Research Publications Authored by SLIIT Staff
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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 Open Access Improved Path Planning for Multi-Robot Systems Using a Hybrid Probabilistic Roadmap and Genetic Algorithm Approach(Department of Agribusiness, Universitas Muhammadiyah Yogyakarta, 2025-03-24) Jathunga, T; Rajapaksha, SThis study focuses on the development and application of an improved Probabilistic Roadmap (PRM) algorithm enhanced with Genetic Algorithms (GA) for multi-robot path planning in dynamic environments. Traditional PRM-based methods often struggle with optimizing path length and minimizing turns, particularly in complex, multi-agent scenarios. To address these limitations, we propose a hybrid PRM-GA approach that incorporates genetic operators to evolve optimal paths for multiple robots in real-time.The research contribution is an enhanced PRM-GA framework that improves efficiency in multi-robot navigation by integrating evolutionary techniques for dynamic obstacle handling and optimized path generation.The research methodology involves testing the algorithm in various environments, including varying robot numbers and environmental complexities, to evaluate its scalability and effectiveness. Our results demonstrate that the PRM-GA algorithm successfully reduces both path lengths and turn counts compared to standard PRM-based methods, ensuring collision-free and smooth paths. The algorithm showed robust performance across different scenarios, effectively handling dynamic obstacles and multi-agent coordination. However, in highly dynamic environments with rapidly changing obstacles and constraints, the algorithm may occasionally produce paths with turn counts and distances similar to or slightly higher than those of simpler approaches due to the need for frequent re-optimization. Future research can explore incorporating additional factors such as energy consumption and time optimization, alongside distance and turns, to further enhance the algorithm's efficiency in real-world applications. Overall, the PRM-GA approach advances the state of the art by offering a more adaptable and scalable solution for multi-robot path planning, with applications in logistics, industrial automation, and autonomous robotics.Publication Embargo Cloud-based Salesman-Bot for Ontology-based Negotiation(IEEE, 2023-04-06) Fernando, A; Rahubedda, T; Jayasinghe, B; Mallikahewa, S; Hettiarachchi, O; Rajapaksha, SWe have proposed a cloud-based ChatBot (Salesman-Bot) approach to handling multiple negotiation scenarios in a supermarket environment. The web application is a simple interface that can be implemented on a single standalone device or interacted with through a mobile phone. The Salesman-Bot responds both via text and speech. By introducing a Salesman-Bot, efficient negotiation, with quick preferences and suggestions can be provided. A new architecture proposed to operate the Salesman-Bot together with Google APIs and libraries such as Natural Language AI, Vision AI, Speech to Text API, Text to Speech API and Machine Learning using TensorFlow. The application also uses the Google Cloud Platform with related services such as Google App Engine. The goal is to make ChatBots more efficient in negotiating in different business scenarios. This paper presents the work carried out with ontology and machine learning in a cloud-based environment to handle multiple negotiation scenarios based on a negotiation hierarchy. It also proposes the opportunities and drawbacks of such a system.Publication Embargo A Smart Waste Disposal System: To Encourage Proper Waste Disposal(IEEE, 2022-12-09) Alwis, D; Munasinghe, P; Rajapaksha, S; Ranawaka, B; Krishara, J; Tissera, WWaste disposal is one of the most important industries in the world. If not maintained properly it would lead to the destruction of the environment. Improper waste disposal is becoming a critical issue in Sri Lanka and the lack of waste segregation, inadequate waste collection methods, the lack of support for waste management from the public are among the root causes of the problem. As a solution we propose an IoT-based solid waste management system that allows garbage bin monitoring, routing of garbage collector trucks, a prediction model and a point rewarding system. As the end result of this research the following prototypes was built; a prototype model of a smart bin with the capabilities of opening and closing by itself and detecting the waste level of the bin, a prototype mobile application for garbage collectors which delivers analysed data on truck position and ensures timeliness, a prototype mobile application for the public which receives the weight and type of solid waste discarded as an input and calculate reward points to encourage the public in proper waste disposal, a prototype web application which delivers statistical data for detailed reports and a prediction model which predicts the amount of waste to be collected in the coming month using machine learning. This is a low-cost IoT-based solution that uses existing resources to handle the massive amounts of garbage collected each day.Publication Embargo SMART DIARY: Autonomous System for Daily Diary Creation and Prioritization of Daily Activities for Improved Well-Being Using Neural Networks and Machine Learning(IEEE, 2022-12-09) Abraar, S.F.M.; Thuduhenage, D.T.; Balasubramaniyam, V.P.; Mohanraj, S.R.; Wimalaratne, G; Rajapaksha, SIn the present world, the IT (Information Technology) industry is so advanced that it has opened many opportunities to communities with numerous roles. Even though the industry is growing day by day and providing more opportunities, it has had serious effects on human well-being. If a person fails to control the demands of work or study, such as tasks with higher complexity, an unmanageable workload, pressure, enduring conflicts within the team, and other physical and emotional demands, it could lead that person to exhaustion, anxiety, and stress. Such factors can affect the health of a person in an extremely negative way. The proposed topic “Smart Diary: Auto generation of diary and Prioritization of Daily Activities for Improved Well-Being” is a solution for people with uncontrolled job demands and busy work schedules. This helps to keep track of day-to-day life activities and review them to make better plans for the future. It also helps the user prioritize their daily tasks and provides suggestions for people who are stressed and showcasing negative emotions based on text analysis.Publication Embargo Autonomous Hydroponic Environment with Live Remote Consulting System for Strawberry Farming(IEEE, 2022-12-09) Samaranayake, S.L; Krishmal, S; Cooray, P.L.R.K; Senatilaka, T; Rajapaksha, S; Nuwanthika, W.SStrawberries are a very popular fruit and are widely consumed all over the world. Due to its nutritional value, its consumption has increased tremendously in recent times. Strawberry, which has such high health and economic value, is grown in only one area in Sri Lanka. This is since the climate in those areas