3rd International Conference on Advancements in Computing [ICAC] 2021
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/947
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Publication Embargo Permissioned Blockchain Platform to Enhance Scalability, Security and Performance Issues in Livestock Farms in Sri Lanka(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-11-09) Rathnayka, W.A.C.L.; Jayasena, K.P.N.The blockchain is being applied in the food supply chain, livestock, and farm management to enhance food quality, management activities, and animal health and build trustworthy transactions. The present paper provides an overview of blockchain in livestock farming. This paper identifies the current research topics, their contribution, and the benefits o f applying blockchain in livestock farming. Blockchain applications in the livestock sector are increasing worldwide, and most of them are proposed for security and trust issues. This research study implements a permission-based blockchain platform to enhance the livestock sector’s scalability, security, and performance issues. The designated Platform aims to provide distributed digital data storage with animal disease tracking service and access control security mechanism that cannot be tampered with by an unauthorized person. The performance of the proposed blockchain is evaluated through a series of experiments using a different kinds of metrics.Publication Embargo Crime Analysis, Prediction and Simulation Platform Based on Machine Learning(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12) Herath, I.S.; Dinalankara, R.; Wijenayake, U.As a global social-economical problem, crime has shown complex correlations with spatial-temporal, socio-economical, and environmental factors. Understanding patterns and interactions in the crimes is essential to prepare better to respond to those criminal activities. This study is focused on research and development of crime analysis, prediction and simulation platform that provides descriptive analysis, predictive crime analysis, Reinforcement learning based crime entity simulations and safest route navigation services based on crime data from the city of San Francisco. Ultimately, the proposed crime analysis, prediction and simulation platform provides critical information on root causes and statistical patterns of crime and future crime predictions for the policymakers and security officials to create strategies to minimise the crimes.Publication Embargo Data-driven Business Intelligence Platform for Smart Retail Stores(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 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.; 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.Publication Embargo Mobile Based Solution to Weight Loss Planning for Children (with Obesity) in Sri Lanka(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Rajapakse, R.M.M.P.K.; Mudalige, J.M.A.I.; Perera, L.A.D.Y.S.; Warakagoda, R.N.A.M.S.C.B.; Siriwardana, S.Obesity is a condition where there is excess fat in the body, and it is one of the world's most extreme and dangerous dietary diseases. Genetic factors, lack of physical activity, unhealthy eating patterns, or a combination of these factors are the most common causes of obesity. This is important because it influences every part of a child's life. More, in particular, this disorder leads to poor health and negative social standing with perceptions. Nowadays, children are paying keen interest in technology and related devices. Therefore, in this research, we are planning to give a mobile-based solution with a smart band that is used to monitor the child. In this solution, we are mainly focusing on Sri Lankan children with obesity who are aged between 5-10. In our solution, there are four main sections which are, monitoring child activities, recognizing the activities, and getting relevant data, then based on those data and previous activity completion levels, this solution will suggest activities for losing weight, provide specific diet plans for each child considering the health conditions and predict the probability of having main obesity-Publication Embargo Artificial Intelligence-based Business Strategy for Optimized Advertising(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kannangara, L.; Harsha, S.; Isuru, T.; Wijesiriwardhane, C.; Wijendra, D.R.; Kishara, J.Television commercials are a passive type of advertising technique that does not consider consumer demographics who are viewing the television at a specific time. As a result, the user sees irrelevant advertisements, which tends to reduce user engagement and sales conversions.As Sales ,which is the expected target of any advertisement campaign, a user-based advertising approach can be considered as a solution to mitigate the negative aspects. A user-based advertisement suggesting system for television, which is extensively utilized in every other digital media, is expected to be given as the solution. For the suggestion process, user attributes such as age, gender, peer group, and the mood identified in which the advertising is shown were taken into consideration. This will result in more relevant commercials for consumers, making television advertisements more