🤖 AI Summary
Traditional Business Process Management (BPM) struggles to unify discrete events with continuous sensor signals from Cyber-Physical Systems (CPS). Existing Signal Temporal Logic (STL)-based hybrid declarative approaches support only retrospective monitoring and lack real-time execution capabilities. To address this, we propose the first three-layer architecture enabling real-time execution of hybrid declarative processes, deeply integrating STL into a Complex Event Processing (CEP) engine. This integration supports joint temporal constraints over discrete events and real-valued signals, proactive activity triggering, and dynamic enforcement of process boundaries. Our approach achieves, for the first time in BPM, STL-driven online execution and closed-loop control—bridging the semantic and execution gap between declarative modeling and real-time physical-world operation. We validate its effectiveness and scalability in智能制造 and Industrial IoT scenarios.
📝 Abstract
Traditional Business Process Management (BPM) focuses on discrete events and fails to incorporate critical continuous sensor data in cyber-physical environments. Hybrid declarative specifications, utilizing Signal Temporal Logic (STL), address this limitation by allowing constraints over both discrete events and real-valued signals. However, existing work has been limited to monitoring and post-hoc conformance checking. This paper introduces a novel Complex Event Processing (CEP)-based execution architecture that enables the real-time execution and enforcement of hybrid declarative models. Our three-layer approach integrates STL-inspired predicates into the execution flow, allowing the system to actively trigger activities and enforce process boundaries based on continuous sensor behavior. This approach bridges the gap between hybrid specification and operational control.