Web App for Dynamic Pricing Modeling in Automotive Applications and Data Mining Analytics

In this paper the authors propose a web application oriented on business to business (B2B) and internet automotive marketing. The study case is related to an industrial project concerning tires recognition application and real time comparison of prices of competitors. By means of a smartphone camera able to identify and classify car plates, the system provides different associations of compatible tires for a specific car model and the best prices. The frontend system is based on Optical Character Recognition (OCR) method and the backend works on automatic extraction of competitor prices from different databases and from internet network. The dynamic pricing is due to the best price choice related to period of car plate recognition. The price choice is supported by data mining processing performed by a k-Means workflow. The paper summarizes the results of a research industrial project. The used approaches could be used for different automotive applications involving market of different car parts.