1st International Conference on Advancements in Computing [ICAC] 2019
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/1599
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Publication Embargo Plus Go: Intelligent Complementary Ride-Sharing System(IEEE, 2019-11-21) Wickramasinghe, V; Edirisinghe, A; Gunawardena, S; Gunathilake, A; Kasthurirathna, D; Wijekoon, JCurrently the world population is gathering to the cities making huge traffic congestion throughout the day. This has drawn serious attention to the society incurred to implement smart solutions for traffic management. One of the prominent problems for traffic congestion is the number of vehicles entering the cities is high. It is a popular fact that the solitary travelers coming to a defined destination make the vehicles underutilized. Therefore, this study proposes a solution to implement a new ride-sharing platform: Plus Go, to reduce this underutilization. Plus Go matches the travelers by considering the designation, traveler preferences, shortest path details, and the ratings of the users. Moreover, Plus Go intelligently estimates the traveling cost based on the fuel consumption of the vehicle, distance traveled, and the time taken to reach the destination. The proposed solution matches the travelers with 98% accuracy ensuring that ride-sharing is an effective solution to reduce the number of vehicles entering the cities.Publication Embargo SmartOne: IoT-based Smart Platform to Manage Personal Water Usage(IEEE, 2019-11-21) Vithanage, J; de Silva, R; Karunaratne, K; Silva, M. D; Bogoda, P; Kankanamge, R; Kehelella, P; Jayakody, K. D; Wijekoon, JThe origin of life is water, and consistent water consumption is essential for the proper functioning of human organs. Thus, regular hydration is vital for human beings because improper hydration leads to diseases such as cholera, diarrhea, bladder stones, and kidney issues. However, maintaining a sufficient and regulated water intake is challenging for many personal as the livelihood, i.e., busy life schedule, is getting complicated, and sometimes due to limited access to clean water. To this end, the SmartOne water bottle was introduced to enable effective management of daily water requirements and to ensure users drink good quality water. The initial prototype of the water bottle was implemented as a combination of hardware and mobile application, and it was evaluated in terms of measuring water goal, quality, drink and sift event detection.Publication Embargo Recognition and translation of Ancient Brahmi Letters using deep learning and NLP(IEEE, 2019-12) Wijerathna, K. A. S. A. N; Sepalitha, R; Thuiyadura, I; Athauda, H; Suranjini, P. D; Silva, J. A. D. C; Jayakodi, AInscriptions are major resources for studying the ancient history and culture of civilization in any country. Analyzing, recognizing and translating the ancient letters (Brahmi letters) from the inscription is a very difficult work for present generation. There is no any automatic system for translating Brahmi letters to Sinhala language. However, they are using manual method for translating inscriptions. The method that used in epigraphy is being taken a long period to decipher, analyze and translate the inscribed text in inscriptions. This research mainly focuses on recognition of ancient Brahmi characters written the time period between 3 rd B.C and 1 st A. D. First, we remove the noise, segment the letters from the inscription image and convert it into the binary image using image processing techniques. Secondly, we recognize the correct Brahmi letters, broken letters and then identify the time period of the inscriptions using Convolution Neural Networks in deep learning. Finally, the Brahmi letters are translated into modern Sinhala letters and provide the meaning of the inscription using Natural Language Processing. This proposed system builds up solution to overcome the existing problems in epigraphy.Publication Embargo gCodex: A tool to analyze software repositories over time (visualization)(IEEE, 2019-12-05) Nuzrath, S; Amarasinghe, N. H; Liyanage, K. T; Suriyawansa, K; Madanayake, D. P; Kodagoda, NgCodex is a novel tool for analyzing and visualizing the code base in a manner that it allows its users to get an idea of the insights of the codebase. This tool was built to analyze code bases and it supports any language. In addition, it provides a visualization of the file structure, rate of change of complexity and defects rate. In order to improve the quality of the software and the controllability of the project, it is necessary to control the complexity of the software by measuring the associated aspects and visualize those in a descriptive and attractive dashboard. Using the existing tools, it is not possible to visualize the rate of change of code complexity with the time. This tool uses Cyclomatic complexity, line of code and Halstead complexity metric and their impact on the software quality, and visualize those in a descriptive dashboard which provides analytics that describes and summarize past trends.Publication Embargo A Mobile Application to Predict and Manage High Blood Pressure and Personalized Recommendations(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Rajapaksha, S.; Abhayarathne, W.J.A.; Kumari, S.G.K.; De Silva, M.V.L.U.; Wijesuriya, W.M.S.M.The purpose of this investigation is to present a mobile application using AI expert and how to predict and