Techniques in Data Visualization for Electrical Engineering: From Embedded Systems to the Internet

Abstract

Many electrical engineering students involved in embedded systems or microcontrollers are able to collect data using various sensors from the environment. The challenge for these students is once they have the data, how to best display or interpret it. There are currently a handful of websites and hardware platforms that offer ways to capture and display data, but the ability for the engineer to fully customize the graphs and manage the storage of the data is not well developed.

It is the goal of this paper to provide an intuitive and easy to code framework for pushing data from an embedded system to a database and then querying the database to display the data in an attractive format. This will provide electrical engineering students and professionals a method to culminate their work. The methods described are universal for any microcontroller or embedded system that is able to transmit data using a TCP/IP stack or some form of radio-frequency communication, allowing for seamless integration into many projects.

This was accomplished using a Linux, Apache, mySQL, and PHP stack on a Raspberry Pi connected to a local area network (LAN) serving as a gateway. The Raspberry Pi is able to receive UDP or TCP packets from an embedded project fitted with a LAN connection or a pair of radio-frequency transmitter/receivers. After data is pushed into the database, flot charts, a JavaScript plotting library, is used in conjunction with PHP to query the database and produce attractive and informative plots of the data. All of the software packages were carefully selected to be open-source and community supported. This allows engineers to use the technology free of cost and with support when a specific issue arises.

Through the use of the framework in this paper, students and professionals will be able to take their projects from local LCD screens and LEDs to the Internet for remote monitoring, higher applications of algorithms on the stored information, and trend tracking over a desired time period.