Graduate and Undergraduate Research Topics (For Fall 2014 and Spring 2015): Here is a list of topics, under four separate categories: Biomedical Systems, Internet of Things, Embedded Robotics, and Data Mining for Education.
- Biomedical Systems: Several undergraduate students are taking DIS credits to develop a biosignals lab. Here is the link to their work: http://smartsystems.eng.fau.edu/biomedical-signal-processing/. Dr. Shankar is offering a course on biologically inspired architecture in fall 2014. The syllabus is here. Dr. Shankar has utilized nonlinear dynamics in both biomedical and electronic systems to build innovative solutions.
- Internet of Things (IOT): This is a new field. Dr. Shankar will use open source tools from Eclipse (see http://iot.eclipse.org/) , Rasperry Pi (http://www.raspberrypi.org/), and Arduino (http://arduino.cc/). See Presentations by MOOR and Chris Murphy to appreciate the current IOT challenges – that applications and infrastructure both require better data both quantitatively and qualitatively. The two courses that Dr. Shankar is teaching in Fall 2014 will address this issue from two different perspectives: sensor level and systems level. Dr. Shankar is also developing floor board games using autonomous robots which will use a hierarchical framework of communication and computation between the robots and players with Android phones and Raspberry Pi systems.
- Embedded Robotics: We have developed low cost robots with the intent to make them affordable by middle and high schools. The cost has been brought down to $100. These robots are built with off-the-shelf mass produced components, so they can be easily repaired/maintained. During summer, our effort was on making the robots robust and precise. More can be found here. We also worked this summer on image transmission between Raspberry Pi and Android phone, and distance estimation with Android, both essential steps in building the hierarchical framework mention under IOT. A courseon embedded robotics is planned for Spring 2015 that will unify all this work.
- Data Mining for Education: This is an area with significant funding potential. We have submitted several NSF proposals and funding from local community service providers is being realized. We will use smart phone Apps and wearable computing as avenues to help middle and high school students, and undergraduate students at FAU develop STEM skills. Our goal is to mentor these students and understand mechanisms to help improve their STEM skills so the university can recruit, retain, and graduate more of our local students in STEM programs. There will be resources such as the following to analyze and develop tools for: https://bitbucket.org/shankarfau/profile/teams and http://smart.eng.fau.edu/display/PUB/Mobile+Apps+for+Google+Android