user-friendly, resulting in greater sales conversion for the advertising agency.Publication Embargo Symptomatic Analysis Prediction of Kidney Related Diseases using Machine Learning(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Lansakara, D.; Gunasekera, T.; Niroshana, C.; Weerasinghe, I.; Bandara, P.; Wijendra, D.Sri Lanka has been witnessing an increase in kidney disease issues for a while. Elderly kidney patients, kidney transplant patients who passed the risk level after the surgery are not treated in the emergency clinic. These patients are handed over to their families to take care of them. In any case, it is impossible to tackle a portion of the issues that emerge regarding the patient at home. It is hoped to enter patient’s data from home every day and to develop a system that can use that entered data to predict whether a patient is in an essential circumstance or not. Additionally, individuals in high-hazard regions cannot know whether they are in danger of creating kidney disappointments or not and individuals in danger of creating kidney sickness because of Diabetes Mellitus. Thus, we desire to emphasize the framework to improve answers for this issue. The research focuses on developing a system that includes early kidney disease prediction models involving machine learning classification algorithms by considering the relevant variables. In predictive analysis, six machine learning methods are used: Support Vector Machine (SVM with kernels), Random Forest (RF), Decision Tree, Logistic Regression, and Multilayer Perceptron. These classification algorithms' performance is evaluated using statistical measures such as sensitivity (recall), precision, accuracy, and F-score. In categorizing, accuracy determines which examples are accurate. The experimental results reveal that Support Vector Machine outperforms other classification algorithms in terms of accuracy.Publication Embargo Standalone Application and Chromium Browser Extension-based System for Online Examination Cheating Detection(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kariyawasam, S.; Lakshan, A.; Liyanage, A.; Gimhana, K.; Piyawardana, V.; Mallawarachchi, Y.Educational organizations and institutes that provide services to the public use e-learning frequently than before. The incapacity to evaluate the knowledge acquired is a flaw in education. Due to the current situation, traditional evaluation and examinations are not possible. In a developing country like Sri Lanka, the conduct of online examinations has not been efficient, resulting in cheating at examinations due to vulnerabilities resulting from organizational policies and the difficulty to track down candidates who are prone to cheating, therefore use of facial features for candidate verification and to monitor the background interactions the use of audio and video is taken into consideration with the aid of two cameras; the system mounted camera and a wearable camera containing a microphone allowing audio detection. In this research, we suggest using the training data set generated from individuals to undertake a training approach to improve the robustness for background interactions through audio and video to detect the level of cheating of candidates.Publication Embargo Dogodo: IoT Based Mobile Application to Provide Essential Health Services to Dogs(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Thilakarathne, L.V.I.S.; Salay, M.S.; Wijethilaka, M.G.R.; Fernando, T.S.C.; Sriyaratna, D.; Rupasinghe, S.Voice of dogs can be heard by people who listen to them. The more you listen, the more you learn about the dogs. This study proposes a platform to identify and observe dogs’ behavior and their activities by using the newest technologies. The proposed system will mainly cover the relevant areas that are supposed to be covered to full fill the pet owners’ expectations by providing necessary services such as internal health, voice recognition, and emotion translations and external issues such as skin diseases, breeding patterns, and breeding outcomes. Our priority is to emphasize necessary services in the mobile application and provide fluid services with fewer interruptions. Primarily research will offer an IoT device and a mobile application that covers the dog’s internal health and external health consecutively. The study revealed current developments andPublication Embargo Optimization of Microservices Security(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kalubowila, D.C.; Athukorala, S.M.; Tharaka, B.A.S.; Samarasekara, H.W.Y.R.; Samaratunge, U.S.S.Microservices is a trending architecture, and due to its demanding features and behaviors, billions of business applications are developed based on it. Due to its remarkable ability to deploy and coordinate containerized microservices, Kubernetes deployments support the service mesh architectures, and that ensures secured inter-service communication. The Istio is the widely used service mesh tool at present. However, service-to-service communication happens in the present Istio architecture, and there is a probability of exchanging unauthorized and over-provisioned requests due to incorrect implementation. Currently, these requests are verified within the upstream