manage high blood pressure and provide personalized recommendations to lower it. Basically, the system interprets the inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to the diversity of food components and a large number of dietary sources, it is challenging to perform a real-time selection of diet patterns that must fulfill one’s nutrition needs and with considering your health issues and diseases. In this research, to address this issue to present an android based system, called Smart Blood Pressure Recommendation app. The purpose of this system is to allow patients to have an easy way to monitor their health and to see how their blood pressure has changed over time. This offer advice or suggestions, without having to schedule an appointment. As the system continues to gather data from a patient, it begins to offer advice its own if it finds that the patient’s current conditions fit a certain condition or pattern. To generate a recommendation, it refers to an Ontology based data model. The data model gains information about its knowledge by doctors and nutritionists that can be used by AI expert. This research helps users to identify their previous record charts of blood pressure, reliable alarms for user blood pressure medication, popup notifications, build healthPublication Embargo Smart wheelchair to facilitate disabled individuals(IEEE, 2019-12-05) Jayakody, A; Nawarathna, A; Wijesinghe, I; Liyanage, S; Dissanayake, JThis paper describes the design and implementation of a voice controlled smart wheelchair for disabled whom the manual operation is difficult due to lack of physical strength. The main objective of this research is to develop a smart wheelchair to facilitate disabled individuals which can be operated with lesser effort while operating the wheelchair. The proposed wheelchair can be controlled through voice commands which enables the user to control the wheelchair with less effort. This aids the disabled in carrying out daily activities independently within indoor environments. The proposed solution has five modules namely, speech recognition module, obstacle avoidance module, autonomous navigation module, health monitoring module, and central system controller. The wheelchair operates in two modes called manual mode and the autonomous mode. This paper presents a smart wheelchair that makes the disabled individuals' life easier with technology. Further this paper elaborates testing and evaluations carried out to prove the proposed title.Publication Embargo Automated Smart Checkup Portal Network System to Check the Vision and Hearing of the Patients.(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Dias, A.A.T.K.; Vithusha, J.; Liyadipita, L.A.M.T.J.; Abeygunawardhana, P.K.W.The human eye and ear are impressive systems in the body. Vision and Hearing are the main functions of those organs. We should regularly check our vision and hearing, It's the most reliable ways to maintain good vision and hearing. Not only that, every patient must keep a medical history and previous checkup records, those related to vision and hearing and those results should be real-time processed. Therefore, we have built an Automated Centralized Smart EE (eye and ear) Checkup Portal Network System. We have designed and developed an automated centralized vision and hearing checkup rooms network, Automated centralized live traffic indicating cloud-based web application to establish in every hospital.Publication Embargo Drown Prevention and Flood prediction using smart embedded devices(IEEE, 2019-12-05) Samarasinghe, D; De Silva, P. M; Mudalige, T. U; Gamage, M. K. I; Abeygunawardhana, P. K. WDrowning and Flood becomes major negative impact to the mankind and infrastructure. Drowning is caused by the when person go into deeper areas or else due to a person's health condition. Flood is a natural disaster commonly caused by the run of rivers due to excessively highly rainy season or due to environment effect or global warming effect. Hence IoT with sensor technology support us to efficiently cover up this impact for mankind. This research support for each mankind to survive from the drowning threat and this may help for people to survive from the natural disaster like flooding. This research presents two IoT Devices consisting with sensors and monitoring system to determine the flood level, the user condition and water level when user in the water. Then generating alert via the mobile application to notify the user. Machine learning algorithms were implemented to perform the level classification.Publication Embargo Film-it: Virtual Location Scout and Movie Production Planning Assistant for Film Industry in Sri Lanka(IEEE, 2019-12-05) Wijesekera, C; Kosgahakumbura, D; Alwis, J; Kaluarachchi, B; Thelijjagoda, SThe global multi-billion-dollar industry of film making is not that healthy in Sri Lanka. Film industry majors say that this happens because not enough local movies are made within the country by local artists. Therefore, there is no problem with the number of creative minds in the country. The reason for the lack of local movies made annually in the country is because it takes a lot of effort, time and money. And if the movie fails, millions get wasted. Movies mostly fail because they are not organized very well from the beginning. Everything starting from the script to the final tickets that are going to be sold needs to be planned during pre-production. If