IoT-Integrated Image Recognition System for Microplastic Detection and Classification

Microplastic pollution threatens aquatic ecosystems and public health, requiring innovative detection solutions. This paper presents an IoT-based system combining a microscopic camera with a YOLOv8 model for real-time detection and classification of microplastics, including types like LDPE, PE, PHA, and PS. The system achieves high accuracy, robustness in diverse environmental conditions, and real-time data visualization through a cloud-based dashboard. Challenges like class imbalance and IoT hardware constraints were mitigated using model optimization and advanced preprocessing. This scalable solution offers a practical tool for monitoring microplastic pollution, with future potential for marine vessel integration and enhanced detection using advanced imaging and deep learning methods.