microservice. Obtaining a response to an erroneous request may take considerable time latency. This research thereby aims to address a solution to reduce the latency of a response by implementing an external validation model. The proposed external validation model ensures that the required parameters are validated and actions are taken before requests reach the service level. External validation enables applications to save significant time and resources.Publication Embargo Intelligent Violence Video Detection System(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Jayasanka, H.K.B.; Jayasanka, B.M.R.D.; Diyunuge, K.D.C.D.R.; Jayasekara, T.H.D.Y.M.; Lunugalage, D.; Samaratunge, U.S.S.Due to the busy and stressful lifestyle, humans tend to feel frustrated frequently. This harmful emotional behavior results in violations of several rules, regulations and legislation. Violence is one of the serious issues which emerges due to this situation. It also results in uncontrollable human behavior. This behavior can either be verbal arguments or even physical conflicts. A trend of recording and publishing videos related to these kinds of violations in various platforms can be observed widely at present. Therefore, the terms and conditions of these platforms are subjected to frequent changes. Difficulty in identifying and controlling of violent events will result in an increase of such cases. Due to these reasons, the demand for violence detection systems will be significantly increased. Efficient violent detection systems are lacking currently. But, the usage of artificial intelligence in these systems are further limited. Four major components have been used to achieve this goal. They are video-based, embedded audio-based, abused textbased and thumbnail-based violence detection. The machine learning and image processing techniques are used along with these components to improve the clarity of violence detection.Publication Embargo E-Agrigo(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kartheepan, T.; SirigajanK, B.; Subangan, K.; Mohammed Azzam, M.A.; Bandara, P.; Mahaadikara, M.M.D.J.T.H.To feed this population, food production should be increased by at least 70%. Developing nations have a vast potential to increase the amount of food produced by doubling the current production. However, the traditional methods of farming are making agriculture unviable and inefficient. The increasing food production needs to be met by double the current level of farming. The conventional of farming is making industry uncompetitive and inefficient. This paper aims to analyze the various factors that affect the implementation of autonomous machinery in agriculture. The development of autonomous machinery for agriculture has emerged as vital step towards achieving this goal. Now a day’s farmers are planning their cultivation by finding proper weather and geographical condition on their own experience, but they are failing to cultivate profitable crop and unaware of the diseases that will affect their crops, sometimes these diseases may affect their whole crops and let the farmers to sink in zero profit. Despite these issues plays a major role, there are some other problems also have an impact like, lack of irrigation plans and question of how and where to sell their cultivated crops. By considering these major threats we have planned to propose a solution to some of the selected issues. This can be achieved by applying machine learning algorithm, Image processing and IOT systems. By using our platform farmers will get a chance to plan their yield in a profitable way by using our optimized weather and geographical data.Publication Embargo Dynamic User Interface Personalization Based on Deep Reinforcement Learning(2021-12-09) Silva, K. G. G. H.; Abeyasekare, W. A. P. S.; Dasanayake, D.M. H. E.; Nandisena, T. B.; Kasthurirathna, D.; Kugathasan, A.Personalization is one of the most sought out and popular methods for brand recognition and consumer attraction. The usage of deep reinforcement learning due to its’ ability to learn actions the way humans learn from experience, if utilized and evaluated properly it can result in a revolutionary effect on personalization. The methodology proposed in this research utilizes deep reinforcement learning where an artificial agent may be trained by interacting with its environment. Utilizing the experience gathered, the agent is able optimize in the form of rewards. The approach explained, can be utilized across applications which can be personalized. Several scenarios ranging from changing the layout of webpages, to rearranging icons on mobile home screens are discussed. The main objective is to develop an API for the web developers and smartphone manufacturers to utilize so that depending on the application personalization can be achieved by enhancing saliency, minimizing selection time, increasing engagement, or an arrangement of these. The technique can manage a variety of adaptations, such as how graphical elements are shown and how they behave. An experiment was conducted which showcased improved user experience considering the position change of thePublication Embargo SmartCoach: Comprehensive Tutor Recommender and Student Attentiveness Measuring