Browsing by Author "Kanchana, B. C"

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    PublicationEmbargo
    COVID 19 Navigator Taxi Application for Urban Mobility during Pandemic Period
    (IEEE, 2022-02-23) Wickramarathne, J; Perera, D; Kanchana, B. C; Peiris, R
    This research paper focuses on increasing the awareness between taxi users and can help to protect themselves in COVID-19 and take precautions. Since 2019 the global pandemic of Covid-19 is spreading at an astonishing rate and causes a negative impact for economic, social, and cultural factors. Government agencies are warning people to reduce the transportation and to maintain social distance. To stop the spread of COVID-19 required to identify persons who are susceptible to infection and need to trace the COVID-19 positive first contacts. Most people are reduced to using public transportations and taxi services due to unidentifiable health conditions in earlier users. The proposed approach can be used to track the taxi drivers and their passengers previous COVID-19 status as well as navigate the safest route by showing the COVID-19 contamination areas. By using this approach users can be aware of earlier users of the taxi service and COVID-19 status of the taxi driver or passenger before taking the trip as well as if they get touch with any COVID-19 patients, can take immediate precautions. This application helps to increase the usage of taxis by making users trust and confidence against COVID-19 infection. By testing with real users our system was able to trace down 45 passengers and 16 drivers within 3 months.
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    PublicationOpen Access
    IOT Based Smart Microgreen Sprouter
    (Springer, Cham, 2022-01) Rankothge, V; Kehelella, P; Perera, D; Kanchana, B. C; Peiris, R; Madushan, K
    This research paper focuses on enhancing indoor farming technologies with an emerging technology: Internet of Things (IoT). The proposed approach creates a microgreen sprouter unit that automates the process of monitoring and providing optimum growing conditions with the minimum human supervision. This model can be used to achieve healthy growth of microgreen by providing ideal ventilation, moisture, humidity, light, and temperature levels, which prevents sprouts from ultraviolet radiation and pest attacks. Users can track the growth rate of sprouts and change the moisture, humidity, light and temperature levels. Our prototype implementation has been tested for mung-beans sprouts and validated for its accuracy and efficiency