Browsing by Author "Lokuliyana, S"

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Aqua Safe: Blockchain Based Maritime Communication System using Ad hoc Network
(IEEE, 2022-12-26) Lokuliyana, S; Wellalage, S; Warusavithana, L; Pathirana, M; Kodithuwakku, S
The lack of a pre-existing infrastructure for facilitating long-range connectivity with the land makes maritime communications extremely difficult. Satellite connections, which are expensive, and use much power, are generally used to communicate on the high seas. For better connectivity between fisheries and land stations, different functional methods such as whether detection, boundary detection, data security, barrier detection, and data communication without interruption have been implemented in the system. Implementing a LoRa WAN system is to inform about emergencies in the deep sea and send the information indicated above. IoT node-based Ad hoc network is used to communicate with the land station without an internet connection. In case of emergency or when the fisheries need to send data and information to the land station in real-time, the fishing boat can interact with the land station through this proposed system. Blockchain technology is used in the system to ensure secure communication of information. In this scenario, the blockchain technology has enabled it to deploy distributed networks and perform secure peer-to-peer transmission and data integrity without a third party accessing the network.
Open Access
BIOMETRIC SMART SECURITY SYSTEM WITH CHILD CARE FOR A SMART SOCIETY
(IET- Sri Lanka Network, 2019) Lokuliyana, S; Mundigala, I. U; Sanjeewa, G. H. A
This research is mainly focused on Infant movement detection and alerting, in order to enhance their security within the home premises. As the first move, the research focuses on the identification of the human and classifying whether an adult or a baby. Then a model was built up in three classifications to identify static and dynamic positions of the infant, through Image Processing and analysis. In order to enhance the accuracy of the custom classifiers an already trained model using 1 million image set was retrained by customized image sets. To present this research as a smart home solution modern technology were used in implementing the close connection between the infant and the parent.
Embargo
Context Rich Hybrid Navigation Using WiFi and Geomagnetic Sensors in Smartphones and Map Generation Using Lidar
(IEEE, 2019-10-08) Jayakody, A; Lokuliyana, S; Weerawardene, V. N. N; Somathilake, K. D. P. S; Ishara, A. M. D. D. U
Navigation systems perform a huge role in traveling component of life. Most importantly it helps people to get to places even in foreign or unfamiliar environments. This research introduces a way of mapping environments with less effort, which shows that mapping an indoor environment is an easy task that could be performed by any tech savvy individual. This has been done by examining several projects and researches conducted by various personnel and organizations including NASA. It has become clear that the technology `LIDAR,' is clearly feasible for the requirement of indoor map generation. A software was later built to accommodate the device which is built using LIDAR and to give the user a better experience in map generation. The software helps to overcome the limitations that are imposed by the device. The overall product with the device and software integrated provides an ideal low-budget solution for the users. The proposed system service features three highly desirable properties, namely accuracy, scalability, and crowdsourcing. IPS is implemented with a set of crowdsourcing-supportive mechanisms to handle the collective amount of raw data, filter incorrect user contributions and exploit Wi-Fi data from diverse mobile devices. Furthermore, it uses a big-data architecture for efficient storage and retrieval of localization and mapping data. In this research, the service relies on the sensitive data collected by smartphones (Wi-Fi signal strength and geomagnetic measurements) to deliver reliable indoor geolocation information.
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CURETO: Skin Diseases Detection Using Image Processing And CNN
(IEEE, 2020-11-17) Karunanayake, R. K. M. S. K; Dananjaya, W. G. M; Peiris, M. S. Y; Gunatileka, B. R. I. S; Lokuliyana, S; Kuruppu, A
Busy lifestyles these days have led people to forget to drink water regularly which results in inadequate hydration and oily skin, oily skin has become one of the main factors for Acne vulgaris. Acne vulgaris, particularly on the face, greatly affects a person's social, mental wellbeing and personal satisfaction for teens. Besides the fact that acne is well known as an inflammatory disorder, it was reported to have caused serious long-term consequences such as depression, scarring, mental illness, including pain and suicide. In this research work, a smartphone-based expert system namely “Cureto” is implemented using a hybrid approach i.e. using deep convolutional neural network (CNN) and natural language processing (NLP). The proposed work is designed, implemented and tested to classify Acne density, skin sensitivity and to identify the specific acne subtypes namely whiteheads, blackheads, papules, pustules, nodules and cysts. The proposed work not only classifies Acne Vulgaris but also recommends appropriate treatments based on their classification, severity and other demographic factors such as age, gender, etc. The results obtained show that for Acne type classification the accuracy ranges from 90%-95% and for Skin Sensitivity and Acne density the accuracy ranges from 93%-96%.
