物联网技术的深入发展促使传感器网络得到了广泛的应用并逐渐成为水利领域重要的基础设施。同时,传感网络采集到的实时感知信息,也必然成为闸站等智能应用系统的信息来源和必要的决策依据。引入基于语义模型网的物联网信息资源描述、推理和应用模型,并以多智能体系统决策支持为应用基础,研究了物联网环境下水利闸站调度的智能决策支持技术。该技术采用多智能体系统的任务分解方法,并通过本体推理方法把子任务执行时需要的决策信息转化为精确的传感器信息查询,从而实现从物联网中准确定位具体的传感器并获取相应感知信息的实时决策信息支持机制。
With the development of internet of things technology,sensor network has been widely used and has become important water conservancy infrastructure. At the same time,real-time sensory information collected by sensor networks will inevitably become a source of information for station intelligent application systems and the necessary basis for decision making. For this reason,Things information resource description,reasoning and application model based on semantic model networks was introduced. Station scheduling supported by intelligent decision technology was studied based on multi-agent systems for decision support applications. The technology uses task decomposition method for multi-agent systems,and through the implementation of decision-making information needed to handle the task ontology reasoning accurate sensor information into a query,in order to achieve accurate positioning of things from specific sensors and obtain the corresponding sensory information real -time information to support decision-making mechanisms.