Scalable Geo Web Techniques using Spatial Data Mining for Air Pollution (International Journal of Advanced Research in Computer Science, 2017)
This paper proposes to bolster Geo Web Techniques and spatial data mining techniques for air pollution in Delhi-NCR for real time analysis and identification of relationship among the pro &anti pollutant objects effecting in a specific zone of area. A Geo Web based solution is proposed by provisioning of feature and attribute data services over the web. The functional constituents are collection, transformation, Spatial Data Mining, OGC Web Services i.e. Web Map Service (WMS),Web Feature Service (WFS) ,Web Coverage Service (WCS) query and Geo Web Publishing elements. The collecting element provisioned to access the onsite monitored data through a interface with sources of actual data sets . It need to transform the data into the required spatial format and mining component give an interface to the end user. Spatial information mining systems can be connected to different fields' specifically human services, metrological information, activity examination, client insight, transport administration, urban arranging and utilities industry. Albeit spatial data mining does not yet belong to the most commonly used spatial information analysis, it was found effective to detect solid relationship among geological feature objects. Keywords : Spatial Data Mining, Geo Web, Web Map Service (WMS) , Ambient Air Quality