Designing an Authentication System for Augmented Reality Devices

The following report details the potential of using BVP and BCG waveforms as a biometrics means for user authentication using a head-mounted device. We trained a convolutional neural network to retrieve an optimal model that will allow for correct user authentication. We analyzed the results using ROC curves to determine the best performing models. The ROC curve analysis showed us that there were errors with our BVP results and therefore we moved on with only the BCG waveform. This research aimed to find alternative methods of authentication for users while considering the security of their passwords. The waveforms help us achieve this goal of authentication as users provide their subtle head movements which are much harder for adversaries to mimic than a typed password

Madinat Al Irfane: Is Smart Mobility Feasible?

The goal of this project was to assess the feasibility of incorporating smart technologies into the current transportation systems within Madinat Al Irfane in Rabat, Morocco. Our team worked in collaboration with Dean Essaidi, of l\u27Ecole Nationale Supérieure d\u27Informatique et d\u27Analyse des Systèmes (ENSIAS) to accomplish this goal. Through research, site assessments, surveys, and interviews, our team gauged the publics discontent with the current bus service. After completing our assessment of the existing transportation systems in Madinat Al Irfane, we concluded it is not feasible to implement smart mobility initiatives. In hopes to alleviate prevalent issues the team found in the transit systems, we developed a preliminary design review for a sensor based tracking system for the buses