Full integration of semantic stream processing in Industrial IoT/IoE

Establish architectures, methods, and operational frameworks that fully integrate semantic stream processing into industrial Internet of Things and Internet of Everything environments, combining ontology-driven contextual knowledge with distributed real-time stream processing to achieve deep, context-aware data manipulation at scale.

Background

The paper surveys distributed stream processing platforms (e.g., Kafka, Flink, Storm, Spark Streaming) and highlights that, despite performance and scalability, most rely on syntactic data manipulation and lack deep contextual understanding.

Recent research has explored enriching pipelines with semantic models and graphs, yet the authors note that a complete, end-to-end integration of semantics with real-time industrial stream processing has not been achieved, identifying this gap as an open area for further work.