Browsing by Author "Kahandawaarachchi, K.A.D.C.P."

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Air Visio: Air Quality Monitoring and Analysis Based Predictive System
(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Dissanayaka, A.D.; Taniya, W.A.D.; De Silva, B.P.A.N.; Senarathne, A.N.; Wijesiri, M.P.M.; Kahandawaarachchi, K.A.D.C.P.
Sri Lanka is facing a serious air pollution problem that severely impacts the daily life of every Sri Lankan. The main source of ambient air pollution in Sri Lanka is vehicular emissions. A methodology to monitor the air quality in real-time with an overall coverage of Sri Lanka, and automatically process these huge data to identify air quality levels in a specific area is now becoming a timely research topic. An air quality monitoring and analysis based predictive system is proposed to monitor the ambient air quality, provides the best route with minimum polluted air, maps the heatmaps to identify the current air quality of an area easily and predict the future air quality of each area. The prototype was implemented by hierarchically deploying two different gas sensors, an Arduino Uno board and a wifi module, to implement in open spaces between smart buildings, and transfers the sensor data back to the information processing center by using IoT technology for real-time display. The information processing center stores real-time information which is collected from the sensors to the database. By reading sensor data stored in the database, the front-end system draws real-time, accurate air quality levels included maps and predicts the less polluted routes and the air quality level over an area. Further, an energy harvesting system is also presented for the power consumption of the device. A route is suggested in an accuracy of 70% from this system. The final product provides a low cost, highly portable and easily maintainable system for the users.
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Proximity based Intelligent Air Pollution Alerts for Garbage Disposal Sites
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Wijerathne, W.G.D.U.; Perera, M.L.M.P.; Nuwandika, R.H.C.; Ranasinghe, R.A.K.A.; Kahandawaarachchi, K.A.D.C.P.; Gamage, N.D.U.
Air pollution is one of the key trending challenges faced by the public at present. The garbage disposal sites are the major contributors which emit harmful gases (CO, CO2, CH4) where toxicity is at a higher level. This research attempts to fill the lacuna by providing an intelligent proximity-based air pollution detection system that alerts and makes the public aware of the danger and risk of the garbage dumps that are located near them via a mobile application. The device is developed to detect harmful gas with MG811, MQ7, MQ4 sensors with 0.80 accuracy. The device also contains a DHT22 temperature humidity sensor with 0.80 accuracy and SD011 particulate matter sensor which has a 0.95 accuracy. The application can notify the responsible authorities regarding the possible risks of the garbage dump and the health effects that can cause. The air toxicity is calculated with an accuracy of 0.75 and visualized, using the landfill classification and pollution level prediction algorithms with an accuracy of 0.96 in a geo proximity map with 0.92 percent accuracy.
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Remote Treatment Management Approach to Rural Healthcare in Sri Lanka
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Shashishka, P.W.T.; Madhusankar, M.S.; Perera, M.T.K.; Gnanasena, A.M.J.C.; Kuruppu, T.A.; Kahandawaarachchi, K.A.D.C.P.
With the complications of society, people tend to ignore their medical status and focus on other priorities. Majorly due to lack of time to consult medical help, also in a pandemic situation like Corona Virus people have tended to detour their health issues. Patients lack options to contact their medical consultant without being physically present. “Remote Treatment” is designed to address this issue. App offers video conferencing between the patient and the medical consultant. Patients can choose the quality of the stream depending on the internet connection's capability, implemented utilizing WebRTC. Additionally, Remote Treatment provides patient data management and prescription handling along with improved security. Medical consultants has access to patient's previous and current reports also detailed graphs on their progress, implemented by utilizing Fusion charts, prescription handling has digitalized the prescription process hence patients wouldn't have the risk of acquiring inaccurate medicines. prescription handling is based on voice recognition built on using sphinx package In a telemedicine feature information security is utmost importance since these information violations could result in devastating situations. Information is secured with the aid of blockchain technology to provide maximum security. Remote Treatment allows patients to access medical help quickly with optimized condition.
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Secured, Intelligent Blood and Organ Donation Management System - “LifeShare”
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Wijayathilaka, P.L.; Pahala Gamage, P.H.; De Silva, K.H.B.; Athukorala, A.P.P.S.; Kahandawaarachchi, K.A.D.C.P.; Pulasinghe, K.N.
The scarcity and exigency for blood and organs has created many discrepancies in current approaches. These have created the criteria for malpractices such as organ trafficking and black market selling. This research presents a solution with a secured-smart blood and organ donation web developed system, allowing both patients and healthcare providers to access information about the blood and organ processing records. The database would be managed using the Blockchain technology which could be only accessed by authorized users. Finally, tracking all registered donors, the proposed system generates a smart identity developed by Ethereum Smart Contract (ESC). System predicts blood demand for the future ten years using Linear Regression Model with 0.998 of high R-squared accuracy value. This reduces shortages and wastage of blood. Also, using global positioning system and K-Nearest Neighbors Machine Learning algorithm, the system finds the best matches among donors and seekers according to the nearest location. Further, the system will automatically send questionnaires for registered users to identify and evaluate their awareness and issues about organ donation. Overall, this study aims for a secured and transparent web application. Thus, it facilitates an innovative and a productive blood donation and organ transplantation process in Sri Lankan healthcare sector.