Faculty of Computing

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    Remotify: The Emergency Remote Learning Solution using Learning Analytics
    (IEEE, 2022-07-18) Amarasinghe, S. N.; Thalakumbura, T. M. D. D; Wijewardena, M. D. N. K.; Perera, D. H.; Manathunga, K; Senaweera, O
    Current pandemic situation has manipulated people to adapt to a new normal forcefully and due to the same reason education system is also evolving but the actual question is how productive the new methodologies utilized are. E-learning is not a novel concept but is becoming a necessity and the proposed platform could be identified as a direct response to the current emergency. This can also be known as an "ERT" situation; a shift of instructional delivery to an alternate delivery method in response to a crisis situation. The main intention in these situations is not to recreate a robust educational system but to provide access to institutions in a manner that is easy to set up and is dependable during an emergency while outperforming both E-learning & traditional classroom methods. To provide a solution to overcome barriers faced in a pandemic situation in a virtual classroom, the implemented system is encapsulated with a dashboard centralizing facts gathered from audio & video analyzing components which are analyzed against student performance utilizing personalized assessing techniques to deliver learning analytics.
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    Emergency Patient Identification System
    (IEEE, 2019-12-05) Sandamal, T; Fernando, N; Jayasinghe, I; Xavier, J; Kuruwitaarachchi, N; Rupasinghe, L
    Emergency patient identification system (EPIS) will enable the more powerful quality system in the health industry. This research study was conducted to develop an EPI system, which is a complete patient-based medical information recording system. This system will help to identify the patients uniquely. Doctors can get patients' latest situation and can make quick decisions to do the treatments in emergencies. To achieve this approach, authors use the patient's fingerprint, face recognition technology, and eye recognition to identify the person. The patient can view his medical records; system reminds the notifications. The system helps the patients in storing and tracking the diet weight, medications, allergies, health history, fitness, lab results, x-rays, blood pressure, ongoing surgeries, drug reminders, doctor visits, doctor's appointments, images and more. The system helps the user in receiving and sending necessary health-related information to the doctors and hospitals. This system has many unique features; an emergency will help to find nearest hospitals. This can add patient's family member's history so it can help to remind his present medical situation. The main system is working on web interface; another part is offered as a mobile application.