Field survey of smart metering implementation using a simple random method: A case study of New Juaben Municipality in Ghana

Banuenumah, W.; Sekyere, François; Dotche, K. A.

doi:10.1109/powerafrica.2017.7991250

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…This SCADA system has limited reach, covering only high-voltage transmission lines and some portion of the medium-voltage distribution network (Nunoo & Ofei, 2010). To improve monitoring, ECG has recently deployed some smart meters, but economic and social challenges raise barriers to achieving broad smart meter coverage in the short term (Acakpovi et al, 2019;Millennium Development Authority, 2014;Banuenumah et al, 2017). ECG recently completed a much larger effort to upgrade their prepaid meters; however, many of the prepaid meters do not regularly communicate power quality measurements back to the utility (Quayson-Dadzie, 2012;Electricity Company of Ghana., 2019).…”

Section: Saidi =mentioning

confidence: 99%

Measuring Grid Reliability in Ghana

Klugman

Adkins

Berkouwer

et al. 2022

Introduction to Development Engineering

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What challenges arise when deploying a novel technology at increasing scale? This case study details our experience developing and deploying technologies to monitor power outages and voltage fluctuations at high temporal and geographic frequency. After a small initial pilot, our deployment grew over time and eventually exceeded 450 sensors and 3500 mobile app downloads with households and firms across Accra, Ghana. Our first lesson is that ad hoc solutions to deployment challenges may not scale, as larger scales bring unique challenges requiring unique and progressively more complex solutions. Second, challenges that arise with scale span distinct domains – not only technological but also cultural, organizational, and operational. Finally, we stress the importance of adaptability of operational structure, and of frequently updating operational strategy based on new learnings.

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Section: Saidi =mentioning

confidence: 99%

Measuring Grid Reliability in Ghana

Klugman

Adkins

Berkouwer

et al. 2022

Introduction to Development Engineering

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“…A partir de diversos testes preliminares, foi definido empiricamente que a coleta do rastreamento do mouse e do olhar seria feita a cada 100 ms através de uma webcam com resolução em 1280x720 px, com uma margem de erro de predição de 100 pixels, utilizando monitor com resolução em 1920x1080 px. Para isso, foram selecionados dez participantes, com o Método de Amostragem Aleatória [28]. Todos os usuários eram estudantes do curso de Engenharia da Computação com conhecimento sobre acesso a websites diversos.…”

Section: Estudo De Casounclassified

Metodologia Baseada em Agrupamento de Rastreamento de Mouse e Olhar para Melhoria da Experiência do Usuário

Aviz¹,

Souza²,

Seruffo³

et al. 2020

Anais Do 14. Congresso Brasileiro De Inteligência Computacional

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Com a expansão de sistemas em plataforma web, tornou-se crítico o desenvolvimento de novas ferramentas e metodologias de avaliação da experiência do usuário (UX) para tornar tais sistemas mais intuitivos. Técnicas como rastreamento de mouse e rastreamento de olhos geram dados de interação que podem ser usados para melhorar o layout e a usabilidade destes sistemas. Além disso, recentemente aárea de desenvolvimento de sistemas passou a adotar Interfaces de Usuários Adaptativas (IUA), visando aprimorar em tempo real a UX. Nesse contexto, este artigo propõe uma metodologia para capturar e analisar os dados de comportamento de um grupo de usuários e sugerir a adaptação de um sistema web. Nesta análise foi utilizado o método de clusterização k-means. Os resultados sugerem que a metodologia pode auxiliar em mudanças automatizadas para melhoria da UX. Keywords-avaliação de experiência do usuário; rastreamento do mouse; rastreamento do olhar; interface de usuários adaptativas; agrupamento.

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“…Users were selected based on the random sampling method [32]. This method considers a subgroup of individuals (a sample) chosen from a larger group (a population).…”

Section: Case Studymentioning

confidence: 99%

User Experience Evaluation Using Mouse Tracking and Artificial Intelligence

et al. 2019

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Business platform models frequently require continuous adaptation and agility to allow new experiences to be created and delivered to customers. To understand user behavior in online systems, researchers have taken advantage of a combination of traditional and recently developed analysis techniques. Earlier studies have shown that user behavior monitoring data, as obtained by mouse tracking, can be utilized to improve user experience (UX). Many mouse-tracking solutions exist; however, the vast majority is proprietary, and open-source packages do not provide the resources and data needed to support UX research. Thus, this paper presents: 1) the development of an interaction monitoring application titled Artificial Intelligence and Mouse Tracking-based User eXperience Tool (AIMT-UXT); 2) the validation of the tool in a case study conducted on the Website of the Brazilian Federal Revenue Service (BFR); 3) the definition of a new relationship pattern of variables that determine user behavior; 4) the construction of a fuzzy inference system for measuring user performance using the defined variables and the data captured in the case study; and 5) the application of a clustering algorithm to complement the analysis. A comparison of the results of the applied quantitative methodologies indicates that the developed framework was able to infer UX scores similar to those reported by users in questionnaires.

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Field survey of smart metering implementation using a simple random method: A case study of New Juaben Municipality in Ghana

Cited by 8 publications

References 3 publications

Measuring Grid Reliability in Ghana

Measuring Grid Reliability in Ghana

Metodologia Baseada em Agrupamento de Rastreamento de Mouse e Olhar para Melhoria da Experiência do Usuário

User Experience Evaluation Using Mouse Tracking and Artificial Intelligence

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