This paper describes a novel experimental study that investigates the merits of an integrated cybersecurity plus robotics lesson plan, using the NAO humanoid robot, when it comes to introducing cybersecurity and robotics together to college and pre-college learners. We first present our unique cybersecurity plus robotics lesson, which is based upon a nifty experiential-learning model that combines basic cybersecurity concepts with educational robotics (ER) in the form of a hands-on experiment with NAO. Our lesson plan includes a demonstration of a successful hack into NAO's video stream, followed by covert capturing of its live camera feed. We then discuss results from two separate experimental case studies, the first one being a conventional approach of introducing cybersecurity concepts via a traditional lesson plan, which involves no robot. The second study involves our non-traditional technique of introducing cybersecurity plus robotics using NAO. We present the student survey data collected from these two studies and discuss their respective outcomes. We also analyze the pre and post student survey-based assessment data from these studies for showing preliminary evidence of the effectiveness and potential of our approach. Existing literature indicates that there is limited work on investigating the efficacy of learning cybersecurity plus ER using an interactive, humanoid robot, like NAO. Our work is an attempt to address this research gap in the literature. We intend to prepare the grounds for further research within this emerging topic of integrated cybersecurity and robotics education, so that students can gain from a positive and engaging experiential-learning experience.
Mainstream public video-surveillance systems are not generally designed to provide accommodations for under-privileged and under-represented subjects [1,2]. These subjects comprise of physically-challenged individuals, visually-impaired people and senior-citizens. With the recent emergence of the GDPR act [3,4], all surveillance data subjects, including these under-served populations, need to be offered an opportunity to provide consent, according to the Opt-in and Opt-out rule, regarding being recorded on closed-circuit televisions (CCTV) and other security cameras. Research advances in privacy-enhancing innovations [5,6], and privacy-mediating features [6,7] have helped visualsurveillance systems evolve towards offering more subject-centric privacy consenting options. However, these present state-of-theart technologies do not account for the underserved people. In order to be more inclusive in its privacy-mediating design, a video surveillance system needs to address the difficulties posed by technologies to the under-served subjects. In this article, we discuss this potential gap in research work, and explore the need of designing more inclusive privacy consenting functionalities within video-surveillance systems. B. INCLUSIVITY ISSUES -VIDEO SURVEILLANCE I. Under-served Populations
One of the challenges in healthcare is to provide equitable access to services, given that the provider and the patient are traditionally expected to be physically present in the same place [1], [2], [3]. Technological advancements have been made to overcome obstacles to equitable healthcare services and enable convenient access to quality healthcare for consumers throughout the world. The field of digital healthcare, which is known as telemedicine [2], [3], [4], [5], is rapidly making its way globally across the healthcare services domain. It allows the transfer of images and video through telecommunication technology, giving physicians the ability to evaluate, diagnose, and in certain cases, treat patients remotely [6]. Patients can visit providers over live video without travelling for immediate care and for follow up treatment. Not only does it give patients the ability to schedule appointments with local physicians via live video communication without having to leave home, but it also allows them to consult with distant healthcare professionals and avail their services remotely.
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