Design And Implementation Of Business Process-Aware IoT Service Model

In recent years,with the help of the Internet of Things(IoT),traditional systems are gradually evolving into a new form of convenient interaction and integration among people,machines,and things.There exists a large class of process-aware information systems(PAIS)supported by business process management(BPM)in the industry,which has the potential to provide business logic and programming paradigms for IoT.Meanwhile,IoT can help PAIS capture physical world changes quickly and accurately and make timely responses.However,IoT entities have heterogeneity in terms of data,protocols,and their data is continuous,while traditional PAIS lacks strict time semantics,and its event interaction mechanism is only suitable for discrete events,making it difficult to efficiently process continuous events.In the context of these problems,this thesis’ s main contributions are as follows:First,this thesis proposes a new IoT service model to address the current difficulty of integrating business processes with the IoT.The model is designed based on an event publish/subscribe mechanism,which encapsulates the processing logic of heterogeneous streaming IoT data to generate business events that PAIS are interested in,reducing the cost of directly processing massive IoT data by business processes.The significant feature of this model is its ability to process and respond to IoT events continuously,and enable business processes to sense the physical world through IoT services by extending the business process modeling component.Finally,the feasibility of the IoT service modeling method is validated through a real case and experimental study of the LNG(Liquefied Natural Gas)logistics safety supervision system.Assuming that you are a reviewer for a scientific journal,please translate this paragraph into English according to standard English rules.Second,to address the problem of the IoT service model’s inefficient processing of raw IoT data during the execution process,this thesis proposes a K-I(Kalman-IoT Services,KI)model combined with IoT services based on the Kalman filter.The model improves the efficiency of the IoT service model in processing massive IoT data by filtering IoT data.The experimental results show that although the introduction of this model reduces the event recognition accuracy by about 2%,it increases the overall efficiency of the IoT service by about 15%,further validating the superiority of the K-I model.Third,a prototype system for IoT service modeling tools is implemented,providing functionality for physical entity modeling,IoT object and IoT service modeling.The implementation of this prototype system verifies the feasibility and effectiveness of the IoT service model and method proposed in this thesis,providing technical support and assurance for the practical application and promotion of the IoT service model.