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 Embargo Energy and Operations Optimization for Effective Greenhouse Management(IEEE, 2022-12-09) Prihan Nimsara, K. I.; Bodaragama, J.; Roshan Maduwantha, K. A.; Fernando, S. D.IoT technology-based process automation that can be applied to a greenhouse leads to making condition management and status monitoring more robust while leading to saving energy and resources. The proposed system which is based on IoT technology and MQTT protocol can set optimal growth conditions for plant and seed growth within the greenhouse. The sensor-based inputs are to be transformed into the processed values based on the defined logic and the standard benchmarks gathered from the local agricultural authorities. The key areas of condition monitoring to be done via temperature, humidity, soil moisture, and lighting can ultimately yield an increased harvest having supported both the plant and seeds-based implementations for multiple types of plants. One of the most important factors to consider is that the farmers can have energy savings through the proposed solution by controlling the actuators in an optimal manner and reducing manual intervention by a considerable amount. The excess usage of electricity by lights and cooling fan usage in the greenhouse can be controlled with real-time data tracking and better analytics. The use of water can be properly maintained for the plants by putting only the required amount will make the soil wet and spraying the required amount to air will make better humidity control. Thus, the real-time condition-based controlling of the actuators leads to making the greenhouse operations more optimal and better utilization of resources and energy which ultimately results in financial benefits for the greenhouse owner. Based on the evaluated power consumption of the greenhouse power usage before and after the system was installed, the newly introduced system can save energy by having optimal control of actuators by performing algorithmic calculations to meet only the required level of weather conditions. This is to be proven experimentally by implementing the proposed system for a defined period of time under the monitoring of energy usage.Publication Embargo Carbon Emission Optimization Using Linear Programming(IEEE, 2022-12-09) Magenthirarajah, V; Gamage, A; Chandrasiri, SIn this fast-growing modernization, excess carbon emission plays a crucial role in climate change. Targeting and experimenting with sustainable ways of Carbon neutrality and management is the pathway toward a greener society. Data show that factories and industries take a high market stake in carbon emission and management. In actions, Governments defined a limit for carbon emissions to each organization which is called carbon credit. Every organization must focus on reducing carbon emissions. This is a critical task for each organization, In some cases, it is still not possible to explore other sustainable options. An innovative solution proposed for the above scenario is to implement a real-time platform that can provide insights into the most up-to-date emission statistics of the organization. This paper provides advanced analytics and precise proactive planning and actions in the simplest form and a discussion on future elaborations and insights about conclusions. By finding the minimum optimal emission values of each emission source, organizations can maintain carbon emissions without exceeding their carbon credit. Also, how industries and factories can create a smart carbon optimization system that can create an even greener society.Publication Embargo “ServPort”: Process Reengineering in Optimization of The Process in Vehicle Service Station(IEEE, 2022-06-27) Withana, R. D. K; Fernando, W. S. C. S; Nethsara, V. R; Jayasinghe, N. B. A. C.T; Lokuliyana, S. L; Kuruppu, T. AThe usage of vehicles is increasing across the world. Thus, vehicle maintenance has become a key factor when considering vehicles' continuous performance, which leads to the increasing need for vehicle service providers. However, there are some challenges faced by vehicle service providers when providing a high-quality service within a reasonable price range for their customers. A process optimization solution for vehicle service centers named as ‘ServPort’ is proposed through this study to provide a solution to the challenges experienced by vehicle service providers and to support them in providing a quality service at a fair price to their clients. According to the findings, a process optimization solution was not yet introduced for the vehicle service sector in Sri Lanka. Therefore, this paper addresses the selected machine learning models and the approaches taken to optimize the process in a vehicle service station by predicting key fields in a vehicle service station. Under this, customer retention and its impact on the vehicle service center's profitability were predicted using linear regression algorithm, which achieved 99.29% accuracy rate. In comparison, other selected machine learning models achieved lower accuracy rates. When predicting employee efficiency, decision tree model achieved 90% accuracy rate, whereas linear regression algorithm achieved only 50% accuracy rate. To predict the next vehicle service date, logistic regression algorithm, which performed with an accuracy rate of 98% was used.Publication Open Access Experimental study on an efficient dengue disease management system: Planning and optimizing hospital staff allocation(The Science and Information (SAI) Organization, 2018-01) Jayasuriya, M. M. C; Galappaththi, G. K. K. T; Sampath, M. A. D; Nipunika, H. N; Rankothge, WDengue has become a serious health hazard in Sri Lanka with the increasing cases and loss of human lives. It is necessary to develop an efficient dengue disease management system which could predict the dengue outbreaks, plan the countermeasures accordingly and allocate resources for the countermeasures. We have proposed a platform for Dengue disease management with following modules: (1) a prediction module to predict the dengue outbreak and (2) an optimization algorithm module to optimize hospital staff according to the predictions made on future dengue patient counts. This paper focuses on the optimization algorithm module. It has been developed based on two approaches: (1) Genetic Algorithm (GA) and (2) Iterated Local Search (ILS). We are presenting the performances of our optimization algorithm module with a comparison of the two approaches. Our results show that the GA approach is much more efficient and faster than the ILS approach.Publication Embargo Towards a Smart City: Application of Optimization for a Smart Transportation Management System(IEEE, 