot extremely small amounts of plastic pollution - as little as 0.13 milligrams per gram of water. This technology could help us better monitor plastic contamination in our drinking water and environment, which is important since these tiny plastics can harm both ecosystems and human health.
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.
A solution for controling microplastics in drinking water
Researchers developed and tested a system for controlling microplastic contamination in drinking water, reporting on removal efficiency at levels relevant to public health. The approach offered effective microplastic reduction from drinking water sources including tap and bottled water.
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.
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.
Economical and Novel Microplastic Detection Using a Arduino-Based Turbidity Sensor: A Comprehensive Investigation
Researchers developed a low-cost Arduino-based turbidity sensor system for microplastic detection as an accessible alternative to expensive FTIR and Raman spectroscopy methods. The sensor demonstrated the ability to detect microplastic-induced changes in water clarity, offering a practical monitoring tool for low-resource settings and smaller waterways that are typically undersampled.
Identifying microplastic contamination in drinking water: analysis and evaluation using spectroscopic methods
Researchers developed analytical methods to identify and quantify microplastic contamination in drinking water, evaluating extraction efficiency and detection accuracy across different water types and plastic particle sizes. The study assessed health implications based on measured plastic loads in treated water.
Towards online monitoring of water pollutants: an optofluidic chip for characterizing microplastics in water
Researchers developed a miniaturized, low-cost optofluidic chip for online monitoring and characterization of microplastics in drinking water, enabling real-time detection without sample pre-concentration. The smart chip design integrated optical and microfluidic components to identify and size microplastic particles, demonstrating feasibility for continuous water quality surveillance.
Life is Plastic? Detecting the Presence of Micro-Plastics in Food and Drink Containers
Researchers developed a novel wearable optical sensing system to detect the presence of microplastics in food and drink containers. The study highlights that humans may ingest significant quantities of microplastic fragments weekly, and demonstrates a low-cost approach using micro-controllers and signal processing for real-time microplastic detection.
Cost-Effective and Wireless Portable Device for Rapid and Sensitive Quantification of Micro/Nanoplastics
Researchers developed a wireless portable device for rapid quantification of micro- and nanoplastics in water samples, offering a field-deployable alternative to laboratory-based analysis for environmental monitoring.
Low-cost IoT based system for lake water quality monitoring
This study built a low-cost sensor system using Internet of Things technology to monitor basic water quality parameters like turbidity, pH, and dissolved oxygen in lakes. While not focused on microplastics specifically, affordable real-time water monitoring tools like this could eventually be adapted to track microplastic contamination. Better water quality monitoring is an important step toward understanding and reducing the pollutants, including microplastics, that end up in drinking water sources.
Droplet-based Opto-microfluidic Device for Microplastic Sensing in Aqueous Solutions
Researchers developed a microfluidic device using light to detect plastic microspheres in water droplets, offering a new tool for identifying microplastic contamination in aquatic environments.
Size- and Concentration-Resolved Detection of PET Microplastics in Real Water via Excitation–Emission Matrix Fluorescence Quenching of Polyamide-Derived Carbon Quantum Dots
Scientists developed a new method to detect tiny plastic particles (called microplastics) in drinking water using special fluorescent dots that dim when they encounter plastic pollution. The technique works best at finding very small plastic pieces—smaller than the width of a human hair—which are hardest to detect but potentially most dangerous since they can get into our bodies more easily. This could help monitor plastic contamination in tap water and other water sources we use daily, giving us better information about our exposure to these harmful particles.