This diploma thesis focuses on the design and implementation of a solution for the collection, integration, and visualisation of real-time data from sensors monitoring river systems and catchment areas. The work will build on the Time.IO solution developed at the Helmholtz Centre for Environmental Research in Germany. It will adapt and extend it for the data-management and data-processing infrastructure being developed for the Czech University of Life Sciences Prague (CZU). The resulting system will primarily address CZU-specific use cases related to data acquisition from sensors deployed across different projects, including support for both online and offline data ingestion, transformation of heterogeneous data from devices of different manufacturers and communication protocols, and integration of sensors and measurements into project-oriented data structures. At the same time, the solution will be designed with sufficient generality and extensibility to enable its future deployment within the European eLTER research infrastructure, where it will support analogous scenarios of online data acquisition and integration from measuring sensors.

An important part of the thesis will be the analysis of the existing software components provided by the UFZ solution, their decomposition, and their suitable integration into the target architecture. The student will implement an integrated solution and create a new graphical environment supporting multilingual deployment and the required functionality, including, among others, data ingestion, sensor and project management, data quality assessment, batch imports, configurable visualisation portals, and access control. The thesis will describe the proposed architecture, adaptation strategy, and implementation approach. It will evaluate the suitability of the resulting platform for environmental monitoring scenarios in the CZU context and discuss its deployment within the eLTER research infrastructure.