On Efficient Data Sharing for Planetary Digital Twins: Distributed Microplastic Monitoring

Massive garbage patches within all oceanic gyres have garnered global attention, underscoring microplastic pollution as an emerging concern. Various isolated approaches have been proposed for real-time monitoring of microplastics in environmental and industrial settings. However, these fragmented solutions may hinder distributed data and knowledge sharing across applications, limiting the potential for leveraging AI development to enhance early warning systems and decision-making in large-scale industrial operations. To address these challenges, this paper introduces a framework that utilizes Planetary Digital Twins (PDTs) and affordable modular flow cytometry tools. These innovations enable the real-time tracking and sharing of data on microplastic pollution, tracing their origins from polymer-based industrial processes to their presence in the environment. The proposed framework includes a distributed system architecture based on publisher/subscriber for robust and scalable data sharing. By integrating Industry 5.0 principles, which prioritize sustainability and resilient production processes, the digital twin technology enables a dynamic and interconnected monitoring network. The validation results suggest that the proposed system has the potential to expand and enhance environmental risk assessments on a global scale and support the development of mitigation strategies through improved data integration and sharing capabilities for microplastic monitoring.