Research Publications
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Item Embargo Bovitrack:Animal behavior monitoring using Machine learning and IoT(Institute of Electrical and Electronics Engineers Inc., 2025) Viraj, H; Wijesekara, S; Tharuka, K; Fernando, S; Jayakody, A; Wijesiri, PAnalyzing dairy cattle behavior and anomalies is a critical component of precision livestock farming, allowing farmers to remotely monitor animals for health and behavior. In order to accomplish this task better, the use of IoT technology and machine learning algorithms is more appropriate as per the time. The YOLO (you only look once) object recognition algorithm is more suitable for that, and the use of this algorithm allows these processes to be performed automatically and in real time with high accuracy. YOLO's ability to recognize multiple objects in images or videos makes Yolo ideal for cattle detection and tracking.Publication Embargo A survey: IoT enable framework for water quality measurement and distribution(IEEE, 2018-08-08) Lokuliyana, S; Jayakody, A; Bandara, N. B. R. P; Deshapriya, J. W. P; Kavinda, P. C; Wijewickrema, T. LReal-time water quality detection consists of a great practical significance and also it led to management of precious water resources. This paper suggests an IoT enabled framework that analyses, monitor, report, maintain and distribute the physical and chemical properties of water. pH is how acidic or alkaline the water is one parameter that used to analyze the quality of water (7 in pH scale is neutral) apart from this chemical factor, two physical factors are considered in analyzing. Turbidity the measurement of how particle suspended in water, which led to lower the dissolved oxygen, reduce the photosynthesis of aquatic plants. Temperature is the other property, this caused by air temperature, groundwater inflows, exposure to sunlight. The authors examine through various existing implementations and research on such system and attempt to provide an overview of the research gaps and research problems available enabling further pathways.Publication Embargo Location based garbage management system with iot for smart city(IEEE, 2018-08-08) Lokuliyana, S; Jayakody, A; Dabarera, G. S. B; Ranaweera, R. K. R; Perera, P. G. D. M; Panangala, P. A. D. V. RSmart cities integrate multiple ICT and IOT solutions to build a comfortable human habitation. One of these solutions is to provide an environmentally friendly, efficient and effective garbage management system. The current garbage collection system includes routine garbage trucks doing rounds daily or weekly, which not only doesn't cover every zone of the city but is a completely inefficient use of government resources. This paper proposes a cost-effective IOT based system for the government to utilize available resources to efficiently manage the overwhelming amounts of garbage collected each day, while also providing a better solution for the inconvenience of garbage disposal for the citizens. This is done by a network of smart bins which integrates cloud-based techniques to monitor and analyze data collected to provide predictive routes generated through algorithms for garbage trucks. An android app is developed for the workforce and the citizens, which primarily provides the generated routes for the workforce and finds the nearest available smart bin for citizens.