pre-production fails, production fails. If production fails, post-production fails. The success or the failure of a movie starts right at the beginning of the pre-production phase. This phase contains many processes that are very important to carry out the production phase. One of them is location scouting. Since film industry is mostly based on aesthetic pleasure of the people in the society, scenic beauty is a must when choosing locations for a movie. “Film-it” is an application that is capable of giving all kinds of assistance in location scouting and much more in movie planning. That is the reason it is called “The Virtual Location Scout and Movie Production Planning Assistant”. This application has already proved to be beneficial for Sri Lankan movie directors and producers to do months tasks in much less time which is a huge improvement in the industry that saves so much time and money. Major roles in the industry states that this application will take the Sri Lankan movie industry to a whole new level.Publication Embargo MOOCs Recommender Based on User Preference, Learning Styles and Forum Activity(IEEE, 2019-12-05) Hilmy, S; De Silva, T; Pathirana, S; Kodagoda, N; Suriyawansa, KWith the development of MOOCs (Massive Open Online Courses) as a major source of e-learning materials, the number of MOOCs available today has become dauntingly high. Furthermore, MOOCs are produced in many different video production styles and these styles play an important role in helping the consumer stay engaged and interested in the course throughout. However, due to the sheer number of MOOCs available today, it is becoming increasing difficult to find the MOOCs that suits your personal preferences and the learning style. This paper describes how thousands of MOOCs that belong to different styles are identified efficiently while each consumer's preferences are identified to provide personalized MOOC recommendations. Furthermore, the paper describes how forums can be analyzed to identify how consumers feel about MOOCs that they followed, which is a crucial metric in recommending MOOCs to consumers.Publication Embargo VTutor: A Platform for Improving Searchability and Interactivity of Recorded Lectures(IEEE, 2019-12-05) Karunaratna, D; Hettiarachchi, I; Fernando, S; Epa, S; Kodagoda, N; Suriyawansa, KRecorded lectures have gained popularity as a method of delivering lecture content as they give learners a host of distinct advantages such as the ability to follow lectures without time or location constraints and to consume the lectures at their own pace. However, despite such benefits, they have a tendency to be lengthy and tedious to watch. They also prove cumbersome when precise information needs to be extracted from the content. Another drawback is that recorded lecture videos fail to show the connection between the lecture and its support material such as slides and questionnaires. Though many of the existing platforms allow editing lecture videos for more interactivity, the methods employed by these platforms have always been manual, and therefore time intensive. VTutor is a web platform that aims to address these drawbacks by introducing automation into the video enhancement process, eventually combining the lecture material to create an enhanced user experience. Specifically, VTutor allows users to navigate through a lecture video using subtopics, its corresponding slides and code samples. Furthermore, it is equipped with the ability to automatically generate questions by scraping the internet based on provided keywords thus improving the level of engagement that a learner has with the lecture.Publication Embargo Traffic Density Estimation and Traffic Control using Convolutional Neural Network(IEEE, 2019-12-05) Ikiriwatte, A. K; Perera, D. D. R; Samarakoon, S. M. M. C; Dissanayake, D. M. W. C. B; Rupasignhe, P. LThe existing traffic light control systems are inefficient due to the usage of predefined algorithms on offline data. This causes in numerous problems such as long delays and a wastage of energy. Estimation of traffic density indirectly affects in decreasing the high traffic congestion which will occur due to the less planning of transportation infrastructure and the policies. The goal of this research is to introduce an applicable method to improve the existing static traffic signal system into a dynamic system. As an approach we analyze the use of machine learning algorithms to measure the traffic density to tackle this research problem of high traffic congestion. The main target is to implement this system for the four-way junctions since it is a place where the possibility of having a traffic congestion seems to be high. With use of these traffic density estimation algorithm, crowd density estimation and signal handling we conduct experiments on minimizing the congestion at four-way junctions. We decided on using convolutional neural networks as an advanced machine learning method to increase the accuracy of the learning algorithm.Publication Embargo Comprehensive Forensic Data Extraction and Representation System for Windows Registry(IEEE, 2019-12-05) W. De Alwis, C; Rupasinghe, LComputer forensics is the process of methodically examining computer media (hard disks, diskettes, tapes, etc.) for evidence. When considering computer forensics, registry forensics plays a vital role because it helps identifying system configurations, application details, user