【摘要】 实现智慧社区需要更智能的方法来管理和优化处理人、机器和物品之间的复杂交互关系。知识图谱可以根据具体需求和应用场景灵活地设计和扩展数据模型，是行之有效的解决途径。该文通过对智慧社区人机物三元交互流程的研究，设计了一种融合强化学习的人机物三元协同智能调度方法，并使用社区数据对人机物本体进行建模，构建了融合知识图谱的社区人机物三元协同调度模型。本模型应用于首农东苑公寓智慧物业服务系统，涵盖了楼宇三维管理、智能设备检修等场景，解决了资源优化和管理问题，适应智慧社区不同服务场景人机物交互需求。更多还原

【Abstract】 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.更多还原