Faculty of Computing
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Publication Embargo Automated vehicle insurance claims processing using computer vision, natural language processing(IEEE, 2022-11-30) Fernando, N; Kumarage, A; Thiyaganathan, V; Hillary, R; Abeywardhana, LTraditional insurance claims processing systems are no match for the modern world due to the increasing population of vehicles and the resulting number of accidents. In this paper, the authors present a novel idea to automate the tedious processes in the insurance industry. The presented system consists of three main components namely, re-identify the make and model of the vehicle, identify the damaged automobile component, type, and severity, and compute an accurate repair estimate using damage component identification. Also, automate the documentation process by identifying the relevant fields in the voice input provided by the user. This ensures both the parties involved in this process will be benefited from the proposed system. Presented solutions Were designed using the aid of Artificial Intelligence techniques, mainly CNN models and Natural language processing techniques.Publication Embargo Geo-enabled FOSS tool supports for immediate flood disaster response planning(IEEE, 2014-12-22) Ramanayake, K; Vithanage, D; Hettiarachchi, N; Rathnayake, G; Rajapaksha, S, K; Fernando, N—Flood is a major natural hazard occur recurrently in Sri Lanka. Allocating victims to camps and provide medical facilities are two main activities at the immediate response phase of a flood and use of manual methods delayed this process. This project developed a geoenabled application to support immediate response planning, mainly focusing on allocation victims to IDP camps, provide medical facilities, and supporting access avoiding already blocked roads based on administrative divisions of the affected area. Capacities and facilities in camps and hospitals are matched against the needs of the victims. It identifies the blocked roads, alternative routes to reach resource centers, camps and hospitals and provide navigation guidance. The tool can be used after a flood disaster, assuming basic demographic data and the current flood affected area data are available. The tool is developed as a plug-in for QGIS, a free and open source desktop Geographic Information System software. The tool is verified with sample data related to “Kaluthara” area. It is intended to integrate with InaSAFE disaster response support tool at a later stage.Publication Embargo Emergency Patient Identification System(IEEE, 2019-12-05) Sandamal, T; Fernando, N; Jayasinghe, I; Xavier, J; Kuruwitaarachchi, N; Rupasinghe, LEmergency patient identification system (EPIS) will enable the more powerful quality system in the health industry. This research study was conducted to develop an EPI system, which is a complete patient-based medical information recording system. This system will help to identify the patients uniquely. Doctors can get patients' latest situation and can make quick decisions to do the treatments in emergencies. To achieve this approach, authors use the patient's fingerprint, face recognition technology, and eye recognition to identify the person. The patient can view his medical records; system reminds the notifications. The system helps the patients in storing and tracking the diet weight, medications, allergies, health history, fitness, lab results, x-rays, blood pressure, ongoing surgeries, drug reminders, doctor visits, doctor's appointments, images and more. The system helps the user in receiving and sending necessary health-related information to the doctors and hospitals. This system has many unique features; an emergency will help to find nearest hospitals. This can add patient's family member's history so it can help to remind his present medical situation. The main system is working on web interface; another part is offered as a mobile application.Publication Embargo A trilateral influence model for online shopping(IEEE, 2017-01-27) Samaraweera, S. A. K. G; Gamage, N. G. H. P; Gallage, I. G; Gunathilaka, D. D. T. M; Fernando, N; Kasthurirathna, DApplication of social influence toward E-commerce has brought a significant benefit for the stakeholders. Consequently, it has enhanced the consumer satisfaction as well as spread of experiences. However, even with the collaboration of social influence there are some visible short comings potentially appearing in such systems. In fact, the contribution of social influence is still in an evolving state. The reliability of products is such recognized key issue that still appears in exiting social E-commerce systems. In this context we introduce a social influence model combined with a built in social network which further improves the customer reliability and satisfaction on available products. Thus, it can propagate reliable knowledge among community and optimize product recommendation process. The implemented model considers the personal preferences of respective consumers, their social influences in social network and external social influences to the system for the execution. Furthermore, it operates as a multi-agent system. The model has been validated by two sample data sets of consumers and products. As the results, majority have picked products suggested by combining external influences, internal social influences, and personal preferences. Therefore it has concluded that recommendation of products considering above three combinations is more effective.