Study On The Scale,layout And Commercial Form Of Canteens In Suburban Campus Through Behavior Data Mining

Canteen is one of focus of the university campus planning,but in recent years the study of university canteen is more focused on building design.The researches have not paid enough attention to the characteristics of suburban university,and there are few systematic studies on the scale,layout and commercial form of the canteen.Big data technology provides a new means of data collection for the research of time and spatial behavior,and it breaks the limitations of traditional survey sample.The campus card and mobile internet data can reflect the time and spatial behavior of students with a little treatment,which record the students' daily behavior.And then applied to the design and planning of campus canteen.This study is based on the campus card data,wireless network connection data,meteorological observation data of Minhang Campus of Shanghai Jiao Tong University.By using the Big data processing method,the study build the association of different data collections to reproduce the students' dining behavior.Questionnaire survey method is used to get the satisfaction index in the layout,scale and commercial form of canteen.And only when combined with the index and the dining behavior,can we have an in-depth quantitative analysis of the campus' s scale,layout and commercial form,find out the existing problems and propose the solutions on the planning level and strategic level of smart campus design.On this basis,the research results will be promoted and advise the planning and design of suburban university canteen on the aspect of scale,layout and commercial form.Besides,the research will put out some constructive comments on strategic level of smart campus design and make a reasonable forecast of the future development trend of the university canteen.This study explores the application of big data in a feasible way of the planning and design,expands the planning and design practitioners' horizon,and provides new data sources,new tools and new methods to traditional planners on geographic spatial cognition.