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A database optimization model with quantitative benchmark
(IEEE, 2016-03-11) Murray, I; Jayakody, A; Herrmann, J; Lokuliyana, S; Kandawala, D. S. A; Nanayakkara, S. E. C
Query optimization and indexing have an immense impact on database optimization. This has been considered in many different perspectives which provide several different solutions in each case. The purpose of this paper is to primarily provide a comprehensive review and discussion of the core problems through the research on query optimization technology and indexing, based on a number of optimization techniques commonly used in the general approach of a query. A new database optimization model is designed and experiments show that this model can significantly reduce the amount of query execution time to improve the optimization efficiency. Regardless of research on the database optimization model, significant work has been done to comparatively evaluate three scenarios; non-optimized query, optimized query without following any optimization standard, and optimized query via proposed optimization model using the same experimental methodology. Further, this paper describes a benchmark that was developed specifically for the purpose of measuring the quantitative evaluations of the proposed database optimization model.
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Digital Assistant to Aid Individuals with Print Disabilities to Interpret Printed Materials
(IEEE, 2022-12-26) Priyashan Sandunhetti, S. H. S; Sanduni Madara, P. G; Dilitha Ranjuna, G. P; Prabhash, K. V. A. S; Jayakody, J. A. D. C. A.; Lokuliyana, S
Print disability is the difficulty or inability to read printed material due to a perceptual, physical, or visual disability. An individual can be classified as a print-disabled individual if the person requires alternative access or accessible formats (Braille, Audio) to gain information from printed materials. Print disability can be caused by vision impairments, blindness, physical dexterity problems, learning disabilities, brain injuries, cognitive impairments, and literacy difficulties. There are millions of people around the world who cannot interpret printed materials due to the above difficulties. This can affect the individual’s day-to-day life as well as their studies. Even though there are tools to interpret printed materials into text, most of them are not sufficient to aid print-disabled individuals and lack accessibility options within the tools. Therefore, we propose to develop a mobile-based application to aid print disabled individuals to interpret printed materials which they cannot access without any assistance otherwise. This application will be based on machine learning and image processing and will be able to interpret printed materials including text and paragraphs, mathematical formulas, tables, charts, and images. Also, the application will be designed with accessibility features which enable print disabled individuals to use the application without any third-party assistance.
Open Access
Digital Talking Book
(https://www.researchgate.net/publication/280314319, 2015-07) Thirasi, W. A. P. B; Illangasinghe, I. M. B. S. C; Dickwella, U. P; Jayakody, A; Peiris, G. C; Lokuliyana, S
This paper, presents user friendly ways to read books for print disable individuals. "Reading" is the process of looking at a series of written symbols and making meaning from them. However, there, the print disabled who are, the blind, partially sighted, dyslexics, those with visual impairments, physically disabled, and learning-disabled who have difficulty in accessing print media information. Digital talking books are the significant technology for the print disabled community to access printed media information. The Digital Accessible Information System (DAISY) technology; it is an open international standard for accessible multimedia developed by libraries serving persons with print disabilities in collaboration with the target users around the globe. The proposed “Talking Book" improves the blind users' ability to read digital daisy books. The main function of the talking book player; computer memory and retrieves bookmarks, automatically unzip downloaded zip files and convert them into readable manner. Additionally, it consists predefined gestures and voice commands to navigate through the pages in the diligence. This paper presents a user interface with an easy-to-distinguish layout, auditory output and gestural input that enables visually impaired people to interact with an Android smartphone device.
Embargo
Driving Innovative Culture with Emotional Intelligence
(IEEE, 2023-06-12) Rizwi, A; Lokuliyana, S
This research aims to examine the relationship between employee innovation and positive and negative contagion within supervising roles. Establishing an innovative culture within the organization and having managers with a high level of Emotional Intelligence are essential. As a result, this enables the study to examine the effects of these factors on employees. The study is evaluated the effects of adopting an innovation culture and working with managers who are emotionally quotient on the performance of the employees. In the corporate sector, innovation takes place under different conditions than in the private sector. Human beings experience emotions daily. An employee survey of 40 items (5-point Likert Scale) is distributed. A total of 200 surveys have been evaluated. The validity and reliability of the data were checked using SPSS, and the results were assessed using regression analysis. It involves constructing a confidence interval based on a single sample and a given level of confidence. The findings indicate that Emotional Intelligence, innovative organizational culture, and employee performance are meaningfully related. In conclusion, organizations must create innovative institution cultures and employ managers that have high levels of Emotional Intelligence to increase their employees' performance using the application of innovation.
