Browsing by Author "Sriyaratna, D"

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Banana Disease Identification Using Machine Learning Based Technologies and Weather-Based Dispersion Analysis
(IEEE, 2022-12-09) Kothalawala, M.U.; Gaveshith, M.G. K; Tharaka, A.H.D.H.; Punchihewa, I.A; Sriyaratna, D
Banana is the fourth most important food crop in the world as well as the most important and popular fruit crop in Sri Lanka. Banana leaf diseases are becoming one of the most important factors affecting agricultural products. As a result of these diseases, the quantity and quality of agricultural produce have drastically decreased. Hence, early detection and classification of banana leaf diseases are becoming more important than ever. But the ancient method of disease identification, visual observation is no longer helpful in this matter as it requires significant knowledge and experience related to banana diseases and symptoms which present farmers severely lacks. Therefore, using ICT-based approaches such as autoML, deep learning, natural language processing and APIs are very important towards the efficiency of the disease identification process and the accuracy of the diagnosis as well as keeping farmers synced with the information related to their plantation such as recent threats and nearby threats.
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Centralized Road Infrastructure Information Collection and Processing System for Sri Lanka
(IEEE, 2018-12-21) Musthafa, M; Magenthirarajah, S; Rauf, A. A; Balendran, K; Kodagoda, N; Sriyaratna, D
The following topics are dealt with: learning (artificial intelligence); mobile computing; feature extraction; support vector machines; natural language processing; image classification; Internet; security of data; power engineering computing; decision trees.
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EasyChat: A Chat Application for Deaf/Dumb People to Communicate with the General Community
(Springer, Cham, 2022-07-07) Sriyaratna, D; Samararathne, W. A. H. K.; Gurusinghe, P. M.; Gunathilake, M. D. S. S.; Wijenayake, W. W. G. P. A.
Sign Language is closely associated with the deaf and dumb community to communicate with each other. However, not everyone understands sign language or verbal languages, so these communities need proper ways to communicate online. Therefore, this paper presents EasyChat, a sign language chat application that can translate three main sign languages into Simple English text as well as Simple English text into sign language, which would benefit for deaf/dumb community to express their ideas with the general community by simply capturing their British Sign Language (BSL) or Makaton gestures/symbols or lip movements. These steps are handled by four components. The first component, Convert BSL into Simple English, and the second component, handles Lip Reading conversion. The Makaton gesture and symbol conversion component produces a simple English text-formatted output for identified Makaton hand signs. Finally, the Text/voice to Sign Converter works on converting entered English text back into the sign language-based images. By using these components, EasyChat can detect relevant gestures and lip movement inputs with superior accuracy and translate. This can lead to more effective and efficient online communication between the community of deaf/dumb individuals and the general public.
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Mixed Reality Supermarket: A Modern Approach into Day - to - Day Grocery Shopping
(IEEE, 2020-11-04) Weerasinghe, N; Jayawardena, S; Mahawatta, D; Navaratne, H; Sriyaratna, D; Gamage, I
In the modern world where there are massive trends in development and implementation of new technologies, combination of Virtual Reality and Augmented Reality is one which has key potential in an everyday developing world. The main concept behind Virtual Reality is simply immersing the user in a virtual environment at the comfort of their own place. This is done by creating a computer-generated 3D environment with hand gestured navigation system combined with concepts of voice recognition, image processing and machine learning that explores intense human interactions. As we are in the 21st century, where technological transformations are most certainly creating blurry lines between fiction and reality, more and more people have the need to fulfill their daily requirements easily without wasting their valuable time. Buying day to day needs from a supermarket is one of the main activities that each one of us struggle to go through during the day. Targeting the above simple daily activities, we are making an effort to apply VR Technology to this area through this research and thus trying to provide a rather new technological experience for purchasing items from a supermarket. This can be beneficial to the consumers to minimize their valuable time wasted, and also, they will be able to get the real experience of shopping while getting exposure to marketing.
