3rd International Conference on Advancements in Computing [ICAC] 2021
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/947
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Publication Embargo Guided Vision: A High Efficient And Low Latent Mobile App For Visually Impaired(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Rizan, T.; Siriwardena, V.; Raleen, M.; Perera, L.; Kasthurirathna, D.This paper presents a novel solution for visually impaired individuals. A mobile app is connected to an ESP32CAM and a remote server to help visually impaired individuals to navigate around their environment safely. A deep learning model is deployed in the mobile app to detect obstacles in real-time without connecting to the internet. Other tasks such as reading texts, recognizing people, and describing objects are done in the remote server. We managed to connect the mobile app to the ESP32CAM and the remote server simultaneously. This was possible because the ESP32CAM is connected to the mobile app through Bluetooth. This gave the mobile the ability to connect to the remote server via the internet. To the best of our knowledge, no research has been done using Bluetooth to stream images to do object detection in a mobile app locally. Hence, our solution can detect obstacles locally and do other tasks mentioned previously in the remote server. This paper discusses how the ESP32CAM, obstacle detection module, face recognition module, text reading module, and object description module was implemented such that a low latent and highly efficient mobile app is created using minimal resources.Publication Embargo E-Learn Detector: Smart Behaviour MonitoringSystem to Analyze Student Behaviours DuringOnline Educational Activities(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Bamunuge, H.K.T.; Perera, H.M.; Kumarage, S.; Savindri, P.A.P.; Kasthurirathna, D.; Kugathasan, A.With the rise of online education more attention is being paid to the deficiencies in online learning platforms. Online Learning environments aim to deliver efficacious instructions, but rarely take providing a conventional classroom experience to the students into consideration. Efficient detection of students’ learning situations can provide information to teachers to help them identify students having trouble in real-time. This idea has been exploited several times for Intelligent Tutoring Systems, but not yet in other types of learning environments that are less structured. “E-Learn Detector is a web application solution to these existing issues in online learning which consists of unique features such as verifying the user during logging procedure and throughout an examination, detecting suspicious behaviors and presence of multiple users during online examinations and detecting low engagement levels of students during online lectures. “E-Learn Detector” is developed with the aim to provide guidance to students to improve their academic performance and behavior during classroom activities and to induce the best out of the educational activities.Publication Embargo Dynamic User Interface Personalization Based on Deep Reinforcement Learning(2021-12-09) Silva, K. G. G. H.; Abeyasekare, W. A. P. S.; Dasanayake, D.M. H. E.; Nandisena, T. B.; Kasthurirathna, D.; Kugathasan, A.Personalization is one of the most sought out and popular methods for brand recognition and consumer attraction. The usage of deep reinforcement learning due to its’ ability to learn actions the way humans learn from experience, if utilized and evaluated properly it can result in a revolutionary effect on personalization. The methodology proposed in this research utilizes deep reinforcement learning where an artificial agent may be trained by interacting with its environment. Utilizing the experience gathered, the agent is able optimize in the form of rewards. The approach explained, can be utilized across applications which can be personalized. Several scenarios ranging from changing the layout of webpages, to rearranging icons on mobile home screens are discussed. The main objective is to develop an API for the web developers and smartphone manufacturers to utilize so that depending on the application personalization can be achieved by enhancing saliency, minimizing selection time, increasing engagement, or an arrangement of these. The technique can manage a variety of adaptations, such as how graphical elements are shown and how they behave. An experiment was conducted which showcased improved user experience considering the position change of the