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, A
The 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.
Embargo
Enhanced algorithmic implementation to assist real-time indoor map generation for vision impaired individuals
(IEEE, 2018-08-08) Jayakody, A; Murray, I; Hermann, J; Lokuliyana, S; Dunuwila, V. R
The complexity of indoor environments has made navigation difficult for vision impaired individuals as well as individuals with clear vision. Although handheld mobility devices have been developed to assist the vision impaired in navigation, they are incapable of capturing parameters such as distance, angle and direction. This paper presents an appraised framework; the Accessible Building Information Model (AccessBIM), which could be used for generating an indoor map in real-time with the classification of real world objects and their locations. The AccessBIM database is equipped with two optimization algorithms; a database optimization algorithm that reduces the time of query execution through indexing, query re-writing, schema redesigning and a memory optimization algorithm known as “Memcache”. Five scenarios were tested using a simulator to determine the accuracy of the map that is generated. The use of the two algorithms ensured that the real-time map generated through the data collected from the simulation environment was similar to the actual floor plan. Hence, it can be concluded that the AccessBIM framework has the potential to play an integral role in assistive technologies related to localization and mapping, thus significantly improving the quality of life for individuals with vision impairment.
Embargo
A framework for Business Process Re-engineering to reduce the number of processes-a case study of National Blood Transfusion Services
(IEEE, 2016-03-11) Jayakody, A; Pemarathna, H. P. P. A; Lokuliyana, S; Mapa, N. T
Blood Donation and Blood Transfusion Services play a vital role in saving people's lives. It is a known concern that the blood donation process usually consumes a lot of time and effort from both donors and medical staff. This issue is present, mainly due to the absence of a concrete and precise information system. If such a systems is implemented it could have the ability to allow donors and blood donation centers to communicate efficiently and collaborate with each other to minimize the time and effort required for the blood donation process. Besides, most blood banks work in isolation and are not integrated with other blood donation centers, which affect and degrade the quality of overall blood donation and blood transfusion services. This work aims at developing a standard framework named as “One Blood” based on business process re-engineering concepts, cloud storage services, and web application development technologies. This paper comprehensively describes the conceptual framework based on a case study of National Blood Transfusion Services in Sri Lanka. As a result, several pitfalls, highly critical processes, and points of failure were identified, which needs to be redefined. Improving the workflows and organizing the processes was conducted by the application of BPR concepts followed by the proposed framework. To further amplify the application of BPR two additional verticals namely Process Re-Organization and Radical Redesign was aligned with the Process Re-engineering phase. Process Re-Organization performs the comparing and contrasting of manual and systematic approaches while Radical Redesign enables the chance to leverage IT related technologies to achieve integration and automation of processes. The outcome of this research was presented as a cloud-based centralized web solution for the NBTS using the One Blood System by the integration of all of these concepts and technologies.
