With continuous development of Internet of Things (IOT), sensor network has been widely applied and become the vital infrastructure of information technology. Specially, the dynamic sensing information provided by the sensor network plays a key role for various intelligent applications in support of information retrieval as well as decision-making. However, since the real-time information requirements are less likely to be transformed into simple sensing queries well matching the low-level sensor query interface, it is hard for those intelligent applications to accurately obtain decision related information online from the sensors. To address this challenge, this paper presents a semantic overlay model with semantic resource description, reasoning and applications for IOT. In addition, an application for the decision making of multi-agent system is deployed to manifest how IOT information techniques can improve agents’ decisions. The key of this approach is the team-oriented plan for agents’ task decompositions. By decomposing the complex task into simple subtasks, their information requirements can be mapped into accurate and sufficient sensor queries with ontological reasoning. Therefore, a real-time decision support system can be established so that task related quires can be accurately allocated to the sensors with best corresponding sensed information for accomplishing agents’ task.%随着物联网技术的不断发展，传感器网络得到了广泛的应用并成为信息技术领域重要的基础设施。尤其是传感网络提供的实时感知信息，为许多智能应用提供了充分的信息支持和必要的决策依据。然而，由于智能应用的实时感知信息需求通常无法转化为简单的查询请求与传感器底层查询接口准确匹配，因此，基于物联网的智能决策常常无法准确获取到决策相关的实时信息。针对此问题，提出一个基于语义覆盖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，研究了新型物联网环境下的多智能体决策信息支持技术。该技术以基于多智能体系统的团队导向规划的任务分解方法为核心，将复杂任务分解为若干简单子任务，并基于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、完备的传感器信息查询，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。
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