Watertech has access to many sensors spread across many companies that are used to monitor water coming into and going out of various systems. The goal of this solution is to enable a user to visualize the data collected by each of these sensors over time, and break the data down into a hierarchy defined by Company, Facility, Building, and System. We have created a system the models the structure and provides an interface to import sensor data, and a dashboard web application that lets a user select and graph individual sensors from any combination of items in the hierarchy on the same graph. These graphs can be evaluated within the application or exported to images or to CSV files that allow further analysis. Ultimately the goal is to provide a tool that allows users to evaluate their water usage and compare it to their production and to production of other companies in the same industry. This would allow companies to make more environmentally conscious decisions and create metrics about the water cost per unit of product made.
We chose this problem because the problem had lots of documentation, which included a sample dataset, sample screenshots, and a list of desired features. We believe that the ability of a company to do this kind of analysis on their own data, and relate it to their bottom line, and create metrics they can use for PR, make it to a companies advantage to do good things in terms of water use and reduction of consumption.
We built a data model that encompasses the entire hierarchy and structure of the incoming sensor data and in a format that will allow for the analysis in the ways desired. We created an application using ruby on rails and jquery and the graphic library highcharts that allows users to select from the hierarchy of sensor data and visualize the sensor data in time and compare it with other sensor data in the same graph. The users can export the data. We built an importing script that takes the sample datasets and imports them into the data scructure.
N/A
Watertech representatives were present to assist in development of the data model and demonstrate the problems they were trying to solve.