INTERNET OF THINGS-BASED FRAMEWORK TO FACILITATE INDOOR LOCALIZATION EDUCATION

Internet of Things (IoT) is becoming a hot topic in Computer Science, especially with the advent of smart appliances such as Nest thermostats, connected light bulbs, and other IPenabled systems. In this paper we are proposing IoT-based framework to facilitate education of indoor localization. The proposed framework employs Arduino microcontroller boards connected with XBee (TM) radio modules to perform indoor localization. The framework uses a master-slave architecture and RSSI-based triangulation to facilitate student learning of localization algorithms. Indoor localization is a field where more research is still needed, since current methods are far from perfect and have limitations in accuracy and precision. Helping students spark interest in indoor localization has the potential to bring in more young researchers into the field as well as bring in much needed new ideas.