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Optimization of Volume & Brightness of Android Smartphone through Clustering & Reinforcement Learning (“RE-IN”)
(IEEE, 2018-12-21) Abeywardhane, J. S. D. M. D. S; de Silva, E. M. W. N; Gallanga, I. G. A. G. S; Rathnayake, L. N; Wickramaratne, C. J; Sriyaratna, D
Smartphone has become one of the most significant piece of technology that humans were able to produce in the 21st century. It has become our life companion; hence the features of the smartphones have developed in advance. But, some features may not work as expected. For instance, auto brightness changing feature is now actualized with smartphones, yet we alter the brightness according to our preference. In the same manner, considering the volume of our smartphone it doesn't change according to our preference subsequently. This research will develop a mobile application (“RE-IN”) to overcome this issue for Android smartphones. Since android smartphones allow accessing its hardware layer we can roll out improvements as we need, yet Apple doesn't permit to proceed with its hardware layer thus hard to do this for the iPhone users. By utilizing the RE-IN mobile application users may have to encounter an optimal brightness and volume on their Android smartphones agreeing the present condition of smartphone users are in. RE- IN application will keep running as a background application on an Android smartphone. When the client changes the brightness and volume as his/her preference. At that point, the reinforcement learning algorithm over the time application will distinguish how to control user's smartphone's brightness and volume relying upon the user's circumstance. When client surrounding is loaded with light, the framework will modify brightness for his/her preference. The client doesn't need to do this manually. Moreover when the client is at the too much boisterous place all of a sudden gets a call from someone; client's smartphone amplifier volume will change consequently and solaces the client's discussion. To actualize this framework it is relied upon to reinforcement learning and machine learning as the research area. By finishing the literature review, research group unable to find an Android mobile application which automates the process of volume and brightness of the Android smartphone as per user preference. After using the reinforcement learning algorithm to learn the data set then distribute the process, using client-server model and come up with a clustering algorithm(K-means algorithm) to share common attributes by considering geographical area which they live in and variables like age, gender, how they interact with the device etc. In addition, this system will identify abnormal behaviors of some particular users. RE-IN will identify the users who are keeping volume level to the highest and brightness level to its maximum and notify them in advance.
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PRODEP: Smart Social Media Procrastination and Depression Tracker
(Institute of Electrical and Electronics Engineers, 2022-11-04) Kulatilake, T.T; Liyanage, P.L.R.S.; Deemud, G.H.K.; De Silva, U.S.C; Sriyaratna, D; Kugathasan, A
Procrastination refers to the voluntary delay of urgent tasks and can have several negative consequences such as stress, health issues and academic underachievement [47]. It is viewed within physiological research as a self-regulation failure [48]. Similar to procrastination, another severe problem which comes up within lots of people including students and teenagers is "Depression". Depression is a massively widespread problem among people around the world as well as in Sri Lanka [49]. As a result of procrastination and depression, students has to face academic underachievement. One of the main cause of these widespread problems are Social media over-usage [50]. Therefore this paper presents a new tracker which presented as a mobile application with four main components. This research study is about identifying and tracking users' facial emotions and eye-aspect ratio to analyze real emotions of the user via device inbuilt webcam to identify user fatigueness and procrastination. This study also analyzes user behavior in two selected social media platforms which are Facebook and Twitter and identifies the negativity and depressiveness of "Sinhala"content using Machine learning based Sentiment analysis approaches. Also as a companion, this paper introduces a chat-bot which communicates with the user in "Singlish"language. Our final products will be a complete mobile application which generates reports to the user based on the analysis done in the four components. As future work we will introduce AutoML approaches instead of traditional machine learning based approaches.
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Realty Scout – Smart System for Real Estate Analysis & Forecasting with Interactive User Interface
(IEEE, 2022-07-18) Hapuarachchi, H. A. V. P. U; Manoratne, M. D; Gamlath, K. G. B. K; Vithane, S. G. G; Sriyaratna, D; Ravi Supunya, N. H. P
The real estate industry is one of the highest income generating sources in the country. As the country moves toward a highly diversified economy, the role of real estate has become a more important part of the country’s economy. However, the state of the local real estate industry is yet to improve and is currently lagging the technology curve. As a result of this issue, useful information is not made available to the end-users. Therefore, the real estate industry needs to improve its adoption of ongoing technologies to move from traditional to smart real estate industry. Therefore, we developed a Smart Real estate system called "Realty Scout" which can analyze and forecast real estate information accurately. The "Realty Scout" is implemented with a highly interactive view of the properties with a given virtual tour for the users to enhance the user experience. This smart real estate system also collects data on property values, in addition to a trained data set, to forecast future property values. Certain machine learning algorithms are used in the backend to generate future values. An accurate and fast prediction of the real estate value is important to buyers, sellers, and other stakeholders. Furthermore, by gathering users’ personal information and tracking their search history through the system, the system recommends properties to users based on collected data. As potential users of the system, they can gain an advantage from this feature by finding their desired property without spending more time. In addition, this system aimed to give advanced property filtrations options to the user. Building up a smart system for the real estate industry would be an advantage for all stakeholders who are actively engaged with the real estate industry.
