Faculty of Computing

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Author: search.filters.author.Attanayaka, B

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Now showing 1 - 6 of 6
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    A Mobile Gamified Application to Improve Mathematics Skills of Students from Age 9 to 11 Years
    (Institute of Electrical and Electronics Engineers, 2022-09-16) Karunasekara, K.K.R; Olinka, P.L.T; Kodithuwakku, K.T.D; Jayashan, B.V.P; Kahandawaarachchi, C; Attanayaka, B
    The revolutionary change in technology has directly involved with e-learning systems. Mathematics is recognized as essential yet difficult for most of students. The main problem is considered as existing solutions were not provided a better solution for knowledge level enhancement of mathematics by detecting the exact knowledge levels of students. Current applications have offered permission to select students' knowledge levels by themselves or initiated from the initial level which has led to wrong identification of mathematics knowledge. As a solution for these problems gamified mobile application is provided by introducing a knowledge level detection with a whole syllabus coverage question classification and answer classification by using a Logistic Regression extra trees classifier. The knowledge improvement is performed from the exact knowledge level detected and positive emotions of students. Convolutional neural network is utilized for emotional recognition. Further mental health is improved via a Chabot as an educational encouragement and gamified application is developed based on psychology and preference around ten years by adhering to the best practices of Human-Computer Interaction. The proposed solution is considered as a multi-valued and cost-effective solution which will improve the mathematics knowledge level and good mental wellbeing of students with an appealing gamification environment.
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    Location Intelligence Based Smart E-Commerce Platform for Residential Real-Estate Industry
    (Institute of Electrical and Electronics Engineers, 2022-10-22) Balasooriya, T; Kavishka, L; Dananjana, I; Yumna, M; Thelijjagoda, T; Attanayaka, B; Marasinghe, L
    Making the decision to purchase or invest in real estate can be a very crucial process due to its high financial risk. The purchasing decision of residential real estate properties can be even more decisive because, apart from the financial risk, the choice of a property can have a great impact on the future lifestyle of the buyer. When considering residential real estate, one major factor to be considered is the property location. This research sought to determine the applicability of modern technologies such as location intelligence and machine learning in the development of an e-commerce system that may assist users in making optimal residential real estate location decisions. Third-party web APIs were used to obtain location data, and as a result of the study, methodologies were defined to convert location data into meaningful insights by using statistical methods like weighted sum and the analytical hierarchy process. The functionalities in the proposed system have been designed, considering the roles of both buyers and sellers in the real estate business. In the proposed system, the location quality index framework provides overall insights on the location, the personalized insights and alternative locations are generated via the personal preference-based suitability analyzer and the price prediction system provides the current and future price fluctuations. The usefulness of image processing technologies and machine learning for making the sellers' journey easier on a real estate platform has also been assessed.
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    Digital Tool for Prevention, Identification and Emergency Handling of Heart Attacks
    (IEEE, 2021-09-30) Mihiranga, A; Shane, D; Indeewari, B; Udana, A; Nawinna, D. P; Attanayaka, B
    Heart attack is one of the most frequent causes of death in adults. The majority of heart attacks lead to death before any treatment is given to patients. The conventional mode of healthcare is passive, whereby patients themselves call the healthcare services requesting assistance. Consequently, if they are unconscious when heart failure occurs, they normally fail to call the service. To prevent patients from further harm and save their lives, the early and on-time diagnosis important. This paper presents an innovative web and mobile solution designed using it as Internet of Things (IoT) technology and Machine learning concepts to effectively manage heart patients, the ‘CARDIIAC’ system. This system can predict potential heart attack based on a set of identified risk factors. The system also can identify an actual heart attack using the readings from a wearable IoT device and notify the patient. The system is also equipped with emergency event coordination functionalities. Therefore, ‘CARDIIAC’ provides a holistic care for heart patients by effectively monitoring and managing emergencies related to heart diseases. This would be a socially important system to reduce the number of heart patients who die due to the inability to get immediate treatment.
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    Data-driven Business Intelligence Platform for Smart Retail Stores
    (IEEE, 2021-12-09) Eheliyagoda, D. R. M. R. R. D. R. S; Liyanage, T. K. G; Jayasooriya, D. C; Nilmini, D. P. Y. C. A; Nawinna, D. P; Attanayaka, B
    The following research paper presents the design and development of a data-driven decision support platform for the effective management of contemporary retail stores in Sri Lanka. This research has four core components, as a solution to the identified shortcomings. These components are Customer Relationship Management (CRM), Supplier Relationship Management (SRM), Price and Demand estimation, and Branch and Employee Performance Monitoring and Rating. The developed system has features such as product replenishment levels, decrease capital movement, reduced material wastage, better item assortment, provide supplier service efficiency, improve employee and branch-level efficiency, and elevated client delivery.This decision support system used Machine Learning (ML) technologies such as LSTM (Long short-term memory) and ARIMA (Autoregressive integrated moving average) models, Regression, Classification, and Associate Rule Mining Algorithms as key technologies. Data were obtained from websites such as Kaggle and other free platforms for the analysis of datasets. The resulting platform was able to perform with an accuracy of over 90% for all four core components with the tested data sets. The system presented would be particularly beneficial for the top management in retail stores to make effective and efficient decisions based on predictions and analyzes provided by the system.
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    Blockchain based Patients' detail management System
    (IEEE, 2020-12-10) Abeywardena, K. Y; Attanayaka, B; Periyasamy, K; Gunarathna, S; Prabhathi, U; Kudagoda, S
    In the data technology revolution, electronic medical records are a standard way to store patients' information in hospitals. Although some hospital systems using server-based patient detail management systems, they need a large amount of storage to store all the patients' medical reports, therefore affecting the scalability. At the same time, they are facing several difficulties, such as interoperability concerns, security and privacy issues, cyber-attacks to the centralized storage and maintaining adhering to medical policies. Proposed Flexi Medi is a private blockchain based patient detail management system which is expected to address the above problems. Solution proposes a distributed secure ledger to permits efficient system access and systems retrieval, which is secure and immutable. The improved consensus mechanism achieves the consensus of the data without large energy utilization and network congestion. Moreover, Flexi Medi achieves high data security principles based on a combination of hybrid access control mechanism, public key cryptography, and a secure live health condition monitoring mechanism. The proposed solution results in successfully deployed smart contracts according to the roles of the system, real time patient health monitoring with more scalable and access controlled system. The overall objective of this solution is to bring the entire medical industry into a common platform using a decentralized approach to store, share medical details while eliminating the need to maintain printed medical records.
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    A New Approach for Consumer Protection with Business Intelligence and Data Visualization
    (IEEE, 2021-12-09) Kariyawasam, K. S. T. U. S; Liyanaarachchi, L. A. A. S; Chathurabhani, H. M. N. N; Jayakody, A; Attanayaka, B
    According to the current market usage in Sri Lanka, there is no proper system to manage the buying and selling process of consumer goods and services. This paper presents a possibility of developing a systematic and essential food items management system using a mobile application with public and private interventions benefiting both the trade and the consumer is being explored. The authors discussed a methodology for managing essential food items through business intelligence and data visualization. It connects the trade and consumer sectors and the public and responsible private sectors related to this sector through a mobile application and presents data related to this sector through business intelligence forecasting and visualization methods. This research will also help reduce consumer problems by building transparency in the essential foodstuff sector. It will also systematically update the future of the essential food and beverage industry. The findings contribute to the body of knowledge on the New Approach for Consumer Protection with Business Intelligence and Data Visualization.