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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2018 - 201912020 - 20211

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Has files: YesSubject: search.filters.subject.Automobile

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    PublicationOpen Access
    E-Commerce Video Based Automobile Website
    (Human Resource Management Academic Research Society, 2018-12-12) Pathirana, U.P.G.Y; Wellala, D. S. M
    With the development of new technologies people tend to take maximum advantage from the new technologies available. This new improvements have a huge impact on buying and selling also. The ultimate target of this project is to provide a better solution for buying and selling which specifically address buying and selling of vehicles. The final outcome of this project is going to be a website which facilitates online video advertising for vehicles available for sale. The basic of the project is going to be data collection in order to identify criteria’s that customers are expecting from this kind of website. An online survey will provide to record responses. When the website is developed vehicle owners can prepare a small video about the vehicle which is on sale which provides a clear understanding about the vehicle. This enable buyers to get more details of the vehicle by staying at home if they are happy about the vehicle they can meet the dealer directly and go for negotiation. Also this website will facilitate them with leasing facilities, location facilities and many more. The basic technology using website is going to be is cloud technology. This enables more advantages from the technological side. The final outcome of this project will provide an advanced platform for customers and seller related to vehicle buying and selling. It will facilitate and, reduce cost and time each individual has to spend on buying a vehicle.
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    PublicationEmbargo
    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.