Open Access
Gesture driven smart home solution for bedridden people
(Association for Computing Machinery, 2020-09-21) Jayaweera, N; Gamage, B; Samaraweera, M; Liyanage, S; Lokuliyana, S; Kuruppu, T
Conversion of ordinary houses into smart homes has been a rising trend for past years. Smart house development is based on the enhancement of the quality of the daily activities of normal people. But many smart homes have not been designed in a way that is user friendly for differently-abled people such as immobile, bedridden (disabled people with at least one hand movable). Due to negligence and forgetfulness, there are cases where the electrical devices are left switched on, regardless of any necessity. It is one of the most occurred examples of domestic energy wastage. To overcome those challenges, this research represents the improved smart home design: MobiGO that uses cameras to capture gestures, smart sockets to deliver gesture-driven outputs to home appliances, etc. The camera captures the gestures done by the user and the system processes those images through advanced gesture recognition and image processing technologies. The commands relevant to the gesture are sent to the specific appliance through a specific IoT device attached to them. The basic literature survey content, which contains technical words, is analyzed using Deep Learning, Convolutional Neural Network (CNN), Image Processing, Gesture recognition, smart homes, IoT. Finally, the authors conclude that the MobiGO solution proposes a smart home system that is safer and easier for people with disabilities
Embargo
HemoSmart: A Non-Invasive Device and Mobile App for Anemia Detection
(John Wiley & Sons, Inc., 2021-04-06) Jayakody, A; Edirisinghe, E. A. G. A; Lokuliyana, S
The Hemoglobin concentration in human blood is an important substance to health condition determination. With the results which are obtained from Hemoglobin test, a condition which is called as Anemia (a low level of Hemoglobin) can be revealed. Traditionally the Hemoglobin test is done using blood samples which are taken using needles. The non-invasive Hemoglobin level detection system, discussed in this paper, describes a better idea about the hemoglobin concentration in the human blood. The images of the fingertip of the different hemoglobin level patients which is taken using a camera is used to develop the neural network-based algorithm. The pre-mentioned algorithm is used in the developed non-invasive device to display the Hemoglobin level. Before doing the above procedure, an account is created in the mobile app and a questionnaire is given to answer by the patient. Finally, both the results which are obtained from the mobile app and the device are run through a machine learning algorithm to get the final output. According to the final result patient would be able to detect anemia at an early stage.
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i-Police-An Intelligent Policing System Through Public Area Surveillance
(IEEE, 2021-10-27) Jayakody, A; Lokuliyana, S; Dasanayaka, K; Iddamalgoda, A; Ganepola, I; Dissanayake, A
Technology and law enforcement are now commonly used hand in hand to improve public safety. Most police departments only use CCTV cameras at a few major intersections for remote surveillance. The public is waiting too long for emergency response lines, therefore using new technologies to improve the current policing system has become one of the police's main goals. The paper presents a coordinated framework that could identify the subtleties of violations via an automated public area surveillance system, specifically the weapon-related crimes and vehicle accidents, which are then disassembled, analyzed, and stored for future inspections. The trained models are aimed to reduce the false positives of incident detection. The weapon detection system had the best average precision (93.8%) by using YOLOv5 while the vehicle accident detection system resulted in the best average precision (94.9%) by using YOLOv4. The system is tested against the collected set of CCTV footage and tested how long it takes to create a notification which is the main goal of this system. Notification is generated in less than 5 seconds after an incident is detected. The evidence collection engine developed with MATLAB delivered the expected with an accuracy of 97% making the extracted evidence reliable to both vehicle accidents and crime scenes. Additionally, the framework provides an effective and efficient communication channel through which the residents can report crimes to regular parties.
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IGOE IoT framework for waste collection optimization
(IEEE, 2017-01-27) Lokuliyana, S; Jayakody, A; Rupasinghe, L; Kandawala, S
Waste management has become a major issue in all the part of the world and tends to grow day by day. Mismanagement in waste has become one of the key environmental and health issue. With the increase of population, especially in the urban areas waste collection, categorization, and disposal has become a major hazard for the government authorities. An IoT based waste collection framework is proposed to automate the solid waste identification, localization and collection process. The authors are involved in the identifying key impact factors in the waste collection process and provide systematic and automated solution to optimize the process to achieve higher efficiency. A layered architecture is introduced to handle the waste collection process and an optimization algorithm is derived for the existing business process based on the proposed evaluation criteria. The final outcome is a complete framework which compromises the Inputs, Outputs, Guide and Enables. The main objective is to implement an optimized automated waste collection system with the use of a vast sensor network capable of gathering waste data and by implementing an optimization algorithm in waste collection.
Embargo
IGOE IoT framework for waste collection optimization
(IEEE, 2017-01-27) Lokuliyana, S; Jayakody, J. A. D. C. A.; Rupasinghe, L; Kandawala, S
Waste management has become a major issue in all the part of the world and tends to grow day by day. Mismanagement in waste has become one of the key environmental and health issue. With the increase of population, especially in the urban areas waste collection, categorization, and disposal has become a major hazard for the government authorities. An IoT based waste collection framework is proposed to automate the solid waste identification, localization and collection process. The authors are involved in the identifying key impact factors in the waste collection process and provide systematic and automated solution to optimize the process to achieve higher efficiency. A layered architecture is introduced to handle the waste collection process and an optimization algorithm is derived for the existing business process based on the proposed evaluation criteria. The final outcome is a complete framework which compromises the Inputs, Outputs, Guide and Enables. The main objective is to implement an optimized automated waste collection system with the use of a vast sensor network capable of gathering waste data and by implementing an optimization algorithm in waste collection.
