Simple clustering cloud application with 2D vizualization in C#

Goal: - implement k-means, k-means-optimized, k-medoid clustering methods on given dataset. Description: - imagine a smart house with couple of sensors (temperature, light, humidity, gas). Each log is represented by this parameters. { "id": "6181090c", "idDevice": "0080", "type": "light", "atLocation": "KITCHEN", "Place": "TABLE", "timestamp": "1448641782", // represent point X coordinate "status": "0025", // represent point Y cooridinate }, Points: - Convert/Parse JSON format into SQL table - Implement/copy code calculations of k-means, k-means-optimized, k-medoid on dataset - Filter input clustering data entering from title screen by user o Select cluster by „type“ (drop down list) o Input count of centroids (textbox) o Select cluster method (drop down list) - Show result o visualize/show simple 2D map result o Start layout with points and random centroids positions o Final layout with points clustered and centroids positions - Publish application on Azure, I will give you credentials - Welcomed are your suggestions Instructions: Please comment the code: objects, functions, classes, calculations to help me understand whole project. I would like you to show the final project using voice call and screen sharing. Please do your best at begin to use my sources or find better by your side, no need to create unique code, feel free to copy and find most comfortable solution for you and best price for me :)