• Karan
• Harjinder Kaur

Microplastic pollution presents a significant threat to aquatic ecosystems, biodiversity, and public health. These microscopic plastic fragments, typically less than 5mm in diameter, originate from diverse sources such as industrial discharge, synthetic textiles, personal care products, and the degradation of larger plastic items. Their minute size makes detection and removal from water systems exceptionally difficult, and conventional methods—such as spectroscopic analysis and filtration—are often expensive, time-consuming, and inefficient for large-scale applications. Recent developments in artificial intelligence (AI) offer promising solutions for enhancing microplastic detection and environmental management. Machine learning and deep learning, particularly convolutional neural networks (CNNs), have proven effective in analyzing images from electron microscopes and remote sensing platforms. These models enable automatic identification and classification of microplastic particles based on their size, shape, and composition, significantly improving detection accuracy and efficiency. AI-assisted spectroscopic methods, including Raman and FTIR spectroscopy, support rapid and non-invasive analysis of polymer types, aiding in pollution source identification. Furthermore, AI supports pollution control through predictive modeling of contamination hotspots and optimization of waste management strategies. Robotic technologies and autonomous underwater vehicles equipped with AI algorithms can detect and extract microplastics in real time, adapting to dynamic aquatic environments. While AI presents clear advantages, challenges such as limited training data, standardization issues, and high computational requirements must be addressed. Continued research and collaboration across disciplines are essential for improving AI models and enabling practical, energy-efficient deployment. Ultimately, AI-driven approaches represent a transformative step toward sustainable microplastic pollution mitigation in aquatic environments.

AI,CNN, Micro plastic Pollution, FTIR and Raman Spectroscopy

"Artificial Intelligence for Microplastic Detection and Pollution Control in Aquatic Ecosystems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.e262-e265, June-2025, Available :http://www.jetir.org/papers/JETIR2506427.pdf

"Artificial Intelligence for Microplastic Detection and Pollution Control in Aquatic Ecosystems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. ppe262-e265, June-2025, Available at : http://www.jetir.org/papers/JETIR2506427.pdf