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      저자 : Peter Nanpon Gambo (검색결과 1 건)
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      • A Novel Interactive IoT-Based Smart Electricity Power Consumption Management System

        Ibrahim Mohammed Abdullahi,Peter Nanpon Gambo,Martins Ake,Ibrahim Aliyu,Seungmin Oh,Jinsul Kim 한국디지털콘텐츠학회 2021 The Journal of Contents Computing Vol.3 No.2

        Effective and efficient management of electric power is of significant benefit to the end users and a nation’s economy at large. The unnecessary huge bills and feuds that occur very often in developing countries like Nigeria after every billing period are often because of energy wastage and improper use of energy. This challenge hereby presents us with the need to not only create awareness but to also develop systems that allow for efficient and economic use of electric power. The existing meters that attempt to handle this challenge are in some cases analog, or not interactive, expensive and imposing. These systems are said to be imposing because they do not afford the user the right of deciding what he/she wants to spend in a billing period. Even with the emergence of prepaid meters, users are still unable to interact with individual connection points and decide what is consumed there so as to enhance conservation. These problems have already brought to table the need to develop systems that are automated, yet interactive and smart. The solution is an interactive smart electric consumption management system. Thus, this research work is formed around interaction and smartness. A linPrec Scheduling Algorithm is used to predict what each connection point requires in a billing period by interpolating between previous data points on the system. With the Android App, the User is allowed to communicate with every connection point in the apartment and comfortably determine how much they are willing to spend on electricity in a billing period. The http client guarantees data arrival with a worst-case average response time of 2.095s and a best-case average response time of 0.894s. Also, the power measurement had a Mean Absolute Error of 8.89% which implies high accuracy of 91.1%.

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