School of Computing and Informatics (SCAI)

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Browsing School of Computing and Informatics (SCAI) by Author "Etene, Yonah"

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    Cloud Computing Accessibility Evaluation Tool: A Comprehensive Approach to Assessing Accessibility in Primary Schools
    (Iconic Research and Engineering Journals, 2024-01-29) Etene, Yonah
    This paper presents the Cloud Computing Accessibility Evaluation Tool (CCAET), a robust system designed to assess the accessibility of cloud computing in primary schools. The tool incorporates a range of metrics and parameters to comprehensively evaluate the accessibility landscape. This paper outlines the design and components of the CCAET tool, discusses the validation testing process, and highlights its functionalities. The CCAET tool offers a user-friendly interface, enabling users to input metrics, capture parameters and sub-parameters, manage institutions, collect respondent feedback, and generate analysis reports. By promoting a systematic and data-driven approach, the CCAET tool facilitates informed decision-making and identifies areas for improvement in cloud computing accessibility in primary schools.
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    Robotics in Food Manufacturing Industry in the Industry 4.0 Era
    (International Journal of Computer Science and Mobile Computing, 2023-08-30) Barasa, Yonah; Etene, Yonah
    Robotics is used in food manufacturing in multiple processes. Prominent existing applications are: preparation of soil, seeding, water sprinklers, harvest controlling, cutting the harvests, food extractions, processing, packaging, loading/unloading, food warehouse operations, and food retail operations. Robots enhancements in Industry 4.0 framework have enabled cognitive and collaboration capabilities related to dynamics, kinematics, self-diagnostics, and self-control. Robots can identify and change their robotic hands as per process requirement. Robotics in food manufacturing is used to improve food quality and hygiene, increasing quality and its consistency, improving process performance, improving production rate and productivity, production reconfigurability, improving supply chain resilience and responsiveness, improving food traceability, reducing food loss and wastage, and improving workplace safety. Industry 4.0 allows robotic cyber physical systems (RCPS), HMI interfacing with robots through augmented reality thus ensuring remote real time precision monitoring and control of field robots. Robots with attached cameras with machine learning for image visualization analytics can ensure quality assurance and control of food products during all the stages of the food manufacturing logistics. The key drivers for adopting robotics in food manufacturing are cloud manufacturing, Internet of Things (attached with robotic controller cards), virtual reality simulations, augmented reality for HMI controls, additive manufacturing in food processing, integration of Industry 4.0 systems (IoT with blockchains, edge computing, big data analytics, and machine learning), and autonomous automation software. Robotics in food manufacturing using Industry 4.0 capabilities is a positive change. However, there are ethical and financial challenges. Increased usage of robotics can affect employment of food harvesting and manufacturing workers in developed as well as developing economies. Further, economics of using robotics in food manufacturing is not yet justified in developing nations given the high initial costs and prolonged time to break even. Overall, robotics in food manufacturing using Industry 4.0 has many technical and production advantages but ethical and financial viability is an ongoing research domain.
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    Technology for Predictive Health Monitoring of Elderly and Vulnerable Citizens in Kenya using Healthcare 4.0: A Theoretical Review
    (International Journal of Computer Science and Mobile Computing, 2023-08-30) Barasa, Samuel; Etene, Yonah
    The traditional critical healthcare planning is based on periodic routine checks and a reactive strategy of interventions whenever the individuals have entered high risk states (such as heart attacks or strokes). The Healthcare 4.0 design is based on the principle of continuous predictive health monitoring such that the buildup process towards high risk states of individuals can be identified much before their critical levels thus ensuring proactive interventions by the hospitals. Kenya has significant potential to adopt Healthcare 4.0 technology using traditional information and networking components. This research investigates how Healthcare 4.0 can be used in predictive health monitoring of the elderly and vulnerable citizens that individual hospitals can adopt for operational excellence. Desktop review methodology was used. The technical literature review was used to define an operations algorithm. The results suggest that several customizations are needed in the traditional information and networking components to make them fit for predictive health monitoring. The individuals under critical monitoring should not be allowed high mobility as it has a negative effect on monitoring reliability and effectiveness. Healthcare 4.0 adoption in Kenya is feasible. Its operational details need to be defined with several tiers of customized solutions for different patient classes. There are some limitations found in this research, which should be kept in mind while designing and operating Healthcare 4.0 networks in Kenya.