configurations and helps in finding registry malware. Therefore, it is significant to extract this registry information to simplify the investigations for forensic professionals. At present, tools are limited to few commonly used registry information and there is a much border area to cover. Investigators have to manually search for the registries for required artifacts. But the nature and complexity of the registry file structure limits most of the investigators using these registries. Limiting this registry analysis only to the physical registry files and not considering the ability of extraction of registry information from Volatile Memory is another significant issue in registry forensics. Because these tools are only rely on the physical registry files and cannot extract registry artifacts from Volatile Memory. In order to cater to this problem, this research provide a comprehensive solution to registry analysis. This system is capable of extracting registry information from both physical registry files and Volatile Memory.Publication Embargo An Automated Tool for Memory Forensics(IEEE, 2019-12-05) Murthaja, M; Sahayanathan, B; Munasinghe, A. N. T. S; Uthayakumar, D; Rupasinghe, L; Senarathne, AIn the present, memory forensics has captured the world's attention. Currently, the volatility framework is used to extract artifacts from the memory dump, and the extracted artifacts are then used to investigate and to identify the malicious processes in the memory dump. The investigation process must be conducted manually, since the volatility framework provides only the artifacts that exist in the memory dump. In this paper, we investigate the four predominant domains of registry, DLL, API calls and network connections in memory forensics to implement the system `Malfore,' which helps automate the entire process of memory forensics. We use the cuckoo sandbox to analyze malware samples and to obtain memory dumps and volatility frameworks to extract artifacts from the memory dump. The finalized dataset was evaluated using several machine learning algorithms, including RNN. The highest accuracy achieved was 98%, and it was reached using a recurrent neural network model, fitted to the data extracted from the DLL artifacts, and 92% accuracy was reached using a recurrent neural network model, fitted to data extracted from the network connection artifacts.Publication Embargo Efficient Agricultural Sensor Network with Disease Detection(IEEE, 2019-12-05) Gunathilaka, M. D. N; Lokuliyana, S; Udurawana, A. W. G. C; Dissanayaka, D. M. A. S; Jayakody, AThe smart Agriculture concept is a new trending topic in making traditional agriculture task automation to make them more effective and efficient to suit current human requirements. With machine learning and image processing technologies those tasks are made more robust and accurate while maintaining the low cost made this research inspired to adopt Sri Lankan farmers to develop a real-time disease detection monitoring system with wireless sensor node for crops, so that would be able to harvest and store energy for battery-free operation using supercapacitors and technologies such as Maximum Power Point Tracking. The main outcomes of this nodes are to monitor the growth environment and also the crop for diseases by using image processing and machine learning techniques in order to cultivate a better fruit overall. The wireless sensor node can be adapted to be used on multiple types of remote farms. Pineapple (Ananas comosus) was selected as the test crop for the research which is a fruit grown widely in tropical countries in large fields. The texture, shape of the fruit and the taste of pineapple changes due to various conditions. The final system makes monitoring the crop for diseases a lot effective while making monitoring the growth conditions more efficient compared with what's available on the market.Publication Embargo Ayurvedic Knowledge Sharing Platform with Sinhala Virtual Assistant(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Jayalath, A.D.A.D.S.; Nadeeshan, P.V.D.; Amarawansh, T.G.A.G.D.; Jayasuriya, H.P.; Nawinna, D. P.Apart from western medicine methods Ayurveda medicinal system is a very huge and better resulting medicinal technique. In these Ayurveda methods identification of indigenous plants to predict the medicines is very important and must do very carefully. Generally main components that we use to identify a plant are leaf, flower, trunk and root etc. Among these features, we use images of leaves and flowers. To do this we are using deep learning based CNN approaches and machine learning and technologies. Those are OpenCV, and Tensorflow classification algorithm. According to the evidences that we gathered from surveys and interviews that we conducted with the responsible parties we could find out that lots of people don’t have much knowledge about indigenous medicinal plants and their Ayurveda treatment methods. To overcome this problem we implemented Ayurveda information centralized chatbot which is able to answer user’s questions relevant to the Ayurveda and indigenous medicinal plants. Chatbot will analyze the question that user asks and will provide answers according to that. Another useful feature of this system is it provides relevant information of Ayurveda doctors. So users can find doctors according to their needs and they are able to rate and give recommendations for the doctors. That will