A ternary interaction model of human-machine-object in smart community based on knowledge graph
To achieve a smart community,there is a need for more intelligent approaches to manage and optimize the complex interaction relationships among humans,machines,and objects.knowledge graphs provide a flexible means to design and expand data models according to specific requirements and application scenarios,offering an effective solution pathway.This study,through an examination of the triadic interaction process among humans,machines,and objects in a smart community,devises a collaborative intelligent scheduling method that integrates reinforcement learning.Community data is employed to model the ontology of humans,machines,and objects,resulting in the construction of a collaborative scheduling model for the community,integrated with a knowledge graph.This model is applied to the intelligent property service system of Shounong Dongyuan apartments,encompassing scenarios such as three-dimensional building management and intelligent device maintenance.It resolves resource optimization and management issues and caters to diverse interaction requirements among humans,machines,and objects in different service scenarios within a smart community.
knowledge graphsmart communityternary interaction model
NETL
NSTL
万方数据
