Faculty of Computing

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Author: search.filters.author.Fernando, SHas files: Yes

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Now showing 1 - 8 of 8
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    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.
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    Moderate Automobile Accident Claim Process Automation Using Machine Learning
    (IEEE, 2021-01-27) Imaam, F; Subasinghe, A; Kasthuriarachchi, H; Fernando, S; Haddela, P. S; Pemadasa, N
    In modern-day, traditional automobile accident claim process struggles to keep up with the recurring automobile accidents and furthermore, the claim itself is a critical point in which the policyholder may decide to switch to a different automobile insurance provider. In this paper, the authors present a system which can be used to automate the processing of claims for automobiles which were involved in less severe accidents in a much quicker manner. The presented system comprises of four components, each with a model developed using computer vision or machine learning techniques to facilitate the automation process. The models are built and fine-tuned using transfer learning and ensemble learning techniques in order to determine the damaged component of the automobile, determine the make and model of the automobile, compute an accurate repair estimate and also compute the likeliness of the policyholder may churn, to ensure that the policyholder is satisfied with the appraised amount and will be retained by the insurance provider.
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    PublicationEmbargo
    VTutor: A Platform for Improving Searchability and Interactivity of Recorded Lectures
    (IEEE, 2019-12-05) Karunaratna, D; Hettiarachchi, I; Fernando, S; Epa, S; Kodagoda, N; Suriyawansa, K
    Recorded lectures have gained popularity as a method of delivering lecture content as they give learners a host of distinct advantages such as the ability to follow lectures without time or location constraints and to consume the lectures at their own pace. However, despite such benefits, they have a tendency to be lengthy and tedious to watch. They also prove cumbersome when precise information needs to be extracted from the content. Another drawback is that recorded lecture videos fail to show the connection between the lecture and its support material such as slides and questionnaires. Though many of the existing platforms allow editing lecture videos for more interactivity, the methods employed by these platforms have always been manual, and therefore time intensive. VTutor is a web platform that aims to address these drawbacks by introducing automation into the video enhancement process, eventually combining the lecture material to create an enhanced user experience. Specifically, VTutor allows users to navigate through a lecture video using subtopics, its corresponding slides and code samples. Furthermore, it is equipped with the ability to automatically generate questions by scraping the internet based on provided keywords thus improving the level of engagement that a learner has with the lecture.
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    PublicationOpen Access
    An automatic air inflated tubeless safety jacket for motorbike riders
    (Emerald Publishing Limited, 2021-06-22) Bulathsinghala, R. L; Fernando, S; Jayawardena, T. S. S; Heenkenda, N; Jeyakumar, S; Packiyarasa, p; Gamage, H; Wijesena, D
    Purpose – Motorcycle is one of the popular modes of transport in developing countries. However, the statistics related to accidents show that motorcycles are the most vulnerable vehicles. Research studies have revealed that half of all the possible types of motorcycle injuries could be reduced or prevented using effective protective clothing. Facts and figures emphasize that this is high time to develop a safety jacket for motorbike riders. This paper aims to develop an innovative, integrated automatic air-inflated tubeless jacket to prevent major injuries in fatal accidents. Design/methodology/approach – Two accelerometers integrated near the front axle, an angle sensor and the electronic control unit (ECU) were used to detect the collision or accident. The sensors were fixed on the bike and connected with the ECU via a bluetooth device that was always at the activated stage. The fused sensors were emulated with the ECU under laboratory conditions. The trigger signal generated by the crash discriminant algorithm triggered the chemical reaction to generate N2 gas and inflate the tubeless safety jacket. Findings – Under laboratory conditions, it was found that the signal generated by the ECU unit ejected approximately 15 litres of N2 gas in volume to fill the jacket within 100 milliseconds, which was less than the approximate estimated falling time of the rider 120 milliseconds. Originality/value – The existing developments of airbag systems in motorbikes are mounted on the motorbikes’ frame, following the airbag systems in automobiles. These developments cannot fully protect the rider due to differentiation in crash dynamics and respective positions of the rider at the point of impact. Though few safety jackets and airbag vests are developed, the airbag deployment is activated when rider and motorbike separated during a collision using a tether-triggering mechanism. The authors designed the jacket so that inflation is activated not only by crash sensors but also on the fusion of multiple sensors based on a crash discriminative algorithm. The airbag deployment mechanism is incorporated with the jacket and acts as a safety jacket during a collision
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    PublicationEmbargo
    An automatic air inflated tubeless safety jacket for motorbike riders
    (Emerald Publishing Limited, 2021-06-22) Bulathsinghala, R. L; Fernando, S; Jayawardena, T. S. S; Heenkenda, N; Jeyakumar, S; Packiyarasa, P; Gamage, H; Wijesena, D
