Browsing Faculty Annual Research Session by Document type "Conference abstract"

Browsing Faculty Annual Research Session by Document type "Conference abstract"

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  • Advancing Network Intrusion Analysis: A Hybrid Approach from Detection to Classification 
    Vithusha, B.; Sankeetha, V.; Abiramithan, T.; Lojenaa, N. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Effective network security requires both accurate detection of anomalies and meaningful classification of detected threats. While supervised machine learning models are proficient in identifying anomalous traffic, categorizing ...
  • Agro Guard: A Smart IoT and Machine Learning-Based Assistant for Climate-Resilient Precision Agriculture 
    Libisanan, J.A.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Agriculture plays a vital role in ensuring global food security amid growing population pressures. However, climate change, soil degradation, and natural disasters such as floods pose serious challenges to maintaining soil ...
  • AI-Powered Attendance System Using or Codes and Facial Recognition 
    Adikaram, K.K.J.K.B.; Mohomed Wazeem, S.K.; Ranaweera, S.D.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This research introduces a Safe and Smart Dual Authentication Student Attendance System using Facial Recognition and QR Code verification to eliminate proxy attendance and enhance operational efficiency in academic ...
  • Audio Deepfake Detection Methods: A Review 
    Janani, W.V.M.; Nissanka, N.B.A.S.C.; Thisaravi, K.G.A. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The emergence of audio deepfake technologies has raised new concerns in the area of digital security, privacy, and trust in media. Audio deepfakes are AI-generated synthetic audio clips that are capable of accurately ...
  • Automated Student Attendance Management Using Real-Time Face Recognition 
    Kavindya, S.A.S.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    This paper presents a facial recognition-based student attendance management system aimed at automating and improving accuracy for students attending extra classes. Traditional manual attendance methods are time-consuming ...
  • Carbon Sequestration Estimation in Paddy Fields Using Synthetic Aperture Radar (SAR) Data in Sri Lanka 
    Uthayadharshini, S.; Gajanthan, S.; Madhushani, S.I.S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Soil organic carbon (SOC) is essential for keeping soil healthy, improving crop growth, and tackling climate change. In rice-growing areas such as those in Sri Lanka, knowing how SOC is distributed helps farmers adopt ...
  • A Cloud-Integrated IOT-Based Anti-Theft System for Home Using Image Processing 
    Tharsan, S.; Nusky Ahamed, T. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Home security has become a major concern due to the rise in burglary and unauthorized access incidents. This study proposes a cloud-integrated IoT-based anti-theft system using real-time facial recognition to enhance ...
  • Comparative Analysis of Machine Learning Models for Brown Spot Disease Detection in Rice Leaves 
    Kulaksiga, J.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Rice is a vital crop that feeds more than half of the world’s population, but its productivity is seriously threatened by diseases like Brown Spot, caused by the fungus Bipolaris oryzae. While many studies have shown that ...
  • Deep Learning for Intelligent Waste Sorting in Sri Lanka: A Conceptual Review 
    Herath, H.M.P.H.S.; Kuruneru, R.P.D.; Logeesan, R.; Venuja, N. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Urban waste management in Sri Lanka is increasingly challenged by rising waste volumes, reliance on manual sorting, and inefficient collection systems. This review paper aims to examine how deep learning, particularly ...
  • Deep Learning-Based Detection of Deficiencies and Leaf Diseases in Chili Plants Using Image Processing 
    Kavindu Rashmika, W.A.D.; Semasinghe, T.M.N.M.; Vithanage, M.V.S.C.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Early detection of nutrient deficiencies and foliar diseases is essential to improve chili productivity, especially in rural communities where traditional testing is expensive and inaccessible. This study developed a deep ...
  • Deep Learning-Based Detection of Diseases in Mangifera indica (Mango) 
    Bandara, B.M.A.U.; Chathuranga, T.D.K.; Madhuwantha, D.A.J.A.; Saranga, T.A.D.S.; Mishawrnilanthi, S.; Hasitha Viduranga, G.R.; Dhanaranga, K.W.I.B.; Vinoharan, V.; Suthaharan, S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Mango (Mangifera indica) is one of the most commercially viable fruit crops in Sri Lanka. However, its cultivation faces increasing challenges due to various pests and diseases, which significantly reduce both yield quantity ...
  • Deep Learning-Based Plant Identification in Sri Lanka 
    Chayanthithan, C.; Rajagopal; Bandara, P.R.D.N.; Farhana, M.F.F.; Dharmasiri, T.N.; Bandara, U.M.J.M.; Jayasekara, J.M.T.N.; Saliny, N.; Nirosi, P. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Sri Lanka is home to a diverse range of plant species, many of which play critical roles in agriculture, biodiversity conservation, and ecological balance. Traditional methods of plant identification are often manual, ...
  • Designing a Socio-Technologically Adaptable, Scalable Peer-to-Peer Accommodation Platform to Support SMEs in Sri Lanka After the Crisis 
    Rajapaksha, R.W.V.A.S.C.; Ranasooriya, U.E. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The tourism industry is a globally significant sector that contributes substantially to economic growth. However, small and medium-sized enterprises (SMEs) in the tourism\sector face challenges in accessing global digital ...
  • Detecting Pests in Mango Crops using Machine Learning (ML) 
    Sankeetha, V.; Agalya, V.; Vinoharan, V. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Mango is one of the most important fruit crops in Sri Lanka, playing a vital role in both the agricultural sector and rural livelihoods. Despite its economic value, mango cultivation faces persistent challenges due to pest ...
  • Development of a Voice-Controlled Front-End User Interface Using AI-Based Command Recognition 
    Rakshika, U.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Artificial Intelligence (AI) innovations have revolutionized digital interactions, enhancing accessibility and usability in modern web applications. This project presents a voice-controlled front-end user interface (UI) ...
  • E-Document Classification Using Deep Learning 
    Wijesuriya, M.W.A.S.P.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The proliferation of digital content in the form of electronic documents necessitates efficient classification methods to manage and analyze this growing body of information. This research explores the application of ...
  • Enhancing Flow Rule Eviction Policy in Software Defined Network 
    Vithuckshiha, P.; Shriparen, S. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Traditional network architectures struggle under high-volume, real-time traffic. Software Defined Networking (SDN) separates control and data planes to enable centralized control, but switch flow-table capacity remains a ...
  • Explainable Machine Learning-Based Fake News Detection Using NLP Techniques 
    Nawodi, N.A.R.; Wijegunasinghe, U.S.; Lakshan, W.K.; Vithuckshiha, P. (Faculty of Technological Studies, University of Vavuniya, 2025)
    The rapid spread of misinformation on social media poses significant societal risks. This study develops an interpretable and accurate fake-news detection system that combines traditional supervised learning with Explainable ...
  • Exploring the Biometric Potential of Fingerprints for Blood Group Identification: A Survey 
    Weerasinghe, W.D.; Banu, N.F.N.; Sewmini, A.R.M.N.; Venuja, N.; Saliny, N. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Successful identification of a blood type quickly and correctly is essential for patient centered care and emergency settings. Traditional methods could include technically invasive blood collection (e.g., fingerstick), ...
  • A Framework for Offline Screen Time Control Inchildren: Focus on TV, Gaming Behaviour Studies 
    Asana Sajahan, F. (Faculty of Technological Studies, University of Vavuniya, 2025)
    Effective management of children’s screen time has become a significant concern for parents, particularly working parents, as excessive exposure to digital devices can adversely affect children’s psychological and developmental ...

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