2018-12) Thiranjaya, C; Rushan, R; Udayanga, P; Kaushalya, U; Rankothge, WIntelligent traffic planning, the efficiency of public transport and the improved connectivity of all road users in a city, comprise the mobility characteristics of a smart city. In the era of smart cities, efficient and well managed public transportation systems play a crucial role. The planning and allocation of public transportation systems, especially the public bus scheduling is one of the major resource allocation problems where the optimal resource allocation increases the passenger's as well as bus owner's satisfaction. In this research, we have proposed a platform for public transportation management, especially for optimal planning and scheduling of buses. We have used two approaches for our algorithms: Iterated Local Search (ILS) and Genetic Algorithm (GA). In this paper, we are presenting our optimization algorithms and their performances. Our results show that, using our algorithms, we can decide the optimal allocations of buses and plan the bus schedules dynamically in the order of seconds.Publication Embargo 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, DSmartphone 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.Publication Embargo Sustainable tourism: Application of optimization algorithms to schedule tour plans(IEEE, 2019-01-31) Perera, D; Rathnayaka, C; Siriweera, L; Dilan, S; Rankothge, WOne of the challenging problems in the tourism industry is to maintain the environmental sustainability of the tourists attracted locations while giving a better user experience for the tourists. The proposed platform for sustainable tourism management system consist with following modules: A prediction module to predict an approximate value on tourist arrival for each location, an optimization algorithm module to decide the number of tourists that can be accommodated in each location considering the environmental sustainability, and an optimal path generating module to show the best route to each location. The optimization algorithm module is developed to decide the number of tourists for each location based on two approaches: Genetic Algorithms and Iterated Local Search. Next the optimal path generating module is developed based on traveling salesman problem.In this paper, the performances of the optimization algorithm module and the optimal path generating module is presented. Results show that, using the suggestions given by the algorithms help the tourist to enjoy a better experience in travelling while ensuring the sustainability in the tourism industry.Publication Embargo Optimization of Customer-Friendly Manual Load Shedding System(IEEE, 2019-12-05) Fernando, W. D. I; Rankothge, W; Perera, A. D. S; Dissanayake, S. J; De Silva, W. D. STo maintain the supply and demand of electricity power, load-Shedding is one of the methods practiced by the energy suppliers to hold the power system balanced, when an energy deficit problem arises. Lacking a proper load shedding scheme will lead to system instability and it will cause serious system frequency decay. We have proposed a solution to optimize the manual load shedding schedule with the application of optimization techniques, specifically the Genetic Algorithms. We have considered current hold by all feeders throughout the country, and the time period of load shedding as main factors in the optimization model. Our results show that, using our proposed model, we can minimize the imbalance between the supply and demand of electricity by selecting the best feeder to be selected for load shedding under given constraints.Publication Open Access A Framework for Network Level Pavement Maintenance Planning for Low Volume Roads(Spriger Link, 2020) Pasindu, H. R; Sandamal, R. M. K; Perera, M. Y. ILow volume roads (LVRs) play a pivotal role in the economic development of rural areas especially by providing connectivity for the communities to access markets, education and social needs in an efficient manner. They serve as the link between the local road network to the arterial and collector road network designed at providing accessibility to residential, agricultural or industrial areas. Lack of funding, subjective and ad hoc decision making has resulted in an inefficent utilization of resources in the local road agencies. Lack of a sound analytical process is a major impediment to maintain these roads in cost effective manner under the resource constraints prevalent. Existing pavement management systems (PMS) require extensive data collection and complex analysis processes, which makes them impractical to be deployed in local agencies. The core attributes of the proposed system are, reduced the data requirements, simplified the analytical tools and allowing users to customize considering the resource constraints. In this study, a relationship between International Roughness Index (IRI) and relevant distresses for LVR is established and based on that cost estimation model is developed for distress repair. Furthermore, the strategy which provide maximum condition for preventive maintenance is found by using decision tree approach in the network level optimization. A case study illustrated that the use of proposed PMS provides better overall network condition with compare to conventional decision making for same budget level.Publication Embargo Optimization of controller gains for FPGA-based multivariable motion controller using response surface methodology(IEEE, 2015-05-03) Sekaran, H. P; Liyanage, M. H; Krouglicof, NField Programmable Gate Arrays (FPGA) have become increasingly popular in recent years for control applications. Using contemporary FPGA technology, a powerful virtual processor can be synthesized and integrated with custom hardware to create a dedicated controller that outperforms conventional microcontroller and microprocessor based designs. The FPGA based controller takes advantage of both hardware features and virtual processor technology. This study details the development of a cascaded type PD controller for an inverted pendulum system implemented on a single FPGA device. The controller includes a hardware based implementation of the IO modules including quadrature decoders/counters and a Pulse Width Modulation (PWM) controller for the motor driver. The NIOS II processor was synthesized to implement the cascaded PID controller algorithm. This study also proposes a novel method for obtaining the optimal controller gains for the system. It uses the Central Composite Design (CCD) in Response Surface Methodology (RSM) for obtaining these gains. A classic inverted pendulum system was selected to demonstrate the applicability of the proposed approach. The gains provided by the RSM were verified experimentally to validate the proposed controller tuning method.