Browsing by Author "Gunasekara, S"

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Open Access
From ‘Frying Pan to Fire’: Unprecedented Challenges of COVID-19 on Blind People in Sri Lanka
(2021) Suraweera, T; Thelijjagoda, S; Jayathilaka, R; Bandara, S; Gunasekara, S; Hasintha, S
COVID-19 has shattered all wakes of people’s lives in most countries in diverse proportions. Sri Lanka being no exception, has experienced the spread in early March 2020 and later in September in the same year. Since then, the Government has implemented a wide range of far-reaching health measures and several other social restrictions with the view to combating the spread of the disease. Among the badly challenged fractions of the population due to pandemic was the people with disabilities. It is known that the persons with visually impairments and blindness represent the majority of this vulnerable community. The impact of the pandemic on the blind people are mostly untouched. Purpose of this paper is to examine the challenges of COVID-19 experienced by the blind people in the light of their social and economic life. A qualitative case study approach was adopted for data collection. Thirty-six blind persons representing of diverse livelihood activities, selected through purposive sampling method were interviewed. The interview transcriptions were initially examined through word cloud and subjected to thematic analysis for examining changes to social and economic activities. Results highlight that owing to COVID-19 pandemic shutdown, blind people have been severally disturbed in several aspects, some of which are unique to this community. The key challenges identified are related to mobility and transportation, acquisition of daily needs, disturbed social interactions, income earning opportunities, and information and communication. The precautionary measures implemented on COVID-19 pandemic has brought about disturbances that are relatively severer for the blind people on moving forwards with their day-to-day life activities, than the sighted people. The decision makers dealing with pandemic situations should take into consideration of inclusive policies.
Embargo
Real-Time Greenhouse Environmental Conditions Optimization Using Neural Network and Image Processing
(IEEE, 2020-11-04) Wickramaarachchi, P; Balasooriya, N; Welipenne, L; Gunasekara, S; Jayakody, A
Agricultural business is one of the biggest areas in world economy. With the growth of population losing agricultural lands is the major issue in world food production. Therefore, controlled environment agricultural systems under vertical farming have been introduced with greenhouses. Within greenhouses there is not a mechanism to continuously monitor the growing community and change the climate conditions. Existing systems only predict the required conditions for the plant and once predicted that value is provided to the plants continuously or change the values from season to season. To address these issues, a working prototype of an IoT based smart hydroponic system is introduced, which uses computer vision to gain maximum profits by growing a specific cultivation by providing endemic environmental conditions and addressing the problems over its growing process. There, this research presents a way of external environmental condition optimization. Regression type Feed Forward Neural Network is considered for this research to optimize the required conditions for tomato plants. Based on the current height of the plant, expected height for next 24 hours, and growth date of the plants neural networks predict the CO2, temperature and humidity level for next 24 hours with the accuracy of 88.33%, 89.21% and 92.65% respectively. The objectives of the research can be achieved by this retrieved results. The successful implementation of neural networks results a cost-effective modern farming solution for growers. This research will be supportive to attain a fundamental comprehension on the concept of the research area.