StreamHandler as a Real-Time Decision Support System for Environmental Monitoring in Digital Twins of the Ocean

Digital Twins of the Ocean (DTOs) are virtual replicas of marine environments that integrate observational data, models, and simulations to represent ocean conditions and processes, aiming to support informed decisions for blue economy, as well as societal and environmental concerns. While DTOs traditionally rely on in-situ measurements and model outputs, we observe an increasing need for the inclusion of real-time data streams to support operational decision-making in dynamic maritime environments. This paper presents StreamHandler, a distributed event streaming platform designed to enhance DTOs with improved situational awareness and real-time environmental monitoring capabilities. StreamHandler bridges the gap between conventional DTO implementations and the need for timely decision support. Built on Apache Kafka, it fosters seamless integration of heterogeneous marine sensor data, sophisticated alert generation based on customisable thresholds, and direct triggering of oceanographic models. The platform implements enterprise-grade security features, bidirectional MQTT-Kafka communication, and MongoDB-based data storage to ensure reliability in harsh maritime conditions. We demonstrate StreamHandler’s effectiveness through its implementation in multiple maritime pilot deployments within the EU-funded Iliad project, with particular focus on the harbour safety monitoring DTO in Crete, Greece. Furthermore, we present StreamHandler’s interoperability with the European Digital Twin of the Ocean (EDITO) storage infrastructure, highlighting its potential for broader application across diverse maritime contexts. Our results demonstrate that StreamHandler complements traditional DTO approaches by providing a scalable, secure, and effective foundation for informed decision-making through the integration of real-time monitoring.