Research Publications Authored by SLIIT Staff
Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4195
This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo “SmartGo” – Intelligent Traffic Controlling System with Violators Detection(IEEE, 2022-12-09) Dissanayake, D.M.B.W.D.K.; Aluvihare, W.B.W.M.R.U.P.U.; Weerasooriya, K.T.N; Rajapaksha, K.D; Gunarathne, G.W.D. A; Pemadasa, M.G.N. MRoad traffic is mostly regulated by Traffic Light Control Systems (TLCS) in Sri Lanka. Conventional traffic signals have many problems, including unproductive time management at road intersections. Drivers and pedestrians would prefer to use the TLCS without any difficulties. The study aims to implement a system on a real-time basis using video monitoring and image processing technology. The system will facilitate vehicles to pass the traffic lights within a minimum waiting time and utilize time according to the number of disabled persons. Emergency vehicles will be released soon by detection using real-time data processing. This system includes the highest vehicle count detection accuracy level, nearly 92%. and the red-light violators’ detection system with an accuracy of 88.6%. SmartGo also detects emergency vehicles and smooths the way of passing through the traffic lights, including a YOLOv5 model with an accuracy of 82.3%. Subsequently, a fine-tuning YOLOv5 is then used to detect vehicles and pedestrians. According to experimental data, the suggested method provides a detection accuracy of 90%. SmartGo is a comprehensive system different from the existing traffic light control system in Sri Lanka which provides flexible and efficient service to both drivers and pedestrians.Publication Embargo Intelligent Crowd-Sourced 5G Heat-map with Event-driven Architecture(IEEE, 2021-12-06) Bandara, L; Rathnasinghe, H; Kavinda, E; De. Seram, C; Mahaadikara, M.D.J.T. H5G networks are expected to revolutionize the mobile network and IoT industries. Increased data transfer speeds, reduced latency, and extended bandwidths enable the true power of 5G networks. To support increased bandwidths cellular industry looked to high-frequency bands with high data rates in the spectrum above 24 GHz which are typically called “millimeter waves”. The introduction of millimeter waves reduces the coverage radius drastically due to high penetration losses and the blocking nature of this wave spectrum. The reduced coverage radius causes higher infrastructure costs for the network providers. This research will focus on a crowdsourcing mechanism where network data is collected through a mobile application and use this data to generate a real-time network coverage map. In addition, collected data will be used to predict future network quality demands and locations for cell towers with the help of machine learning technologies. The outcome of this research will be beneficial to network providers to reduce infrastructure costs by optimally laying infrastructures.Publication Embargo Intelligent Hybrid Chatbot Solution for Archaeological Sites Tracking(IEEE, 2021-02-26) Godewithana, N; Kirindage, GNot only in the country like Sri Lanka, but also most of the countries have numerous historically valued places and monuments that provide great survival and civilization history. While searching information about those places, there exists a lack of information and trusted information sources. Even though some information is available, it does not include the convenient and efficient ways to retrieve the information. The proposed system contributes a solution to the aforementioned problem with Artificial Intelligence [AI] & Deep Learning [DL] concepts. The proposed chatbot solution helps to enhance the user experience while retrieving the available information about the archeological places from the system. It can automate the searching task by enabling a methodology for chatting with the user via a conversational interface. The proposed voice detection module, natural language processing model and the dialog management model leverages a higher accuracy rate and it will showcase the power of search assistants. Furthermore, it shows how it can be an alternative to the usage of the application and enhance the user experience without any hesitation.Publication Embargo Arogya-An Intelligent Ayurvedic Herb Management Platform(IEEE, 2020-10-15) Pathiranage, N; Nilfa, N; Nithmali, M; Kumari, N; Weerasinghe, L; Weerathunga, IAyurvedic means a science of life and well-being with its unique approaches to social and spiritual life. Especially in Sri Lanka we have our own set of rare Ayurvedic herbs which have been utilized by generations as medicinal treatments for a variety of diseases. Absence of specialists in this area makes proper identification as well as classification of valuable herbal plants a tedious task, which is essential for better treatment. Hence, a fully automated system for herb detection and classification, information visualization regarding them is highly desirable. There are existing applications which can identify plants with low prediction accuracies, as well as to give information regarding them. However, these applications are based on foreign plant data sets that do not include valuable herbs and shrubs with medicinal qualities. Hence this research proposes an application unique to medicinal plants, which can perform all these functionalities in both online and offline approach. Here, a new Ayurvedic plant dataset prepared from scratch, and preliminary results for classification of 5 types of herbs, compared with several deep Convolutional Neural Network (CNN) models based on transfer learning are presented. Experimental results indicate Marker-based Watershed algorithm as the best object detection algorithm in a complex background, VGG-16 as the best deep CNN classification model which reached a promising testing accuracy of 99.53%, and Seq2Seq LSTM model as the best deep learning model with optimum accuracy in abstractive information summarization.Publication Embargo Intelligent Timetable Scheduler: A Comparison of Genetic, Graph Coloring, Heuristic and Iterated Local Search Algorithms(IEEE, 2019-12-05) Ekanayake, T. W; Subasinghe, P; Ragel, S; Gamage, A; Attanayaka, SA Timetable scheduling is a monotonous task and a problem in an educational institute. This is because many rules and constraints are involved, which can be categorized as hard and soft constraints. Mainly, a