This article first analyzes big data technology. Then, the agricultural Internet of Things system was established, and the acquisition of agricultural data was achieved through the establishment of sensor modules, image acquisition modules, and meteorological acquisition modules. The data are transmitted to the server through GPRS communication technology and 3G network card to realize data transmission. The Web Service technology is used to connect the Internet of Things with the neural network model to achieve data interoperability. By comparing the prediction results and actual data of the model, it is found that the prediction error of the model designed in this article is less than 1%, and the high-precision prediction of agricultural data is realized, which provides an effective guidance for the improvement of agricultural product quality and yield.

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The saving city (SC) evaluation is an important means to promote the construction process of saving city. According to the concept and characteristics of the SC, following the scientific, practical and operational principles, taking the present situation of our country into consideration, the paper firstly puts forward an evaluation index system for SC, which includes 4 levels, 3 subsystems and 25 variables; Secondly, using the multivariate statistical analysis theory, the paper sets up a comprehensive evaluation model based on the Factor Analysis method (FA) for the evaluation of SC; Thirdly, by means of SPSS software system, this paper makes an empirical study based on the actual data of 17 cities in some province. The result shows that: the index system and evaluation model have a good practicability and maneuverability. It will provide means for monitoring and evaluation of the construction of SC for the government and the relevant authorities.