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In this project, an anti-drone system is proposed that can detect drones based on camera-feed, narrowing down potential regions
of interest, and further identifying the existence and location of the drone. Multiple machine learning techniques combined with
image processing methods, are examined to address the problem of malicious drone activity that may directly threaten national
security. The system proposed by the students was composed of a Raspberry Pi that continuously captures the image then
passes it to the detection techniques. Two solutions were investigated to tackle object and drone detection: Haar cascades, and
background subtraction with pre-trained convolutional neural networks (CNN). Figure 1 shows an overview on how the different
methods are related.
Another great presented project is QU Community Application that was done by the students : Abdullatif Mnawar-CS, Alaaeldin
Said -CS, Islam Ibrahim-CS, Saeed Alrashidi-CS, the project was under the supervision of Dr. Ali AL-Jaoua. This project proposed
a mobile app called QU Community app which provides the students and faculty with several functionalities/services. Some of
these functionalities are Instructors ratings, bookshelves for donations, course bank, events, part-time work, lost and found items.
In addition, the app provides entertainment section which includes chatting, and feed of timeline posts similar to Facebook. The
Application is currently in android based and is only for QU members including professors and staff. However, in the future, the
students will like to expand it to the Qatar community in general.