Research On Key Technologies Of Interoperation For Human-centric Industrial Internet Of Things

Issues of integration between human and manufacturing environment have been resolved by vary Industrial Internet of Things(IIoT)systems.However,there are still a lot of challenges on local crowding service discovering and connecting in humanIIoT Interoperation,such as(a)the spatiotemporal dynamic issues of service modeling and requests capturing on the stage of service request launching,(b)The issues of congestion and balance in decentralized service discovering on the stage of service discovering and(c)The overload and random issues on the stage of crowding wireless devices probing on the stage of service connection.The work focus on directly interoperation among local services,workers in smart factory,and proposes several technologies on services integration,service discovering,and service connecting of human-IIoT interoperation.The main contributions are as following:(1)A social device-to-device(Social D2D)architecture of human-IIoT service interoperation is presented.For requirement of human-IIoT directly interaction in the decentralized environment of smart factory and the issue of service space-time identification and tracking,considering machine social networks,a social D2 D architecture of IIoT is proposed.Moreover,based on the proposed architecture.In addition,introducing middleware technology of smart objects,a human-centric middleware of human and IIoT service interrogation is presented.Moreover,a mechanism of decentralized space-time dynamic service link and interoperation recodes storage is presented.(2)An algorithm of location-driven on-demand service discovery is presented.For the inter relevance of human requests and IIoT service and congestion of service providers,a mapping system of request-service in human-IIoT interoperation is built.In addition,introducing Multi-agent System(MS)and Artificial Potential Field(APF),a MS-based request potential field model is built.Moreover,considering the factors of location and social distance,an algorithm of location-based on-demand service elected(LOSE)for decentralized IIoT services selection strategy is proposed.The simulation result shows that the proposed method can improve the service balance of human-IIoT interoperation.(3)An implicit social tie-assisted service connection(ISTSC)strategy is designed.For the issue of blindness candidate device scanning because of crowding swarm devices in smart factory,considering the implicit ties in contacts records of human-IIoT,introducing graph theory and Markov Chain prediction model,a modeling method of local dynamic social D2 D graph is presented.In addition,introducing probability contact model and metrics of social networks,an algorithm of implicit social relationship generation is proposed.Moreover,considering the stability of implicit social relations of human-machine devices,an algorithm of ISTSC for human-IIoT interoperation is presented.The experimental results show that the proposed method can significantly improve the energy efficiency in human-IIoT networks.(4)A prototype simulation platform for human-IIoT interoperation is designed.In the view of the lack of interoperability simulating platform for human-IIoT service interoperation,combining with the characteristics of human mobility and historical contact behavior,an open-source framework of theONE and Mason multi-agent simulation toolkit are introduced to build a human-centric IIoT simulation platform.As a classic scenario of implicit interoperation among human and machines,Andon system of automotive parts assembly scenario is introduced,to analysis the workflow of human-IIoT unnormal status feedback and workshop logistic reconfigration,The case study of human-AGV(Automated Guided Vehicle)handling shows that the proposed method can effectively improve the efficiency of industrial human-IIoT interoperation system.