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IoT Driven Smart Innovation for Microplastic Monitoring and Detection: A Multidimensional Review
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This review evaluates IoT-integrated systems for real-time microplastic monitoring and detection in water, covering sensor technologies, predictive modeling, and risk assessment frameworks applied to common polymer types including PP, PE, PVC, and PET. Scalable IoT-based detection infrastructure could transform environmental monitoring from periodic sampling to continuous surveillance, enabling faster regulatory response to microplastic contamination events.
The rapid demographic expansion has led to a substantial increase in demand for water across the industrial, agricultural, and domestic sectors, further intensifying the challenges of water scarcity, pollution, and management costs. Traditional water management technologies face limitations, including operational failures, high energy consumption, and elevated costs. To tackle these issues, recently, the “Internet of Things” (IoT) has introduced innovative solutions for smart water management, enabling real-time monitoring, precise detection, and efficient control of water resources. This review article focuses on the key parameters of microplastic pollution, exploring the impact of microplastic types such as polypropylene (PP), polyethylene (PE), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) on aquatic systems. The integration of IoT technologies with predictive modeling and risk assessment offers promising benefits by enabling real-time monitoring, precise detection, and effective management of these emerging contaminants. A comparative literature survey highlights current approaches, their limitations, and recent advancements in IoT-based systems for microplastic detection and water quality assessment. This review discusses the challenges, opportunities, and future directions of IoT-enabled microplastic detection, highlighting its role in enhancing water security and addressing global concerns of pollution, scarcity, and climate change.
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