In order to solve the problem of resource waste in colleges and universities, this paper proposes a multidimensional situational information fusion method, which can be used to normalize, analyze and predict the multi-source data such as natural, humanistic and spatio-temporal data on campus so as to meet the application requirements for high-level decision-making. With this method, firstly, the event object model is used to normalize multi-source data. Then, the multidimensional situational information fusion mechanism of twice reasoning is used to obtain the real-time situation and equipment control scheme of the campus so that real-time intelligent semantic understanding is realized. In the process of reasoning, the improved KNN prediction model is used to predict situational trends, and the prediction information is used to continue deep reasoning and mining. Finally, the real-time energy-saving regulation is carried out through control instructions. In addition, through simulation verification, experimental results show that this method can quickly identify, integrate, and predict the current real-time situation and generate reasoning results, and finally achieve the goal of intelligent control for energy saving on campus.
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