Faculty of Computing

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Now showing 1 - 6 of 6
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    Solution to Measure Employee Productivity with Employee Emotion Detection
    (IEEE, 2022-12-09) De Silva, T.R.S.; Dayananda, K.Y.; Galagama Arachchi, R.C.; Amerasekara, M.K.S.B.; Silva, S; Gamage, N
    Health and safety of workers has become a top priority in modern businesses. The reason is that it will have an impact on both individual and team output. In the last few decades, automatic facial expression analysis using machine learning has emerged as a promising and bustling field of study. In this study, the system primarily evaluates the efficiency of workers and, through the detection of their emotional states, determines their levels of motivation. The task completion rate of employees is measured by the system in the first component, and the system predicts the level of satisfaction that the employees will have. In place of linear regression, this component makes use of random forest regression, which boasts a higher degree of precision than its counterpart. The performance of workers on their tasks will be evaluated periodically, about once every fifteen minutes, and the results will be shown on a dashboard. The system will pick up on the emotions of the staff members throughout the second phase of the process. These characteristics will be used to assess the level of motivation inside the organization, with the end goal of increasing overall productivity. The accuracy of this emotion detection will also be checked periodically, namely once every fifteen minutes. The following part of the process monitors the use of the PC and calculates the level of productivity. It will be possible to get an increase in productivity if one monitors and keeps track of the application usage of each employee. The final components monitor the websites that employees visit and how they use the network. This component makes it easier to generate reports based on the utilization of the internet and the network, as well as information on performance and reports that summarize website traffic. When it is fully operational as an integrated system, most businesses will rely on this system as their primary driver of success.
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    Secure Smart Parking Solution Using Image Processing and Machine Learning
    (IEEE, 2022-07-18) Balasuriya, A. I. P; Dilitha, A.G. A. D; Perera, P. A. M. M; Jayaweera, D.K. S; Swarnakantha, N. H. P. R. S; Rajapaksha, U. U. S
    With the IoT connecting the world, finding parking lots is much easier with smart parking solutions. Some of the parking areas in the world use at least some kind of smart parking solution these days. There are existing and broader solutions when it comes to parking a vehicle. So, in this project, we are mainly focusing on developing these existing solutions a step further. I hear we are mainly focusing on a solution that increases the effectiveness of the management processes in the currently existing solutions and developing a relevant and integrated security solution. The project will include a refined prediction system that can predict the outcomes of some of the main processes that are done inside a parking area so that smart parking management and be done much more smoothly and effectively. Prediction systems are designed on the idea of getting possible security issues, vehicle types on peak hours as an outcome. And even in the aspect of security rather than a separate system, there is an integrated one coming with this project that has improved functionality with regards to a parking area. The main possible security threats that happen in a parking area are being identified by us and implemented separate functionalities on detecting them. Furthermore, the project includes a decision-making system that can deduce and take the decision on slot management in a parking area so it can work effectively and with minimum human interaction.
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    Remotify: The Emergency Remote Learning Solution using Learning Analytics
    (IEEE, 2022-07-18) Amarasinghe, S. N.; Thalakumbura, T. M. D. D; Wijewardena, M. D. N. K.; Perera, D. H.; Manathunga, K; Senaweera, O
    Current pandemic situation has manipulated people to adapt to a new normal forcefully and due to the same reason education system is also evolving but the actual question is how productive the new methodologies utilized are. E-learning is not a novel concept but is becoming a necessity and the proposed platform could be identified as a direct response to the current emergency. This can also be known as an "ERT" situation; a shift of instructional delivery to an alternate delivery method in response to a crisis situation. The main intention in these situations is not to recreate a robust educational system but to provide access to institutions in a manner that is easy to set up and is dependable during an emergency while outperforming both E-learning & traditional classroom methods. To provide a solution to overcome barriers faced in a pandemic situation in a virtual classroom, the implemented system is encapsulated with a dashboard centralizing facts gathered from audio & video analyzing components which are analyzed against student performance utilizing personalized assessing techniques to deliver learning analytics.
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    Supply and Demand Planning of Electricity Power: A Comprehensive Solution
    (IEEE, 2019-12-06) Perera, S; Dissanayake, S; Fernando, D; De Silva, S; Rankothge, W
    Electrical energy is one of the fastest growing energy demands in the world. Uncertainty in supplying the demand can threaten the social economic aspects of a country. The biggest driver of electrical demand is weather. Climatic changes not only affect the demand but also renewable energy supply. Wind and Solar are two alternative energy sources with less pollution. We have proposed a platform which helps energy providers, energy traders with services related to electricity supply and demand planning, with following modules. (1) Forecasting electricity consumption patterns (2) Forecasting wind power generation (3) Optimizing Load Shedding. Our platform has been implemented using statistical and machine learning techniques: Multi-Linear Regression for consumption prediction, Random forest regression for wind power forecast, and genetic algorithm to optimize load shedding. Our results show that, using our proposed module, we can minimize the imbalance between the supply and demand of electricity by predicting the consumption patterns of consumers, predicting the wind power generation and by selecting the best feeder to be selected for load shedding under given constraints.
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    A solution for the elephant-human conflict
    (IEEE, 2014-04-04) Gamage, A
    The Human-Elephant conflict is a serious problem that has existed for decades in Sri Lanka. Although the Department of Wildlife Conservation has implemented several strategies such as electric fencing, translocation and GPS/VHF collars, approximately 150 elephants and 50 humans are killed every year while a lot more are affected. The solution developed through this research incorporates a server and a tracking device. The latter, fixed inside each elephants' collar, consumes an ultra-low idle power of 4.7?W and intelligently decides to transmit location information to the remote server via GSM. This paper discusses how the latest technology has been utilized to dynamically bias harvesting sources to extract as low as 10?W and also how such harvesting methods can be implemented inside a collar. The device built is also able to securely accept over-the-air configurations sent by the Department of Wildlife Conservation aiding remote configuration. The proposed tracker unit, once attached, is able to transmit 12 or more locations a day and with a daily solar generation of 271.8mWh efficiently harvested to a 5000mAh LiPo battery. The device is expected to operate for more than 5 years without any human interaction. The main server accepts and decrypts the location information sent from the tracker device whilst maintaining records. It also operates as a web server. Therefore, a privileged user may securely log in to view all elephants in a map. Moreover, it generates alerts when an elephant intrudes into a human territory and is implemented by adding extra hardware to a low cost embedded Linux computer.
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    “Smart Assistant”: A solution to facilitate vision impaired individuals
    (IEEE, 2018-10-02) Sankalpani, P; Wijesinghe, I; Jeewani, I; Anooj, R; Mahadikaara, M. D. J. T. H; Jayakody, A
    This paper presents a solution for vision impaired people to navigate through an unfamiliar indoor environment with the help of their smart phone. Although there are some solutions which address this scenario, they do have some problems such as lack of accuracy and inability to apply for real-life situations. So, the solution presented here avoids those drawbacks and apply more realistic and improved ways of navigating techniques. This prototype demonstrates how to localize and get map details as required to navigate indoor buildings with voice support. The end result of this research is to increase the accuracy and the easiness of this system compared to the existing supportive systems.