Browsing by Author "Perera, M.S.H."

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Modeling and Forecasting the Usage of Cellular and Landline Phones in Sri Lanka
(International Conference on Applied Social Statistics (ICASS) - 2019, Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya, Sri Lanka, 2019) Karunarathne, A.W.S.P.; Perera, M.S.H.; Liyanage, U.P.
Cellular and landline phones are at the forefront of telecommunication. There are two major categories of phones namely cellular phones and landline phones. Landline phones can be classified into another two sub categories as fixed wire landline phone and fixed wireless landline phones. In this study, the total usage of those two categories have considered as the landline phone usage. Since, the mobile segment has instantly developed in Sri Lanka, there can be seen a significant decline in landline phones market.
Modelling and Forecasting the Usage of Cellular and Landline Phones in Sri Lanka: Univariate Time Series Approach
(International Journal of Academic Research, 2020) Karunarathner, A.W.S.P.; Perera, M.S.H.; Liyanage, U.P.
Phones have become a mandatory commodity in human life. Nowadays, there is a very strong increase in the cellular phone market, so we tend to forget landline phone services. According to statistics, cellular phones and landline phones usage up to December 2018 is 32,528,104 and 2,484, 616 respectively. That is, the teledensity (per 100 inhabitants) is 150 for cellular phones and 11.5 for landline phones. Due to the increment of the cellular phones and decrement of the landline phones, it is vitally important to study their behaviour. Therefore, the objective of this paper is to model and forecast the usage of cellular and landline phones in Sri Lanka. The model was developed using 80% of the data and validated with 20%. The usage was modelled with Autoregressive Integrated Moving Average (ARIMA) technique. Several models were fitted and based on the lowest Akaike’s Information Criteria (AIC), ARIMA (1,2,1) and ARIMA (2,2,1) were identified as the best-fitted models with forecasting accuracy measured by Mean Absolute Percentage Error (MAPE) values 1.403 and 0.976 for cellular and landline phones usage respectively, concluding that two ARIMA models have a strong potential for forecasting the usage of cellular and landline phones. This model would be important to those who are with the telecoms market to achieve their business goals.
A wireless sensor network based autonomous logistic trolley system for factory automation
(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Perera, M.S.H.; Prasadini, M.M.N.; Karunarathne, C.N.; Chathurangi, M.; Samarasinghe, P.; Jinasena, T.M.K.K.
This paper presents the low cost autonomous logistic trolley for factory automation. Automation can be defined as the technology by which a process or procedure is performed without human assistance. Factory automation has automated the factory manufacturing process without human interaction. It will increase the efficiency of the manufacturing process, make the process highly accurate and because of less man power it will increase the revenue margin of the factory. The system primarily consists of a Arduino Uno board, ultrasound sensors, infrared proximity sensors, Bluetooth modules, DC motors, and Servo motors. This system mainly includes obstacle detection, line tracking, Bluetooth request transferring technologies and motion control technologies. This trolley is called up by a production desk of the factory if materials are needed, by sending a request. Trolley automatically deliveres the material to that exact production desk using its infrared sensors that are placed at both left and right sides of the vehicle. This can be used to identify each production line. This proposed autonomous trolley was experimented in different methods. It showed very accurate and successful results. This kind of autonomous trolley provides a wide range of benefits to a manufacturing process in a factory. This autonomous logistic trolley is low cost, less complicated and will increase efficiency of the manufacturing process of a factory.