Integrated Environmental Monitoring Information System for the Caspian Sea

Abstract

This article proposes a holistic Environmental Monitoring Information System (EMIS) designed to assess and manage ecological conditions along the northern coast of the Caspian Sea. By integrating multiple data sources—sensor networks, remote sensing, meteorological data, and machine learning algorithms—the EMIS delivers real-time insights into water quality parameters, hydrocarbon pollution, and habitat stability. A scalable, modular architecture ensures that diverse datasets are synthesized into unified, actionable the information, enabling stakeholders to detect anomalies, forecast pollution trends, and identify potential ecological risks. Rigorous data validation processes mitigate discrepancies arising from sensor drift or transmission failures, thereby enhancing reliability. The system also features a cloud-based infrastructure and role-based user interfaces tailored to local requirements, the fostering collaborative decision-making across government agencies, industry operators, and local communities. This study delineates the technical blueprint of the EMIS, documents pilot test outcomes, and highlights implications for sustainable resource utilization and regional environmental policy development.