Research Publications

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Subject: search.filters.subject.mobile application

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Now showing 1 - 6 of 6
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    Press plus-interactive mobile application for effective news reading
    (IEEE, 2017-08-22) Gamage, N. D. U; Udeshitha, K. L. A. D; Jayadewa, K. W. C; Senanayake, S. M. N. K. B; Samarakoon, S. M. U. P; Hennayake, T. M
    Presently younger generation relies more on mobile applications to acquire information instead of traditional methods. Hence, customary approaches of information distribution required to reinforce by modern technology. Especially newspaper industry needs a certain technology enhancement to make the reading experience more interesting and pleasurable for readers. The “Press Plus” is an application to form an association between the newspaper and modern technology to promote newspaper reading by allowing the user to watch news related videos via their smartphone. This application uses scanning and retrieving data through QR code technology with the collaboration of mobile & web application. The mobile application provides three main facilities; Video playback controller; which allows users to scan printed QR code and play news related videos, Top list; which permit users to rate and view top rated videos and live stream; which facilitate users to watch live events independent from location and time. Additionally to the application, a separate survey was conducted to evaluate newspapers reading habits of youth in Sri Lankan context. Survey results indicate that a large number of individuals prefer newspapers reading via modern technologies such as mobile applications. “Press Plus” is beneficial to both newspaper readers and publishers in many ways. It helps to enhance a number of newspaper readers by making it more attractive and pleasurable. In addition, readers get a novel experience while reading newspapers. Publishers indirectly can gain revenue through branding, marketing and event promotions via this application.
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    Zero Food Waste: Food wastage sustaining mobile application
    (IEEE, 2019-12-05) Gunawardane, M. D. C. J; Pushpakumara, H. A. N; Navarathne, E. N. M. R. L; Lokuliyana, S; Kelaniyage, K. T. I; Gamage, N
    Food is the third most essential part of everyone's lives. But generally global food loss and wastage amount has been increased to an amount between one third and one half of all food produced. The reasons can be specified as a lack of appropriate planning, purchase and preparation of too much food, over the preparation of food in restaurants. As a solution, the project team has implemented a mobile application which is capable of capturing an image of a food and identify it and measure the weight. With the gathered data, the implemented system contains an intelligent agent providing suggestions of food recipes with leftover foods and several additional features such as guidance to the user to prepare any kind of food with the help of an interactive Chatbot as well as the user has been directed to get healthy meals by considering the previous meal plans and statistical report analysis. As the results, the implemented recipe generation algorithm of sentimental analysis has obtained 76% accuracy and moreover the team has obtained more accurate unique technique for weight estimation than the currently available calibration techniques.
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    Zero Food Waste: Food wastage sustaining mobile application
    (IEEE, 2019-12-05) Gunawardane, M. D. C. J; Pushpakumara, H. A. N; Navarathne, E. N. M. R. L; Lokuliyana, s; Kelaniyage, K. T. I; Gamage, N
    Food is the third most essential part of everyone's lives. But generally global food loss and wastage amount has been increased to an amount between one third and one half of all food produced. The reasons can be specified as a lack of appropriate planning, purchase and preparation of too much food, over the preparation of food in restaurants. As a solution, the project team has implemented a mobile application which is capable of capturing an image of a food and identify it and measure the weight. With the gathered data, the implemented system contains an intelligent agent providing suggestions of food recipes with leftover foods and several additional features such as guidance to the user to prepare any kind of food with the help of an interactive Chatbot as well as the user has been directed to get healthy meals by considering the previous meal plans and statistical report analysis. As the results, the implemented recipe generation algorithm of sentimental analysis has obtained 76% accuracy and moreover the team has obtained more accurate unique technique for weight estimation than the currently available calibration techniques.
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    SURAKSHA e-Caretaker: Elders Falling Detection and Alerting System using Machine Learning
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Mendis, L.; Hathurusinghe, S.; Epa, H.; Edirisinghe, T.; Wickramarathne, J.; Rupasinghe, S.
    People become unable to perform tasks that were done at the younger ages as they were when the ages pass with time. Falls play a major issue in the lives of elderly people as the physical and mental quality of life is dependable on the effects of falls. This research presents an e-Caretaker SURAKSHA which is an elder falling detection and alerting system based on Machine Learning concepts. Researchers that have been done in this area have produced different solutions to detect only the falls but not to automatically detect and notify them to the caretakers. This solution serves as a smart wearable device that is capable of automatically monitoring real-time postures, detecting sudden falls, possible arrhythmia conditions of the heart of the fallen person, and daily route deviations along with the fallen location which is finally notified to the caretakers through a mobile application. According to the performed studies, python model development was used to implement the system through Machine Learning concepts by referring to the Markov model, Prophet model, and Naïve Bayes algorithms. This solution provides the results of this research with an accuracy of around 89.9% leading to a successful product in the domain. Keywords—
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    Amazon Biology: An Augmented Reality-Based E-Book for Biology
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Somakeerthi, D.C.S.; De Silva, G. W. I.U.; De Silva, L.D.T.; Chandrasiri, S.; Joseph, J.K.
    Biology is a conventionally struggling subject to learn from both high school and college students due to its complexity. Students are used to learning Biology from various methods such as reading textbooks, attending lectures. Biology is based on more practical and most of the schools not available proper lab facilities, anatomic structures, and resources to learn the module easily. And teachers who teach the module face a considerable number of issues when delivering the concepts. Some of them face unavailability of teaching aids, time-consuming, lack of lecture materials. Apart from that, the nature of the topic and the teaching style are the main learning problems faced by the students. Therefore, students do not learn the concepts perfectly and interest in the module has been reduced day by day. To overcome these difficulties “Amazon Biology,” mobile application has been proposed. The application consists of three major modules including image processing for the plant classification, augmented reality for human anatomy, and gamification. The proposed application has used the techniques in augmented reality and game-based learning. The developed system delivers nearly 85% level of accuracy and provides more advantages for students. They are effective and efficient learning, teaching via visual materials, and practical.
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    Mobile Based Solution for Vehicle Assistance
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Wickrama, M.A.D.; Dharmakeerthi, D.S.C.; Balasooriya, S.A.; Ekanayake, U.M.I.S.; Gamage, M.P.; Amarasena, N.
    At present majority of the people in Sri Lanka use private vehicles as their mode of transport. Vehicle breakdown is a main issue faced by the vehicle drivers onroad. But depending on the nature of the underlying reason of breakdown, some minor failures can be fixed by the users themselves if they have the basic knowledge, which the majority lacks. If the vehicles undergo a breakdown in a remote location, getting help or finding the required spare parts become a hindrance. In addition to that, vehicle owners need a platform to get a clear idea and comparisons of vehicle insurance companies and insurance packages. As a solution for the above concerns, authors decided to develop a mobile application to assist drivers with vehicle breakdowns and maintenance along with some extra functions. The suggested system's major functions include providing a personal assistant to aid with vehicle breakdowns, predicting upcoming vehicle maintenance procedures, providing trustworthy spare part pricing, and recommending the best insurance providers to customers. In order to develop the product several technologies and techniques including Natural Language Processing, Neural Networks, and Sentimental Analysis are used. Customers are extremely satisfied with the product's efficacy, according to the results of the survey.