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Related Experiment Video

Updated: Jan 16, 2026

Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris

Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris

Published on: July 28, 2018

Advancing microplastic pollution management in aquatic environments through artificial intelligence.

Mudita Nagpal¹, Krrishika Gupta¹, Tanisha Gupta¹

¹School of Engineering & Technology, Vivekananda Institute of Professional Studies-Technical Campus, Delhi, 110034 India.

Journal of Environmental Health Science & Engineering

|September 26, 2025

Summary

Artificial intelligence (AI) and robotics offer advanced solutions for tackling microplastic pollution in aquatic environments. These technologies enhance the collection, characterization, and monitoring of microplastics, protecting ecosystems and human health.

Keywords:

Artificial intelligence Characterization Degradation Microplastics Sorting

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Sampling and Identification of Microplastics in Groundwater

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Area of Science:

Environmental Science
Marine Biology
Robotics
Artificial Intelligence

Background:

Microplastic (MP) pollution poses a significant threat to marine biodiversity, ecosystems, and human health.
Traditional methods for MP identification and characterization are labor-intensive and time-consuming.
Integrating AI and robotics presents a promising approach to mitigate MP pollution.

Purpose of the Study:

To review the application of AI and robotics in addressing microplastic pollution.
To highlight the benefits and insights of AI-driven approaches in MP management.
To discuss successful initiatives and future research opportunities.

Main Methods:

Review of emerging robotics and AI models for MP collection, sorting, and characterization.
Analysis of AI applications in predicting and monitoring MP degradation.
Examination of global initiatives and policies for MP pollution control.

Main Results:

AI and robotics significantly improve the efficiency and accuracy of MP detection and analysis.
These technologies aid in understanding MP abundance, size, and chemical composition.
AI facilitates the prediction and monitoring of MP degradation processes.

Conclusions:

AI and robotics are crucial tools for effective microplastic pollution mitigation.
Successful global initiatives demonstrate the potential of these technologies.
Further research is needed to overcome challenges and optimize AI/robotics integration for cleaner aquatic environments.