Browsing by Author "Siriwardana, S"

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Embargo
Elegant Fit-On – Virtual Fitting Room on Handheld Devices
(IEEE, 2022-12-09) Galagoda, R.R.N.P.A.B.W.M.S.R; Gunarathne, E.H.N.L.; Maheshi Purnima, K.A.D.; Wickramarathna, H.P.C.S.; Reyal, S; Siriwardana, S
Clothing has been one of the basic human needs since ancient times. It is a common thing to try on clothes and consider certain features when buying clothes. With the current pandemic situation, it is risky to wear and buy clothes by physical shopping. Consequently, people do online shopping. Those existing shopping websites are not user-friendly and less reliable as the customers will not have the privilege to purchase the exactly fitting outfit. Therefore, the customer satisfaction level is low with the clothes they have bought through online platforms. Therefore, the aim is to utilize technology to provide a virtual fitting room experience on handheld devices. The objective is to create a customized 3D avatar that represents the customer’s unique body shapes and features, which allows to try on clothes. This avatar is 360 degrees rotatable with pre-defined poses to check what the fit-on looks like. This solution shows whether the clothes are too fit or loose for the customer by showing live wrinkles. The text and voice feedback are generated at the end, which would be helpful for differently-abled people, especially those with vision issues.
Embargo
EyeDriver: Intelligent Driver Assistance System
(IEEE, 2019-12-18) Gayadeeptha, P; Baddewithana, T. P; Pannegama, K. V; Samarakkody, C. S; Samarasinghe, P; Siriwardana, S
“EyeDriver” is a driver assistance system that analyzes and provides real-time driver assistant data from four separate components. These main components are drowsiness detection and head pose estimation, over-speed detection, lane departure, and front collision avoidance. It is a compact product that included a Raspberry pi board, a USB camera module, Pi camera, and a TFT LCD. Since the “EyeDriver” is a first affordable aftermarket solution in Sri Lanka, it can be mounted and configured in any vehicle without any professional knowledge in less effort. Drowsiness detection and head pose estimation component will monitor the driver's eyes and keep track of whether the driver's head's position is inconsistent or deviated from the optimal position. In accordance with the road's recommended speed, the vehicle's actual speed is analyzed and if it is more than the permitted, the system makes a notification. It is done by the over-speed detection component. Lane departure component consists of assisting in keeping the vehicle stable on the desired lane on the road. Also, when the driver makes an intended lane change, the system provides a notification. The Front collision avoidance part will detect the frontal obstacle on the road and provide pre-collision/proximity warning notification. The notification makes according to the vehicle speed and distance between the object and the vehicles. The whole system is based on the Raspberry Pi 3 Model B+ board and the implementation of the system has been done by using OpenCV and Python.
Embargo
ScheduleME - Smart Digital Personal Assistant for Automatic Priority Based Task Scheduling and Time Management
(IEEE, 2021-10-01) Liyanage, A. N; Madhushanka D, A.G. A; Uduwara L, U.M.; Jayarathne, W. M. S. D; Siriwardana, S; Mithsara M, W. K
At present, it has become challenging for university students to manage their workload such assignments, projects etc. among their day-to-day tasks and personal chores. It has become hard to spend time efficiently on tasks that should be prioritized, and to decide what the best way to spend their remaining time is. Even though integration methods and multi-functional Time Management Tools (TMTs) such as Trello and Asana exist, finding, following, and implementing them is time consuming and monotonous. ScheduleME is a smart digital personal assistant, which will be in a form of a mobile app that collects and stores all the tasks the student must do, prioritize them according to their importance, schedule them intelligently across the student’s remaining time considering his/her existing academic and personal timetables and daily routines. A user-friendly and comprehensible mobile app is designed where the right amount of information is presented to the user without important details that user could conFigure and override and not show too much information such that the user becomes overwhelmed. This overcomes the weakness found in many time-management and to do list apps. (e.g. - Trello, Microsoft Tasks, Todoist) where the user must enter all the details of the tasks manually and set the priority manually. The main emphasis of our suggested system is four primary components. They are Data engineering, Intelligent task breakdown and scheduling, Personalized task scheduling and User-centered interaction design. Aside from that, this system employs a variety of technologies and algorithms to improve the research’s accuracy and efficiency.
Embargo
Smart Caring System for Ornamental Fish
(IEEE, 2022-12-09) Fernando, S; Jayaweera, N; Pitawala, S; Kaushalya, R; Ratnayake, P; Siriwardana, S
Ornamental Fish Industry continues to be one of the fastest growing sectors worldwide. Healthy fish production at aquariums requires intensive care and ensures a stable and an optimum production environment inside the fish tanks, which is a challenging task. Unfortunately, due to the limitations in fish industry, productivity of well-developed, healthy fish has drastically depreciated. Limited skills and knowledge of aquarists have been a challenging task which has led to inaccurate predictions on certain factors such as quantification and length of estimation, amounts and types of fish food and servicing the filters at proper time intervals. Existing aquariums depend on the experience and availability of the aquarists, which can be a challenging process in real life. Developing a system to regulate these major concerns is a prominent solution. This research is done to propose an automated method, with the help of several fish aquariums and existing research papers, to encounter the mentioned major concerns which affects the aquarists and other stakeholders.
Embargo
Voice Enabled Intelligent Programming Assistant
(IEEE, 2022-12-09) Wataketiya, R; Chandrasiri, N; Kithsiri, R; Malwatta, H; Nadeeshani, M; Siriwardana, S
In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one’s voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, “Venic”.