Faculty of Computing

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Mobile Base Solution for Individuals with Limited Knowledge About Cars
(IEEE, 2022-12-09) Nammunige, H; Chamuditha, T; Udara, S; Athapaththu, D; Gamage, A; Gamage, N
Different modes of transportation were discovered by our ancestors from ancient times. Currently, the majority of people choose to purchase a personal automobile for transport needs. However, the vast majority of people are not automobile industry experts. As a result, the majority of people have trouble when recognizing cars. Due to numerous variations of a single vehicle model, even an expert has trouble correctly identifying a certain car model. People must take into account a number of factors before purchasing a specific automobile. Some of crucial factors are service costs and future market prices. Ordinary people require the assistance of a professional when estimating the market price of a car and calculating the cost of servicing a car. Accidents can also occur at any time when driving a car often. In similar circumstances, consumers require the assistance of an insurance agent or a technician to estimate the cost of damage repair. In this study, we provide a way for non-automotive experts to use their smartphones to identify car models, forecast future market prices, determine and forecast servicing costs, and estimate minor damage repair costs. This paper demonstrates how we accomplished aforementioned tasks using YOLO V4, Multiple Linear Regression, Random Forest Classifier and Faster RCNN.
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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.
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Smart wheelchair to facilitate disabled individuals
(IEEE, 2019-12-05) Jayakody, A; Nawarathna, A; Wijesinghe, I; Liyanage, S; Dissanayake, J
This paper describes the design and implementation of a voice controlled smart wheelchair for disabled whom the manual operation is difficult due to lack of physical strength. The main objective of this research is to develop a smart wheelchair to facilitate disabled individuals which can be operated with lesser effort while operating the wheelchair. The proposed wheelchair can be controlled through voice commands which enables the user to control the wheelchair with less effort. This aids the disabled in carrying out daily activities independently within indoor environments. The proposed solution has five modules namely, speech recognition module, obstacle avoidance module, autonomous navigation module, health monitoring module, and central system controller. The wheelchair operates in two modes called manual mode and the autonomous mode. This paper presents a smart wheelchair that makes the disabled individuals' life easier with technology. Further this paper elaborates testing and evaluations carried out to prove the proposed title.
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AVII [assist vision impaired individual]: an intelligent indoor navigation system for the vision impaired individuals with vlc
(IEEE, 2016-12-16) Jayakody, A; Meegama, C. I; Pinnawalage, H. U; Muwenwella, R. M. H. N; Dalpathado, S. C
Vision impaired individuals confront unique challenges every day in their day-to-day life when navigating in unfamiliar public locations. The proposed system focuses on designing a device for vision impaired people that is comfortable, user friendly and can help with travelling independently. The solution is an audio guidance system that provides guidance through voice commands and beep sounds. In this study, authors propose an indoor navigation system that utilizes visible light communication (VLC) technology, which employs LED lights, geomagnetism technology, best path detection algorithms and obstacle detection aimed at supporting visually impaired people to overcome the positioning and navigating problems. System uses a MCU based mechanism to transmit positional information by leveraging the existing LED lights of the indoor environment. The study looks at an improved version of Dijkstra's algorithm to estimate search time and distance to find the best path for the navigation purposes. Geomagnetic sensor is used to obtain the travelling direction of the visually impaired individual to provide an extreme accurate system to take the turns accurately according to the best path and to correct the individual while traveling. Sonar sensors are used for obstacle detection which aids the individual to prevent any collisions or injury. Database optimization involves in increasing the speed and efficiency of the retrieved data and reduces the system response time.

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