be help others to find doctors more easily and efficiently without any doubt.Publication Embargo Wedaduru-An Intelligent Ayurvedic Disease Screening and Remedy Analysis Solution(IEEE, 2019-12-05) Bandara, R. I. S; Prabagaran, S; Perera, S. A. K. G; Banu, M. N. R; Kahandawaarachchi, K. A. D. C. PHeart disease is one of the most common diseases worldwide. According to Ayurveda, behavior of humans associated with food habits are root causes of heart diseases. This research focuses on providing a diagnostic tool for heart diseases through a web- based application, where the diagnosis will be directed through the practices of Ayurveda. The proposed web-based solution `Wedaduru' uses artificial intelligence (AI), which analyses the physical appearance of the patient through image processing, and symptoms using a model with questionnaires. Thereby, the solution/application identifies remedies and treatments using supervised learning and provide herb details including the commonly grown areas of herbs using Google API. Heart diseases are predicted with an accuracy of over 86% and classified into four categories as Vataja, Pitaja, Kaphaja and Krimija. The proposed system provides a detailed report of the diagnosed Heart disease along with remedy treatments, diet plan and herbal plants along with locations where herbs can be found. At the end, `Wedaduru' will provide awareness in Ayurveda medicines and its values to common people.Publication Embargo Online Music Platform to Create Interaction between Music Artists and Fans(IEEE, 2019-12-05) Rupasinghe, L; Fernando, W. J. C; Perera, A. G. M. M; Weerasooriya, D. G. T. V; Perera, K. A. D. W. H. DIn music industry, purchasing of digital music has been popular lately. This online music platforms make music artists to upload their piece of work and their fans will purchase the songs. When purchasing songs, some people may face problems like not secured way or non-transparency of currency and data transaction. The transparency of currency and data files are not there in most of the platforms, it will make doubt the users about the transactions. Also, People frequently change their music listening behaviors. Which scales by the genres, artist, or specific tracks. When someone wants to find a song which was heard for the first time, he/she would not be able to remember the song at once. If the song is in other language it is difficult to find that because less knowledge of that language. If that language of the song can be translated to English language. But what if they remember nothing of the song or singer but know how to sing or hum a part of that song. And also when a person is singing or humming there are some situations lead to errors such as not in the right pitch, background noise.Publication Embargo MOOCRec 2 for Humanities-Learning Style Based MOOC Recommender and Search Engine(IEEE, 2019-12-05) Fazuludeen, F; Vijayakumaran, G; Mahroof, Z. A; Kodagoda, N; Suriyawansa, KIntroduction of Massive Open Online Courses (MOOC) has a great impact on the e-learning sector. Further, MOOC platforms like Coursera, EdX, and Future Learn have made learning accessible to millions of people for free. Also, availability of such platforms has become a blessing and a burden to people since users cannot find the right courses that suits them due to the availability of similar topic of courses in different platforms. Moreover, MOOCRec Humanities is a curated search platform for these courses. Further, MOOCRec tries to address this problem by considering the learning style of user and matching them with the right courses. Additionally, the courses are mapped using VARK learning model. For the mapping purpose, course video styles and course practical content such as quizzes and reading materials are considered. In addition, users can search individual topics that can be covered in a course.Publication Embargo Analyzing Payment Behaviors And Introducing An Optimal Credit Limit(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Bandara, H.M.M.T.; Samarasinghe, D.P.; Manchanayake, S.M.A.M.Identifying an optimal credit limit plays a vital role in telecommunication industry as the credit limit given to customers is influence on the market, revenue stabilization and customer retention. Most of the time service providers offer a fixed credit limit for customers which may cause customer dissatisfaction and loss of potential revenue. Therefore, it is essential to determine an optimal credit limit that maintains customer satisfaction while stabilizing the company revenue. Clustering algorithms were used to group customers with similar payment and usage behaviors. Then the optimal credit limit derived for each cluster is applicable to all the customers within the cluster. In order to identify the most suitable clustering algorithm, cluster validation statistics namely, Silhouette and Dunn indexes were used in this research. Based on the scores generated from these statistics KMeans algorithm was chosen. Furthermore, the quality of the KMeans clustering was evaluated using Silhouette score and the Elbow method. The optimal number of clusters are identified by those validation statistics. The significance of this approach is that the optimal credit limits generated by these clustering models suit dynamic behaviors of the customer which in turn increases customer satisfaction while contributing to reducing customer churn and potential loss of revenue.