Browsing by Author "Chandrasiri, S"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    item: Conference-Full-text
    Diagnostic intervention for mental disorder
    (Faculty of Information Technology, University of Moratuwa., 2021-12) Senanayake, S; Karunanayaka, C; Dananjaya, L; Chamodya, L; Kumari, S; Chandrasiri, S; Ganegoda, GU; Mahadewa, KT
    Mental health is one of the essential factors in the topic of healthcare and wellbeing. However, mental health disorders could cause severe damage, even loss of life to the person or the surroundings, if mental health disorders were not identified and appropriately cured. Unfortunately, though there is good help there, some people have a hard time detecting whether they are suffering from mental health disorders or not. In this study, the team proposes a system to detect mental health issues using facial emotion recognition (FER), sleeping patterns, social media web scraping, and heart rate. The intention is to give an accurate prediction of the mental health status of a person using these three nodes.
  • Thumbnail Image
    item: Conference-Full-text
    Kidland: an augmented reality-based approach for smart ordering for toy store
    (Faculty of Information Technology, University of Moratuwa., 2021-12) Wijayalath, WMCD; Ranasinghe, RMTT; Kumari, S; Thennakoon, MTH; Vithanage, HD; Chandrasiri, S; Ganegoda, GU; Mahadewa, KT
    Augmented reality (AR) is an iconic topic that can be applied in different domains in modern world technology. With the rapid development of technologies, eCommerce (Online Shopping) has become closer to human life. As a result, AR was started implemented with eCommerce platforms by the developers. With the busy lives and the pandemic situation, people are limited to visiting toy stores while providing a solution. An AR-based virtual toy store is proposed with 3D Toy generation for visualizing selected toys, a Virtual tour for enhancing the remote virtual shopping experience, and an Indoor navigation system visualizing the path within large scale shopping malls are new features of the proposed system. The majority of the existing eCommerce platforms are missing image search features. As a solution, “KidLand” has implemented an image search engine, suggesting add-on-related items and nearest branches using machine learning algorithms. An intelligent chatbot uses a reinforcement learning algorithm and Natural Language Understanding (NLU) to give possible solutions regarding the toy store. As a solution to the language literacy problem, developed a chatbot that can chat both English and Sinhala languages. “Kidland” was developed to provide the users the next level of shopping experience with attractive features of AR technology with marketing and use advanced technologies overcoming the issues of ordinary eCommerce platforms. In Sri Lanka, this system has been identified as a solution for the issues with ordinary shopping platforms.