Open Access
Indoor Positioning: Novel Approach for Bluetooth Networks using RSSI Smoothing
(Foundation of Computer Science (FCS), NY, USA, 2016-03) Chathurangi, D; Vithana, D; Jayakody, A; Lokuliyana, S
In recent years, localization and navigation have been important topics in research. The most popular navigation system is an outdoor navigation with “GPS”; however, the positioning within indoor environments is not possible with “GPS”, so it is resulting in limited operation for indoor environments. In order to overcome this limitation, this paper discussed Bluetooth Low Energy technology based localization model. The “BLE” provides several major forms of parameters linked to location estimation such as “RSSI” and “LQI”. In real time applications such as object tracking and distance estimates require continuous reception of RSSI measurements to estimate the position of the object accurately. Nevertheless, on that point, there are some constraints such as signal attenuation, signal loss, multipath effects, temperature, reflection, a human body and other communication signals. Hence, this research work considered the “RSSI” smoothing approaches. Although there are so many solutions, no RSSI smoothing method has been recognized as a standard method. This paper presents a Feedback filter together with shifting technique at distance domain to reduce fluctuations of the real-time signals. Experiments show that the probability of locating errorless and it is better than the other existing interference avoidance algorithms.
Open Access
Intelligent Vision Impaired Indoor Navigation Using Visible Light Communication
(Springer, Cham, 2020) Jayakody, A; Murray, I; Hermann, J; Lokuliyana, S; Dunuwila, V
Recent statistics of the World Health Organization (WHO) indicate that over 253 million of the world’s population to be visually impaired. Most of these individuals use the white cane as an assistive tool or are often accompanied by caretakers or voluntary helpers as indoor navigation is particularly challenging for them. This chapter describes a substitute vision system designed to assist vision impaired individuals through the use of visible light communication and geomagnetism. Furthermore, the use of database optimization increases the speed and efficiency of data retrieval thus reducing system response time. Though navigation systems that support the visual impaired are readily available, there have been no systems that use both visible light communication and geomagnetism capable of providing accurate and secure indoor navigation assistance, which in turn would increase the overall satisfaction of the system users.
Embargo
IoT Device to Detect Anemia: A Non-Invasive Approach with Multiple Inputs
(IEEE, 2019-12-05) Hafeel, A; Fernando, H. S. M. H; Pravienth, M; Lokuliyana, S; Kayanthan, N; Jayakody, A
Detection of diseases is a key aspect when considering the world today. Diseases if not cured early it gets worse day by day. Therefore, early detection of the disease is a key aspect that needs to be considered. In this project, the team aims to develop a device to detect Anemia which is a disease caused due to the lack of Fe3+ ions in the body. This is a disease that would even lead to organ failure eventually leading to a heart attack or death. Anemia is causing the red intensity of blood to reduce. Therefore, the team is using that factor to detect the disease. The team has built this device using a key symptom where the intensity of red in the blood is measured and the output is sent to a central server, whilst the server also gets input from a questionnaire that is built in-app. Using this data, the server will decide whether the user is suffering from anemia or not. When tested against the anemia patient there is an accuracy rate of almost 83% that is obtained and when crossed checked against the actual testing done, it qualifies the taken accurate result.
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Location based garbage management system with iot for smart city
(IEEE, 2018-08-08) Lokuliyana, S; Jayakody, A; Dabarera, G. S. B; Ranaweera, R. K. R; Perera, P. G. D. M; Panangala, P. A. D. V. R
Smart cities integrate multiple ICT and IOT solutions to build a comfortable human habitation. One of these solutions is to provide an environmentally friendly, efficient and effective garbage management system. The current garbage collection system includes routine garbage trucks doing rounds daily or weekly, which not only doesn't cover every zone of the city but is a completely inefficient use of government resources. This paper proposes a cost-effective IOT based system for the government to utilize available resources to efficiently manage the overwhelming amounts of garbage collected each day, while also providing a better solution for the inconvenience of garbage disposal for the citizens. This is done by a network of smart bins which integrates cloud-based techniques to monitor and analyze data collected to provide predictive routes generated through algorithms for garbage trucks. An android app is developed for the workforce and the citizens, which primarily provides the generated routes for the workforce and finds the nearest available smart bin for citizens.