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Author: search.filters.author.Wickramarathne, J

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    An Online Dashboard Platform for Weather Data of Major Sri Lankan Cities, and Global Climate Trends
    (IEEE, 2022-12-08) Pemasinghe, S; Dayarathna, D; Panditharathna, P M R A; Saparamadu, S; Wickramarathne, J
    Having easy access to vital weather information and latest climate trends can be of utmost use for a myriad of stakeholders specially for sectors such as fishing community and the agricultural sector. In this paper we have mainly focused on major Sri Lankan cities and providing a one-stop station for easily accessing useful weather information for all the major Sri Lankan cities scattered over 25 administrative districts via a series of dedicated dashboards for each of the cities. The parameters that are displayed in the dashboards have been decided via surveys covering major stakeholders. Steps have been taken to disseminate not only the weather information but also information about latest climate trends regarding stratospheric ozone concentration and global land and ocean temperature anomalies, and providing all this information in one place with a lot of potential to extend the breadth of information provided in terms of weather and climate changes in the years to come.
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    COVID-19 Infection Risk Assessment for Shoppers in Retail Stores
    (IEEE, 2022-12-26) Rathnayake, B. R. M. S. R. B.; Senadheera, R.I.A.; Ranasinghe, R.A.K.H.; Sameer, U.M.; Wickramarathne, J
    Over the last few years, a large number of smartphone apps have been developed to “flatten the curve” of the rising number of COVID-19 infections. Knowledge of potential symptoms and their distribution enables the early identification of infected individuals. We developed a mobile app-based crowdsourcing methodology to assess the COVID-19 infection risk through shopping habits at indoor retail stores. The app’s goal is to instil trust in customers to visit stores, which will assist small and medium businesses to survive their operations in the near term. According to the literature, there are several implementations for COVID-19 infection risk estimations for such scenarios. A mobile app prototype was developed, and the risk was calculated using the COVID-19 Aerosol Transmission Estimator model established by the University of Colorado Boulder. The developed prototype mobile app was tested with end users to gather their feedback through a questionnaire. In comparison to the complex implementation associated with AI-based alternatives, this solution could be delivered at a lower cost with adequate accuracy of COVID-19 infection risk assessments.