Open Access
A Singlish Supported Post Recommendation Approach for Social Media
(SCITEPRESS – Science and Technology Publications, 2022-01) Sandamini, U; Rathnakumara, K; Pramuditha, p; Dissanayake, M; Sriyaratna, D; De Silva, H; Kasthurirathna, D
Social media is an attractive means of communication which people used to exchange information. Post recommendation eliminates the overflooding of information in social media to the users’ news feed by suggesting the best matching information based on users’ preference that in return increase the usability. Social media users use different languages and their variations where most of the Sri Lankan users are accustomed to use Sinhala and Romanized Sinhala. However, post recommendation approaches used in current social media applications do not cater to code-mixed text. Therefore, this paper proposes a novel post recommendation approach that supports Singlish. The study is separated into two major components as language identification and transliteration, and post recommendation. In this study, script identification was performed using regular expressions while a Naïve Bayes classification model that accomplished 97% of accuracy was employed for language identification of Romanized text. Transliteration of Singlish to Sinhala was conducted using a character level seq2seq BLSTM model with a BLEU score of 0.94. Furthermore, Google translation API and YAKE were used for Sinhala-English translation and keyword extraction respectively. Post recommendation model utilized a combination of rule-based and CF techniques that accomplished the RMSE of 0.2971 and MAE of 0.2304.
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Smart Driving Assistance System to Elevate the Driving Experience in Sri Lanka-Dryv Assist
(IEEE, 2018-10-02) Rauf, A. A; Musthafa, M; Magenthirarajah, S; Balendran, K; Kodagoda, N; Sriyaratna, D
Smartphones have become an important part of our lives and unfortunately also the cause of increasing rate accidents due to driver distraction. However, the increased capabilities of smartphones have helped driving easier through applications such as navigation. Even with these functionalities, it is still required that the driver be vigilant by watching out for road signs and pedestrian crossings, figuring out appropriate speeds and avoid unintended lane departures. In this paper we present a driver assistance mobile system that is accessible through smartphones and would aid the user on aforementioned tasks thus making the driver more efficient.
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STEP UP: Systematically Motivating the Children with Low Psychological Maturity Level and Disabled Children using Gamification and Human Computer Interaction
(IEEE, 2022-07-18) Dharmarathne, R. S. C. K; Medagedara, K. A; Madhubashinee, N. B. W. N.; Maitipe, P. T.; Sriyaratna, D
Children are the future of this world. Therefore, teaching them to have a better future is very important. Also, as the adults we have to motivate them to overcome the obstacles and challenges they face throughout their lifetime. When considering about the children, there are various types of children in our society. As examples there are children with special needs and there are children who are mentally and physically stable. Children with special needs require special attention than the other children. These kinds of children with special needs have various types of development disabilities. They are children with low psychological maturity level, autism, down syndrome, genetic disorders etc. We have proposed a system to motivate these children who are with low psychological maturity level named as ‘STEP-UP’. This system is a combination of four individual modules that have the common goal to motivate these kinds of children which were implemented using gamification, Image processing, machine learning and Human Computer Interaction. One individual module is focused on disabled children, and it will motivate those children using gamification. Another two modules are focusing on the children who are with low psychological maturity level. And that will motivate those kinds of children using gamification and HCI based technologies like Virtual Reality. The other module is a protocol to secure the data sent between the system and the database. The common goal of this overall STEP-UP system is to motivate the children with low psychological maturity level and disabled children.