Research Publications
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Item Embargo MaizeGenie - Mobile Platform for Sustainable and Profitable Corn Cultivation(Institute of Electrical and Electronics Engineers Inc., 2026-03-26) Suraweera A.G.S.S.; Pasindu J.D; Rathnayaka R.M.T.P.B; Perera P.D.P.N; Samarakoon, U; Hathurusinghe, SMaize is an important crop in Sri Lanka, but many farmers still face low yields and income losses due to pest and leaf disease attacks, uncertain weather, and market price changes. Farmers also have limited access to real-time, easy-to-understand decision support in Sinhala, especially in areas with weak internet coverage. This research proposes MaizeGenie, an AI-powered mobile advisory platform that supports sustainable and profitable corn cultivation. The system combines computer vision and machine learning to deliver four main services: (1) pest identification and control guidance using object detection and image classification, (2) leaf disease identification with severity-based advice, (3) yield prediction with prediction-based site-specific real time fertilizer advisory system, and (4) price forecasting and cultivation timing decision support using time-series forecasting. The application is designed for farmerfriendly use, provides Sinhala/English guidance with voice/text output, and supports operation where possible. Overall, the proposed solution aims to reduce trial-and-error farming, improve timely actions against pests and diseases, and help farmers plan inputs and selling decisions with more confidence.Publication Embargo Know More: Social Media based Student Centric E-learning platform with Machine Learning Approaches(IEEE, 2022-07-18) Malavige, O; Nasome, V; Costa, M; Jayasinghe, B; Karunasena, A; Samarakoon, USocial media has become increasingly popular among the younger generation in the last decade. Students engage with social media on daily basis, and it affects their interests, lifestyle, and attitude. There are many existing e-learning applications used by higher educational institutes, but such applications are mainly focused on delivering teaching content rather than facilitating active and interactive learning. This paper proposes a novel e-learning platform to create an active and interactive learning environment for students leveraging social media strategies, especially those of “Facebook.” The objective of this platform is to promote self-motivation, self-learning, and interaction. The platform features were built on considering three aspects important for learning, which are personal knowledge management, learning management, and collaborative learning. Features of the proposed platform that it comprises are Newsfeed, Classmates, Profile, Cluster, Repository, Knowledgebase, Bookmark, Topic Map, Search Engine, Test Mark Prediction, and Slide Show Summary generator. Machine Learning techniques and Natural Language Processing were used to build some of the platform features. The feedback collected on the proposed system, “KnowMore,” shows that the satisfaction of the students has increased with the system.