Platform(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Samarasekara, H. D. K.; Hansaka, H. M. P.; Rajapaksha, S. D. D.; Tharaka, W. A. D. G.; Manathunga, K.; Sriyarathna, D.C.With the pandemic, coaching or tutoring classes became to halt as the underlying system wasn’t facilitating to adapt to emergency teaching mechanisms due to sparse of relevant technologies and tutor unawareness. SmartCoach is an integrated platform that allows students to find suitable tutors based on recommendations and other parameters like proximity, previous track record etc. using sentiment analysis and natural language processing. For tutors, SmartCoach allows publishing learning materials, automatic quiz creation, tracking attendance and, attentiveness during classes using OpenCV library. Moreover tutors get a dashboard featuring critical aspects about their classes and, personal income. This research is aimed to introduce a comprehensive distance learning platform with novel technological approaches that connect both potential students and tutors to a common platform.Publication Embargo AI Based Monitoring System for Social Engineering(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Yapa, K.; Udara, S.W.I.; Wijayawardane, U.P.B.; Kularatne, K.N.P.; Navaratne, N.M.P.P.; Dharmaphriya, W.G.V.USocial media is one of the most predominantly used online platforms by individuals across the world. However, very few of these social media users are educated about the adverse effects of obliviously using social media. Therefore, this research project, is to develop an advisory system for the benefit of the general public who are victimized by the adverse impacts of their ignorant and oblivious behavior on social media. The system was implemented using a decision tree model with the use of customized datasets; and for the proceeding operational implementations, Python programming language, Pandas, Natural Language Processing and TensorFlow were used. This advisory system can monitor user behaviors and generate customized awareness reports for the users based on category and level of their behaviors on social media. Furthermore, the system is also capable of generating graph reports of the use behavior fluctuations for the reference of the user. With the help of these customized awareness reports and the graph reports, the users can identify their potential vulnerabilities and improve their social media habits.Publication Embargo Performance Evaluation for Relay Selection on Device-to-Device (D2D) Communications in Rayleigh Fading(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Woo, W.H.; Annur, R.; Ponnusamy, V.Relay-aided device-to-device (D2D) is an alternative method to support short-distance direct communication in the facts of poor channel links and limited coverage. In a wireless communication system, failed communication can be caused by many factors, such as a lack of energy to maintain the transmission or the inability to hear the signals due to weak RSS. This paper presents Received Signal Strength (RSS) and battery awareness as the parameters of relay selection to select one or more optimal relays. In order to study the impact of radio propagation on the proposed scheme, the D2D network is implemented in the Rayleigh fading with obstacles environment. Performance is determined by packet drop, throughput, and end-to-end delay. Overall, the proposed scheme performs better than the existing scheme. From the evaluations, the packet drop in the proposed scheme is lesser than the existing scheme, reducing the throughput by 46%. The end-to-end delay in the proposed scheme is lesser than the existing scheme by 0.003s.Publication Embargo EduHelp – An Online Tutoring Application(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Fernandopulle, S.R.; Warnasooriya, W.M.C.D.B.; Jayasinghe, J.M.H.N.; Theeraj, S.M.D.; Samarakoon, U.; Kumari, S.E-learning via electronic mail, the Internet, the Worldwide Web (WWW), and multimedia has emerged as a result of the convergence of digital technologies and growing interest in the computerized delivery of higher education. The rapid emergence of Covid-19, a lethal disease caused by the Corona Virus, shocked the entire world. It was labeled a pandemic by the World Health Organization. This has posed a challenge to the global education system, forcing instructors to switch to an online form of instruction overnight. Many academic institutions that had previously been hesitant to adapt their traditional pedagogical method now have no choice but to fully embrace online teaching-learning. Because the platform is new to students and teachers, it appears that they are having some difficulties conducting their classes. Hence in this paper, we proposed an E-learning Application called EduHelp to design and build a tutoring platform that includes payment validation for each student, lesson summaries with a video summary note, and more. Upload relevant files and papers by automatically identifying and directing them, as well as creating automated questions and monitoring student attention.Publication Embargo Sensor-Based Emotion Tracking System for Computer Games(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Wickramasinghe, W.R.M.G.K.; Devduni, R.M.B.; Dasanayaka, D.T.C.B.; Mohomed, M.N.N.; Kumari, S.; Dassanayake, T.The