Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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    Identifying Objects with Related Angles Using Vision-Based System Integrated with Service Robots
    (IEEE, 2022-07-18) Pasindu Lakshan, K. K; Rajapaksha, U. U. S; Jayawardena, C
    Manipulation of an object can be done with the collaboration of a human to a robot by properly introducing the object. To do this easily, we can model the object inside the robot’s head and let the robot identify it using some sensors and cameras. But when it comes to the real world, robots should have some mechanism to recognize objects in a perspective frame with angels. In this research authors will present a strategy to identify the unknown objects using a vision-based system and with the perspective angles of the detected object and the system is integrated with service robots. This will go in a way when the robot should be able to identify the objects around the robot in an asynchronous manner with rotational angles and the pitch and roll angles, perspective to the robot standing surface. The research will be based on Artificial intelligence, Machine learning, and Robotics.For the identification process, a few ways can be used. Vision-based identification using color and depth images from an RGB camera, and this research is mainly based on this RGB and depth feature integrated with YoloV5. And there are some other ways to identify objects like using LiDAR laser scanner. However, this learning process, should have a stable object to model and train the object. After the object recognition, by using the proposed methodology robots can calculate and estimate the rotational angles and pitch and roll angles of an object.
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    E-patient Card: An Integrated Electronic Health Recording System for Patient
    (IEEE, 2022-01-11) Pivithuru, K. W. A; Srinivasan, A; Wijeratnam, A; Nassar, I; Chandrasiri, S. S; Suriyaa Kumari, P. K
    Smart cards are portable integrated devices with data storage and processing capabilities that are utilized in information technology. An electronic patient card is kept on smart cards. Their efficient use with easy and fast data access facilities leads to implementation particularly widespread in hospitals. A smartcard-based Integrated e-Patient Card System is created in this research. The technology communicates data and uses a smart card for personal identification and data transfer. e-Patient Card has several advantages over paper records, including increased accuracy and quality of patient treatment and cost, efficiency, and productivity savings. In the present work, diseases were identified using chest x-ray images, improving the disease detection process faster and more reliable. This system helps the users to get a better idea of the disease with symptoms they got. To make this process more user-friendly chatbot has been implemented. In the future place predictions of coronavirus spread for each place of the infected regions were identified. The patient’s smart card is filled with general health information. Over the distributed object protocol, encryption keys and digital signature keys stored on the system’s smart cards are utilized to exchange secure and authorized data between clients and database servers.
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    FIMAA: Four-way Integrated Mobile Authentication API
    (IEEE, 2019-12-05) Kariyawasam, L; Moonamaldeniya, M; Samarawickrama, V; Premalal, S. H; Rupasinghe, L; Abeywardena, K. Y
    In this era of the digital world, mobile device users have been increased to a significant number. This proposed system presents a hybrid authentication approach which can be considered as a combination of silent authentication and input based authentication to enhance mobile security in android mobile applications. A four-way integrated mobile API introduces the gait patterns and location traces as well as the image context and face ID-based emotions of the user. This application silently authenticates the exposed location trace and gait patterns of the user while other ear and emotion inputs will be prompted to end-user accordingly with input authentication.