Application of Density Based Clustering Algorithm in Pharmacy

Abstract

At present in the pharmacies may or may not have stock details and also due to current hike in the prices of medicines because of GST, people are unaware of the uses and also the prices of medicines. So people has to go to the pharmacy directly to know the status of the medicines. Time, money are being wasted. This applications enable users to view the pricelist, medicines in stock and location of pharmacies. If users search required medicines, this application returns pharmacies with optimal total cost (possibly low) and distance are returned as output.

 The Scheme “Application of Density Based Clustering algorithm in pharmacy” using dynamic clustering of data with DBSCAN algorithm. The algorithm can be used in such a way that it takes the input and first searches in the available datasets. But it cannot be applies to large datasets. So we go for DBSCAN algorithm which is known density based spatial clustering algorithm.

Here the similar available datasets have been grouped and pre-processed before searching and the remaining datasets have been termed as noise. Pharmacies the location and range are taken as input and also the cost of each medicine available in it. These grouped datasets will be searched for the feasible solution.

The application of DBSCAN algorithm works for the overall feasible solutions in a particular area and if not enough, it searches the next cluster which is termed as the noise. Here the optimal solution based on distance of shop and cost of medicine have been obtained by using this algorithm. The DBSCAN algorithm ranks pharmacies based on distance and the additional filter is applied to rank pharmacies based on price constraint. Hence, the people could not be exploited as they know the best price medicine available in the nearest shop