university must produce two types of timetables, which are examination, and semester timetables. This paper has reviewed the Exam Timetabling problem with Genetic and Graph Coloring algorithms and the Semester Timetabling problem with Heuristic and Iterated Local Search algorithms. Our aim here is to develop a possible and correct solution for each timetabling problem using the above-mentioned four different approaches.Publication Embargo Fitness Mate: Intelligent workout assistant using motion detection(IEEE, 2016-12-16) Madanayake, P. S; Wickramasinghe, W. A. D. K; Liyanarachchi, H. P; Herath, H. M. D. M; Karunasena, A; Perera, T. DEngaging in physical exercises such as weight training and physiotherapy stretching exercises at home requires proper execution and awareness of the exercises. One of the main problems in engaging exercises at home is that there is no proper guidance and feedback provided to align the exercises to the correct movements due to the absence of a physical trainer. This paper discusses how a system, namely Fitness Mate is designed and implemented to enable users to engage in physical exercises without the presence of a physical trainer. Visual C#, Matlab programming language, and Unity game engine are the technologies used to develop the system. The main goal is to provide a home-based environment where people can engage in physical exercise without the presence of a physical trainer and to avoid adverse physical injuries.Publication Embargo Intelligent Enterprise Security Enhanced COPE (Intelligent ESECOPE)(IEEE, 2018-12-21) Samarathunge, R. D. S. P; Perera, W. P. P; Ranasinghe, R. A. N. I; Kahaduwa, K. K. U. S; Senarathne, A. N; Abeywardena, K. YMobile devices have come a long way of supporting humans' day to day tasks. Companies from all over the world tend to implement Information Technology (IT) consumerization in their premises in order to attain high productivity as well as employee satisfaction. Bring Your Own Device (BYOD), Corporate Owned Personally Enabled (COPE) and Choose Your Own Device (CYOD) assist to implement IT consumerization according to the organization's requirements. This research looks at the security issues in Corporate Owned Personally Enabled concept. The purpose of this research is to identify major security concerns an organization could have and propose sophisticated yet effective countermeasures. Research components are categorized into four main parts which are web data loss prevention, email data loss prevention, malware identification and malware classification. The information leak can be occurred either deliberately or unintentionally by an individual or a group of individuals in any organization which affects financial status, customer or public security and the reputation. ESECOPE is built with a revived technique that is based on keyword-based search detection to reach the goal. Proposed Implementations consist range of features in data loss prevention such as deep content analysis, secure wiping of sensitive data, encryption of sensitive data. The combination of both machine learning techniques, signature, and behavioral based analysis will be used to craft a tool which is integrated into the system that outputs less false negative results. Apart from identification and classification generation of IT administrator alerts, Quarantine identified malware can be listed as additional features provided by the tool. The platform which supports deploying multiple vulnerability scanning tools together makes the end product unique from other existing COPE solutions provides a vast amount of advantages including mobile device scanning individually or at once, report generation and also it reduces the workload of IT administrator.Publication Embargo Intelligent Flood Management System(IEEE, 2019-12-05) Fernando, M. J. D; Pathirana, D. A. K. K; Jayasooriya, W. J. K. T. D; Rathnaweera, S. A. H; Rupasinghe, LFlooding is one of the major disasters in Sri Lanka. In Sri Lanka, there are no effective pre preparedness procedures follow in a flooding situation. The setting of pre and post-disaster activities like mitigation, preparedness, response, and recovery have very important roles in reducing future hazard risk in disaster-prone areas. Lack of communication and coordination during a disaster situation has led inefficiencies in mitigating adverse, in that situation, messages requesting for any assistance are sent to a central cloud system where the system generates response automatically and communicate and coordinate with the relevant parties. The genetic programming methods have used to plan relief supply distribution and safety location allocation for the flood-affected people in Sri Lanka. The research provides a guide for the administration of flood management for decision making on flood disaster management, preparedness and mitigation damages and deaths, recovery, and development in post-disaster situations in Sri Lanka.Publication Embargo TrendiTex: An Intelligent Fashion Designer(IEEE, 2019-12-05) Wickramarathne, P; De Silva, M; Weerasinghe, C; Nanayakkara, H; Abeygunawardhana, P. K. W; Silva, SIn a highly changing technical era, Intelligent Fashion Designing systems play a key role to bridge the gap between fashion designers and the customers. Most of the people specially females, are fond of fashion. Currently, fashion has become a way of defining a person's preferences and personality. Analyzing through a large number of fashion trends and selecting a one among them will be a highly time-consuming task. Even though most of the people are keen on fashion, with their busy schedules, spending time on selecting a cloth for an occasion among numerous numbers of designs available is a hard task. Therefore, it would be exhausting to select a proper design for an occasion for them. Prevailing the difficulty in finding the clothes up to the user's expectation, we propose a user-friendly fashion designing mobile application and a web application called "TrendiTex". Extracting user preference details, user's body shape predicting and recommending trending fashion designs according to their shape, generating the unique 2D new fashionable design for a specific event and the augmented fit-on facility are implemented in TrendiTex. This system represents an efficient approach to design new unique products according to user's preferences and gives augmented fit-on facility.