is favorable for strawberries. Using the Internet of Things, image processing, and machine learning, this research proposed a design for a closed environment with automatic monitoring and controlling of environmental factors and nutrition required for strawberry cultivation with the capability of remote live monitoring and analysis of each plant. Also, the proposed system captures the images of each strawberry plant using a camera navigation system and analyses those images using a machine learning algorithm to identify the growing stage. This decision making process was verified using strawberry pictures acquired from a strawberry farm. In addition, current capturing images can use in the next growth cycle to increase accuracy. The proposed system can be easily expanded by increasing the height of the tower and refrigeration power. Through this, strawberry cultivation can be expanded to all parts of Sri Lanka by overcoming climatic and geographical limitations.Publication Embargo Computer Vision Based Navigation Robot(IEEE, 2022-12-26) Haputhanthri, M; Himasha, C; Balasooriya, H; Herath, M; Rajapaksha, S; Harshanath, S.M.B.The majority of industrial environments and homewares need help when exploring unknown locations owing to a lack of understanding about the building structure and the various impediments that may be faced while transporting products from one spot to another. This is because there is a lack of knowledge about the building structure and the potential obstacles that may be encountered. This paper provides “Computer Vision-Based Navigation Robot” as a strategy for indoor navigation with optimal accessibility, usability, and security, decreasing issues that the user may encounter when traveling through indoor and outdoor areas with real-time monitoring of the most up to date IoT technology. The article is titled “Indoor Navigation with Optimal Accessibility, Usability, and Security.” This article proposes “Computer Vision-Based Navigation Robot” as a solution for interior navigation that provides optimum accessibility, usability, and security. This is done in order to tackle the issue that was presented before. Since the readers of this post include people who work in industry as well as physically challenged people who live alone, CVBN Robot takes object-based inputs from its surroundings. This is because the audience for this essay includes both groups of people. This study also covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot. This connection enables real-time position and status updates for the robot as it navigates a known but unknown interior environment. In addition, this study covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot.Publication Embargo Elderly Care Home Robot using Emotion Recognition, Voice Recognition and Medicine Scheduling(IEEE, 2022-12-26) Kularatne, B.M.U.S.; Basnayake, B.M.J.N.; Sathmini, P.D.L.A.M.; Sewwandi, G.V.U; Rajapaksha, S; De Silva, DThe robotic concept is used for several tasks to easier human day-to-day tasks. There are various recreational studies have been done on the elderly people’s care system. In this study, the system can identify the elderly people’s emotional status using thermal image processing that eliminates the halo effect issue in thermal images using a single discriminator Cycle-GAN model, serving medicine to elderly people by moving towards the elderly person while avoiding obstacles using point to point algorithm and obstacle avoidance and identify the semantic analysis by using web ontology based language. The integrated system is evaluated using the Gazebo simulator because the cost is lower than implementing the features in a real robot.Publication Embargo Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions(IEEE, 2022-07-18) De Silva, G. W. M. H. P.; Rajapaksha, S; Jayawardena, CThis system is developed to identify and complete the human’s instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks.Publication Embargo Intelligent System to Verify the Effectiveness of Proposed Teacher Transfers Incorporating Human Factors(IEEE, 2022-02-23) Karunanayake, V; Wanniarachchi, J. C; Karunanayake, p; Rajapaksha, SA data center architecture can be determined as the basic structure of a cloud computing data center. However, the expected outcome cannot be obtained even though the tools, technologies, and elements are advanced. It is crucial to select the right architecture as architecture used, which directly affects the operational cost and power consumption of the data center. The SDN, Software Defined Networking, is a novel technology of cloud computing. This SDN is used to separate the control panel and forwarding plane as well, as it enables programmable network components. Therefore, the components of the SDN can easily control and managed. This research aimed to select an SDN-based architecture for a data center. Here, there are two parameters of average throughput and average packet delay on the three existing architectures that are tested using simulation. Then the results are compared with each other. In this research, the accuracy correlations among average packet delay and average throughput are investigated. The Obtained results show that Fat-Tree architecture is the best one among VL2 and hybrid architecture consists with flat tree and VL2 technology in terms of their performances.Publication Embargo Techniques of Enhancing Synchronization Efficiency of Distributed Real Time Operating Systems(IEEE, 2022-02-23) Rajapaksha, S; Alagalla, HDistributed Operating Systems is one of the most modernizing concepts of the world. When it comes to Distributed Networks and Operating Systems, Real-Time Operating systems are highly crucial for the developers to achieve desired Tasks. To make the concept into the working functionality, Synchronization is playing a huge role. Synchronization has experimented with many techniques by researchers. Still, there is a lack of analysis to find the most optimized and most effective technique to achieve the goal of enhancing the accuracy and efficiency of Real-Time Operating Systems (RTOS) by synchronization context. Apart from that research is analytically produces the explanation about existing synchronization platforms in the computing world including backup Synchronization, On-Chip Memory Handling, Location-Based Network Systems Configuration, and Hardware Oriented Synchronization. Especially this research focuses on the problems and challenges of the existing RTOS and Distributed RTOS (DRTOS) Systems. Further, this paper will elaborate on the best-suited solutions and techniques to follow during the development of Distributed Node Network with Multi-Core Processors. It will propose multiple techniques to enhance the efficiency by using various algorithms comprising lock-based, lock-free, semaphore based, Mutex based, and Hardware related high accuracy criteria. Also, this will be highly beneficial for the people who are interested in Internet of Thing-based Distributed Networks to build more supportive and high-performance processing systems using desired featured objectives.