Browsing by Author "Subasinghe, M"

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    CocoSense: AI-Powered Drone-Based System for Comprehensive Coconut Tree Health Monitoring and Yield Prediction
    (Institute of Electrical and Electronics Engineers Inc., 2026-05-22) Subasinghe, M; Panditharathne, R; Pasanjith, R; Nadun, T; Samarakoon, U; Tissera, W
    Coconut cultivation is vital to Sri Lanka's agricultural economy, yet farmers face significant challenges in early pest detection, disease diagnosis, and yield prediction. This research presents CocoSense, an AI-powered mobile application integrated with IoT technology for automated coconut tree health monitoring using drone-captured imagery. The system comprises four modules: (1) pest detection using EfficientNetB0 (91.44% accuracy) and MobileNetV2 (96.08% accuracy) with a trilingual AI chatbot for treatment recommendations; (2) disease detection for leaf rot, leaf spot, and leaf dieback classification (98.69% accuracy); (3) health assessment for leaf (93.70%) and branch health (99.63%); and (4) coconut yield estimation (87.86% accuracy) using YOLOv8 with dual-view acquisition strategy. Additionally, a coconut bunch detection (88.96% accuracy) module is developed to support yield estimation by identifying fruit clusters within tree canopies. The system integrates IoT-based GPS tracking with Google Maps API for real-time plantation visualization. Experimental results demonstrate that CocoSense provides a robust, accessible solution for intelligent coconut plantation management in Sri Lanka.
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    Effectiveness of artificial intelligence, decentralized and distributed systems for prediction and secure channelling for Medical Tourism
    (IEEE, 2020-11-04) Subasinghe, M; Magalage, D; Amadoru, N; Amarathunga, L; Bhanupriya, N; Wijekoon, J
    Good health and wellbeing, a sustainable development goal introduced by the United Nations to be achieved by 2030. Sri Lanka is a country that highly depends on tourism. A healthcare system which consists of high quality and low-cost services and an abundance of tourist attractions makes Sri Lanka to be one of the best medical tourism destinations. Tourism and travel have contributed to the GDP of Sri Lanka by 11.1 billion USD by 2018. Lack of technological advancements within the medical sector has drawn back the ability to smoothly cater medical tourism. The proposed system aims for an advanced technological improvement that would help in further developing and contributing to medical tourism. To this end, this paper introduces an Intelligent System for Secure Channeling platform that aids medical tourism with the help of artificial intelligence and blockchain technologies. System proposes a treatment prediction and suggesting the best doctor for it and a secured network to store and access electronic health records (EHR). The yielded results show that the proposed method successfully performed treatment prediction with 79-88% accuracy.