| dc.description.abstract | Industrial systems have been developing into more and more complex systems during
last decades. They have changed from centralized solutions to distributed, more robust,
and more
exible eco-systems comprising a high number of embedded systems.
In recent years, we are witnessing the research trend in the area of embedded systems
which concerns the very close integration of physical and computing systems.
This dissertation thesis deals with the problem of the semantic integration of
components (sensors and actuators) of cyber-physical systems within industrial automation
domain and presents resulting bene ts. Cyber-physical systems were created
based on the aforementioned trend of the close integration of computing systems
and physical systems. This tight integration involves infrastructures responsible for
control, computation, communication, and sensing. These systems are composed
of many subsystems produced by various manufacturers, and the subsystems produce
an enormous volume of data. Furthermore, data generated from all of the
system parts has di erent dimensions, sampling rates, levels of details, etc. Next,
cyber-physical systems form systems which represent building blocks of the fourth industrial
revolution (Industry 4.0) for example (Industrial) Internet of Things, Smart
Cities, Smart Factories. Thus, the right understanding of data (data meanings,
given context, subsystems purposes, and possible ways of subsystems integration)
belong to essential requirements for enabling Industry 4.0 visions. In this thesis, the
utilization of ontologies was proposed to deal with the semantic heterogeneity for
enabling easier cyber-physical system components integration.
Moreover, the current widespread e ort to create
exible highly customized manufacturing
requires novel methods for data handling together with subsequent data
utilization. Storing knowledge and data in an ontology o ers a needed solution. For
example, an ontology employment brings easy system data model management, increase
an e ciency of cyber-physical system components interoperability, advanced
data processing, reusability of sensors and actuators, and utilization of ontology
matching methods for an integration of other data models. This work concerns
the problem, how to describe cyber-physical system components using ontologies
to enable e ective integration. Next, the ontology matching system suitable for
integration of heterogeneous data models in industrial automation domain is described. The proposed solution of the semantic interoperability is demonstrated on
the Plug&Play cyber-physical system components.
On the other hand, storing data in an ontology and mainly processing of RDF
statements brings one signi cant bottleneck | performance issue. Thus, Big Data
technologies are employed for overcoming this issue together with a proposal of
suitable storage data models. The overall approach is demonstrated on the proposed
and developed prototype named Semantic Big Data Historian.
In particular, the main contributions of the dissertation thesis are as follows:
1. The proposal of the solution for CPS low-level semantic integration based
on Semantic web Technologies together with a veri cation of a feasibility of
proposed approach using Semantic Big Data Historian.
2. The overcoming performance issues of processing shop
floor data represented
as RDF-triples with the help of Big Data technologies and suitable storage
data models | vertical partitioning and hybrid SBDH model.
3. The proposal and implementation of a suitable way how to integrate heterogeneous
data models from industrial automation domain where the highest
precision and recall are required. The approach is based on similarity measures
aggregation using self-organizing maps and user involvement with the
help of active learning and visualization of self-organizing map output layer.
4. Enabling reusability of cyber-physical system components together with effortless
configuration based on utilization of Semantic Web technologies. This
approach was named as Plug&Play cyber-physical system components. | en |
