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.