    Purpose – Motorcycle is one of the popular modes of transport in developing countries. However, the statistics related to accidents show that motorcycles are the most vulnerable vehicles. Research studies have revealed that half of all the possible types of motorcycle injuries could be reduced or prevented using effective protective clothing. Facts and figures emphasize that this is high time to develop a safety jacket for motorbike riders. This paper aims to develop an innovative, integrated automatic air-inflated tubeless jacket to prevent major injuries in fatal accidents. Design/methodology/approach – Two accelerometers integrated near the front axle, an angle sensor and the electronic control unit (ECU) were used to detect the collision or accident. The sensors were fixed on the bike and connected with the ECU via a bluetooth device that was always at the activated stage. The fused sensors were emulated with the ECU under laboratory conditions. The trigger signal generated by the crash discriminant algorithm triggered the chemical reaction to generate N2 gas and inflate the tubeless safety jacket. Findings – Under laboratory conditions, it was found that the signal generated by the ECU unit ejected approximately 15 litres of N2 gas in volume to fill the jacket within 100 milliseconds, which was less than the approximate estimated falling time of the rider 120 milliseconds. Originality/value – The existing developments of airbag systems in motorbikes are mounted on the motorbikes’ frame, following the airbag systems in automobiles. These developments cannot fully protect the rider due to differentiation in crash dynamics and respective positions of the rider at the point of impact. Though few safety jackets and airbag vests are developed, the airbag deployment is activated when rider and motorbike separated during a collision using a tether-triggering mechanism. The authors designed the jacket so that inflation is activated not only by crash sensors but also on the fusion of multiple sensors based on a crash discriminative algorithm. The airbag deployment mechanism is incorporated with the jacket and acts as a safety jacket during a collision
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    PublicationOpen Access
    Measurement of seam puckering and influence of its causes
    (IOSR Journal of Engineering (IOSRJEN), 2014-04-04) Fernando, S; Jayawardena, T. S. S
    The chlorophyll (Chl) fluorescence signatures of leaves have been widely applied as non-invasive techniques for the in vivo analysis of plant stress. The Chl fluorescence provides ample information on the photosynthetic apparatus as first discovered by Kautsky. Various ratios of the Chl fluorescence determined from the induction kinetics can be used as indicators of the stress effect to the photosynthetic apparatus. The high resolution multi-colour Chl fluorescence imaging techniques for whole leaves have been developed over the last years. These techniques offer the new possibility to study the distribution and patchiness of fluorescence signatures over the whole leaf area. The chlorophyll fluorescence induction kinetics (Kautsky effect) of predarkened leaves (30 min) was measured using the FluorCam 700MF imaging system (Photon Systems Instrument). The images of the measured Chl fluorescence intensity were obtained on false colour, whereby blue is the lowest (zero) and red the highest fluorescence. The images of various Chl fluorescence ratios were obtained by pixel to pixel arithmetic operations performed by FluorCam software. Efficiency of photosynthetic apparatus of analyzed endemic plants grown in different environmental stress conditions was evaluated via chlorophyll fluorescence imaging during induction kinetics and the fluorescence ratios which describe the photosynthetic light processes and quantum conversion of light.
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    Ai based greenhouse farming support system with robotic monitoring
    (IEEE, 2020-11-16) Fernando, S; Nethmi, R; Silva, A; Perera, A; De Silva, R; Abeygunawardhana, P. K. W
    Greenhouses plays a major role in today's agriculture since farmers can grow plants under controlled climatic conditions and can optimize production. The greenhouses are usually built in areas where the climatic conditions for the growth of plants are not optimal so requires some artificial setups to bring about productivity. Automating process of a greenhouse requires monitoring and controlling of the climatic parameters. This paper is an attempt to minimize the cost of maintaining greenhouse environments using new technologies. The end goal of this research an automated system to optimally monitor and control the environmental factors inside greenhouse by monitoring temperature, soil moisture, humidity and pH through a cloud connected mobile robot which can detect unhealthy plants using image processing and machine learning. The mobile robot navigates through a predefined map of greenhouse. Database server has created to store gathered real-time data. And the necessary accurate data represent by using proper application for analyzing.
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    Intelligent disease detection system for greenhouse with a robotic monitoring system
    (IEEE, 2020-12-10) Fernando, S; Nethmi, R; Silva, A; Perera, A; De Silva, R; Abeygunawardhana, P. K. W
    Greenhouse farming plays a significant role in the agricultural industry because of its controlled climatic features. Recent examinations have stated that the mean creation of the yields under greenhouses is lessening due to disease events in the plants. These foods have become an imposing undertaking because these plants are being assaulted by different bacterial diseases, micro-organisms, and pests. The chemicals are applied to the plants intermittently without thinking about the necessity of each plant. Several problems have occurred in the greenhouse environment due to these causes. Therefore, there is a huge necessity for a system to detect diseases at an early stage. This research focused on designing a system to detect disease, which causes yellowish in greenhouse plants. Plant yellowing can be considered a significant problem of plants that grow under greenhouse-controlled environments. Through this research is focused on the most important and one of the most attention-grabbing crop tomato. There are specific diseases that cause yellowish the tomato plant, and they have been identified. The techniques utilized for early recognition of infection are image processing, machine learning, and deep learning.