• 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 ...
• Sense Step: An Innovative Smart Cane for Visually Impaired Individuals 

  Tharsayani, M.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Sense Step is an innovative smart cane designed to empower visually impaired individuals through advanced assistive technology. Traditional mobility aids lack critical features to ensure user safety and independence, leaving ...
• Harvest Guardian: A Mobile Toolkit for AI-Based Crop Disease Diagnosis and Farmer Decision Support 

  Thivakaran, V.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Agriculture in Sri Lanka is predominantly driven by smallholder farmers who face challenges in timely disease detection, access to localized expert advice, and planning around weather conditions. These issues contribute ...
• 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 ...
• 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 ...
• Real-Time Elephant Movement Detection for Human Safety: An IoT-Integrated Smart Fence Approach 

  Budhdhika, W.G.T.M.; Pathiraja, S.P.M.C.P.; Kalubowila, K.D.K.A.; Vinoharan, V. (Faculty of Technological Studies, University of Vavuniya, 2025)

  The escalating Human-Elephant Conflict (HEC) in Sri Lanka has necessitated a transition from conventional mitigation methods to more sustainable and humane solutions. This study presents an Internet of Things (IoT)-based ...
• Intelligent Handwriting Recognition for Preschool Children Using Convolutional Neural Networks (CNNs) 

  Abirami, S.; Jayarathna, J.H.S.S.M.; Abeysinghe, A.K.U.S.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  This study addresses the challenge of recognizing handwritten numbers and alphabetic letters produced by preschool children. At this developmental stage, handwriting is often irregular, unstructured, and inconsistent in ...
• Image-Based Recognition for Sri Lankan Traffic Signs 

  Dhilakshan, T.; Disne, K.; Thadchanamoorthy, S. (Faculty of Technological Studies, University of Vavuniya, 2025)

  This research describes the development of an image-based traffic sign recognition system specifically designed for Sri Lankan road environments. The objective is to enhance road safety by accurately identifying local ...
• 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 ...
• 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 ...
• 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 ...
• University Student Performance Prediction Based on Student’s Habits Using Machine Learning Techniques 

  Lakmal, E.D.S.A.; Mihiran, R.I.B.N.; Wanninayaka, W.M.S.A.B. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Student academic prediction has been the subject of growing research in higher education as a way of predicting students who are at risk and intervening to help them. Universities are constantly searching for evidence based ...
• 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 ...
• 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 ...
• Posture Flow: Extending Yoga Posture Tracking Using Artificial Intelligence and Ayurvedic Insights 

  Nandasena, P.G.M.K.; Weerakkodi, Y.S.; Doshanthan, K.; Perera, K.D.N.N.; Perera, P.E.I.; Srimal, S.J.M.N.S.; Vithusha, B.; Sankeetha, V.; Venuja, N. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Yoga offers profound benefits for physical, mental, and spiritual well-being, yet incorrect posture execution can cause injuries and diminish therapeutic value. To address this, we introduce Posture Flow, an Artificial ...
• Multi-Disease Detection in Paddy and Jackfruit Plants Using Image Processing Techniques 

  Liyanwala, D.K.G; Jayasundara, T.N.; Amarasinghe, P.Y.; Sakuntharaj, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Plant diseases pose a major threat to agricultural productivity, particularly in staple crops such as paddy and fruit crops like jackfruit. Early and accurate disease detection is critical for ensuring food security and ...
• 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, ...
• Tomato Leaf Disease Classification Using Deep Learning Techniques 

  Prabhasha, S.M.U.N.; Wijesinghe, W.P.D.J.N.; Jayasinghe, B.N.D.; Tuvensha, J. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Tomato leaf diseases pose a significant threat to crop yield and quality, necessitating accurate and timely detection methods. This study focuses on developing an automated tomato leaf disease classification system using ...
• Smart Crop Recommendation System Using Machine Learning Models 

  Senevinayaka, R.K.S.D.C.; Amarakoon, B.M.P.P.; Tuvensha, J. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Crop recommendation systems have become essential tools in modern agriculture, assisting farmers in selecting the most suitable crops based on a combination of environmental and soil factors to optimize yield and resource ...

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