game development industry is among the leading industries globally, and in 2020, gaming emerged as a popular entertainment activity upon the COVID-19 outbreak. Thus, competition among gaming companies is high. Hence, they try to adopt new technologies often. Gaming brings multiple feelings for the gamer. At times, the conditions may get even worse from the game’s end where the gamer may end up venting out his rage and annoyance. Hence, there is a massive possibility for the gamer to switch to another game which may result in the company to lose its customers. In that scenario, this system can monitor the emotional states of the gamer while playing and manipulate the gaming environment, sound environment, enemy behavior, and gamer mechanism according to the emotional state of the gamer. The sensor-based emotion tracking system identifies the gamer's emotional state using facial emotions, detected through a webcam and heart rate, detected through sensors. The development was carried out through the machine learning models, open cv, Arduino techniques, and reactive programming. The emotional state and facial emotions that will be tracked will count to an accuracy of above 95%. Through that, the target will be to make the gamer satisfied by building appreciation for the services given and by improving the gamer's gaming experience and retain the gamer with the game provider.Publication Embargo Smart Monitoring and Disease Detection for Robotic Harvesting of Tomatoes(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Pasindu, I.; Viraj, S.; Dilshan, R.; Kalhara, A.; Senaweera, O.; de Silva, R.; Jayawardena, C.Tomato is a one of the most popular produced and extensively consumed vegetables in the world. Typical agricultural systems make extensive use of human labor which is more costly and less effective. This research explores the minimization of human labor through automation. The diseases infected by tomato plants are hard to detect. Identifying these diseases in advance would save the cultivation of the disease from spreading, thereby saving the crop.It is also a difficult task to recognize the ripe harvest and experienced labor is required. The efficiency of the harvesting method will be increased by automating the identification process of ripened fruits. Manually picking tomatoes can cause some harm to the fruits during plucking due to inconsistencies in human labor. Such damage will be reduced through a better implemented robotic scheme. This paper presents the development of autonomous system for tomato harvesting and disease detection.Publication Embargo Enhance the Safety Measurements in Railways with the Aid of IoT and Image Processing(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Vedasingha, K. S.; Perera, K. K. M. T.; Hathurusinghe, K. I.; Akalanka, H. W. I.; Amarasena, N.; Dissanayake, N.R.Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways, caused damages to not only precious lives but also to the economy. The goal of this research is to minimize the railway accidents by developing “Railway Process Automation System” while ensuring human safety with use of Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. As usual, if the system fails to close the rail gate due to any failure, the proposed system can identify the current location and close the rail gate through decision making system by using past data. The proposed system introduces further two features which named as Railway track crack detection and motion detection which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype and tested with real-world scenarios to gain the above 90% of accuracy.Publication Embargo LUMOZ – A Real Time Augmented Reality Based Tool for Media Production(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Wanigasekara, M.P.W.P. A.; Nivarthana, A.N.; Thilan, R.M.B.A.; Gankanda, G.M.J.U.; Thilakarthna, T.; Reyal, S.Globalization has created vast competition among media content productions. Gaining an audience for these products depends on the quality, correctness, timely content and should be produced according to the target audience’s comprehension level. The aforementioned factors can be achieved by using new technology in the process of content production. This trend also affects the local news productions. At present, news delivery and other digital media creations are transforming from traditional delivery methods into more advanced technology-based delivery. For this transformation, Augmented Reality and 3D technologies play significant roles which help improving content’s attractiveness and correctness. And using this new technology can create a new fan base and increase the popularity of the content. The use of these technologies in an industrial base or startup base still provides many challenges. LUMOZ provides a solution for these challenges. This tool provides easier access to point tracking,3D object placement, gesture controls, 3D data visualization, and 3D model library. Simply LUMOZ can be considered as a budget-friendly and time-efficient tool that can handle 3D objects in real-time in a live streaming environment.
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