Research on Intelligent Management of Campus Water Supply System under the Background of Big Data

Abstract

This article uses Excel to preprocess the readings of smart water meters in the four quarters of a university, filter and delete invalid data, and divide 91 water meters by quarter, month and different functional areas into 6 major functional areas. Then get the characteristics of water use in different functional areas. Next, horizontal analysis and vertical analysis are carried out for the relationship between water surface levels. Descriptive longitudinal statistical analysis of big data is carried out through spss software, and then based on correlation analysis and regression analysis, the horizontal relationship model of water surface level is established, the multiple linear statistical regression prediction model is obtained, and the error analysis model between the predicted value and the actual data is established. Finally, the three steps of discovering leakage, determining the location, and repairing the leakage point are used to solve the problems in the campus water supply system, reduce the leakage of the campus, determine a reasonable water use rule, and solve the problems in the intelligent management of the campus water supply system. The purpose of improving campus services and management.