The decreasing prices of monitoring equipment have vastly increased the opportunities to utilize local data, and data processing for wider global web-based monitoring purposes. The possible amount of data flowing though different levels can be huge. Now the question is how to handle this opportunity in both dynamic and secure way. The paper presents a new concept to manage data for monitoring through the Internet. The concept is based on the use of Arrowhead Framework (AF) and MIMOSA data model, and selected edge, and gateway devices together with cloud computing opportunities. The concept enables the flexible and secure orchestration of run-time data sources and the utilization of computational services for various process and condition monitoring needs.

The introduction of new sensors and affordable measurement devices increases the amount of data used in cyber-physical systems and various sensing applications. These systems often grow extensive encompassing not only different kinds of data sources and sensors but also different kinds of use cases for the data. This paper presents a sensor system application architecture outlining the requirements on software and interfaces for connecting different kinds of measurement devices, executing computational functions on various hardware platforms, and connecting this information to various use case applications. Key objectives for the concept include dynamic orchestration of information flows and flexible configuration where computational functions are executed, support for different data sources and hardware, and utilization of computational resources on all levels from edge to cloud. The system application architecture designed is considered for two application domains within the Industry 4.0 paradigm.