This in-person short course will introduce participants to low-cost computing platforms, sensors, and communication devices that are building blocks of Internet of Things (IoT) high-density networks.
|Participant Cap:||Not Announced|
Low-cost, Internet of Things (IoT) high-density networks are expected to be an important part of future infrastructure designed to harness the data revolution for environmental research and applications including pinpoint detection and prediction of severe weather, health impacts from air pollution, and monitoring of the urban heat island. This short hands-on course will introduce participants to low-cost computing platforms (Raspberry Pi, Arduino), sensors (meteorological sensors, spectrometers, strain gauges, etc.) and communication devices (serial wireless, cell modems, etc.) that are building blocks of such sensor networks. The hands-on part of the course will expose participants to:
This short-course will also cover powering sensors using solar panels and brainstorming exercises on innovative uses of simple sensors to develop new environmental monitoring applications. The course will also feature guest speakers that have utilized high-density, low-cost sensor systems for air quality research and applications.
This course does not assume prior knowledge of electronics and will take an maker education approach to learning about low-cost sensor systems. Participants are required to have their own laptop for connecting to the Raspberry Pi, which will be provided for use during the course (alternatively, one can be purchased by the participants). All supplies required for the hands-on exercises will also be provided for use during the course. Raspberry Pi is a Linux-based single-board computer and the Python programming language will be used for writing software interfaces and data-logging programs.
For more information, please contact Udaysankar S. Nair at nairu@ uah.edu.