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Micro-credentials as a pathway to higher learning: the case of an MSc in data science and artificial intelligence degree
(Taylor and Francis, 2026) Dida, Mussa
Micro-credentials (M-Cs) are gaining prominence as credible and flexible options that
support lifelong learning. Increasing acceptance by business for capacity building is
pressuring higher education institutions to recognize and integrate these certifications.
Pioneered by universities like MIT and Deakin, M-Cs must yet be scaled for parity with
traditional degree programs. The primary challenges to integration include non-stand
ardized quality assurance, difficulties in credit mapping, and institutional governance
barriers. This gap is critical in emerging technology fields, including data science and
artificial intelligence, where industry needs outpace university curriculum accreditation,
new staff appointments for course delivery, and degree completion times.
Consequently, industry’s increasing use of M-Cs for skilling staff in new technologies
creates a disconnect between professional and academic recognition. This study inves
tigates this challenge by comparatively analyzing a conventional MSc in Data Science
and Artificial Intelligence and industry-recognized M-Cs. Furthermore, it explores using
M-Cs as a pathway toward a Master of Science degree in Data Science and Artificial
Intelligence. The research compares the skills and competencies provided by M-Cs to
those of the traditional degree program, identifies gaps, and proposes a mechanism
for their formal recognition and integration into an MSc degree in Data Science and
Artificial Intelligence.
Chapter 8 - Architectural design requirements for metaverse-based smart healthcare systems
(Elsevier Ltd., 2026-06-26) Ogundokun, Roseline; Bello, Rotimi-Williams; Owolawi, Pius; Mkoba, Elizabeth; Ogbuju, Emeka; Olugbemi, Adesanjo
The metaverse an immersive, networked virtual environment is poised to transform global healthcare by merging physical and digital realms. This chapter provides a comprehensive literature review and conceptual framework for metaverse-based smart healthcare systems, focusing on both technical architecture and clinical outcomes. We outline key research questions and hypotheses regarding how extended reality, Internet of Things, artificial intelligence, and blockchain can be integrated to enable secure, real-time, patient-centered care in virtual environments. A novel multilayered architecture is proposed, comprising patient and provider domains connected via a virtual hospital metaverse platform with strict cybersecurity and data governance controls. We include mathematical models to formalize data flows and performance requirements, for example, specifying the ultra-low latency needed for realistic telepresence. We then summarize findings from recent studies, including improvements in telemedicine quality, medical training simulations, and remote surgery assistance achieved in prototype metaverse applications. We discuss crucial design requirements (e.g., <20 ms network latency, avatar-based identity management, compliance with health data privacy laws) and address challenges such as protecting patient privacy, maintaining clinical realism, and ensuring equitable access. Technical perspectives (network infrastructure, data security, interoperability) and clinical perspectives (user experience, patient engagement, health outcomes) are examined in depth. The chapter concludes with practical implications for healthcare industries worldwide, including guidance on gradual adoption, workforce training, and regulatory alignment, and outlines future research directions toward achieving safe and adequate healthcare in the metaverse.
Development of an IoT-Based Smart Irrigation System for Efficient Water Management in Uasin Gishu County
(Springer Nature, 2026-04-01) Bundotich, Winny; Sinde, Ramadhani; Tarus, John; Maiyo, Titus
Food scarcity has recently increased due to climate change, population growth, and decreased land for farming. To mitigate this, measures like encouraging irrigation farming have been implemented, but irrigation faces water scarcity challenges. Efforts to improve water use efficiency include scheduled irrigation system technology, mostly targeting greenhouses and neglecting open-field irrigation. To address these issues, this project developed an IoT-based smart irrigation system for efficient water management. Using an ESP32 microcontroller, sensors monitor critical soil parameters, and the OpenWeather API fetches rainfall predictions. The system automatically controls irrigation valves based on soil moisture levels and rainfall predictions, providing remote valve control and farm information visualization via the Thingsboard cloud platform and mobile app. Data was collected using mixed methods, including questionnaires and focus group discussions with sixteen respondents, selected through purposive sampling. Agile software development methodology, specifically extreme programming, was used to develop the system. Validation involved demonstrations to twenty-seven people, who then interacted with the system and provided feedback through a questionnaire. Respondents agreed that the system met their needs satisfactorily. This system contributes to precise water input and can be advanced to monitor and evaluate irrigated farms in Uasin Gishu County and beyond.
Development of an IoT-Based Smart Irrigation System for Efficient Water Management in Uasin Gishu County
(Springer Nature, 2026-04-01) Bundotich, Winny; Sinde, Ramadhani; Tarus, John; Maiyo, Titus
Food scarcity has recently increased due to climate change, population growth, and decreased land for farming. To mitigate this, measures like encouraging irrigation farming have been implemented, but irrigation faces water scarcity challenges. Efforts to improve water use efficiency include scheduled irrigation system technology, mostly targeting greenhouses and neglecting open-field irrigation. To address these issues, this project developed an IoT-based smart irrigation system for efficient water management. Using an ESP32 microcontroller, sensors monitor critical soil parameters, and the OpenWeather API fetches rainfall predictions. The system automatically controls irrigation valves based on soil moisture levels and rainfall predictions, providing remote valve control and farm information visualization via the Thingsboard cloud platform and mobile app. Data was collected using mixed methods, including questionnaires and focus group discussions with sixteen respondents, selected through purposive sampling. Agile software development methodology, specifically extreme programming, was used to develop the system. Validation involved demonstrations to twenty-seven people, who then interacted with the system and provided feedback through a questionnaire. Respondents agreed that the system met their needs satisfactorily. This system contributes to precise water input and can be advanced to monitor and evaluate irrigated farms in Uasin Gishu County and beyond.
A Smart Contract Trust Security Framework for Regulatory Inspection Systems in Nuclear Regulatory
(Springer Nature, 2026-04-01) Khwatenge, Elvira; Ally, Mussa; Lyakurwa, Geminpeter; Mbelwa, Hope
Blockchain technology has emerged as a transformative force across various sectors, including regulatory inspection systems. Blockchain integration offers solutions to enhance trust and transparency in nuclear regulatory environments, where data security and integrity are paramount. Our framework enhances the security, efficiency, data integrity, and transparency of regulatory inspections in the nuclear regulatory domain by leveraging Hyperledger Fabric, a permissioned blockchain platform, and smart contracts. The proposed system utilizes a Proof of Authority (PoA) consensus protocol to create a decentralized, immutable ledger for inspection data. The system features include automated workflow management, role-based access control, real-time tracking of inspection status, and an immutable audit trail. We use the STRIDE threat modeling methodology to perform security with mitigation strategies for identified risks. The performance evaluation compares the blockchain-based system to traditional database-driven approaches, demonstrating improvements in report generation time and system availability, despite some trade-offs in transaction throughput and latency. The framework's potential to streamline inspection processes, reduce manual errors, and enhance regulatory compliance is illustrated using a simulated case study. While acknowledging limitations and areas for future work, this research contributes to the evolving landscape of blockchain applications in nuclear safety and regulatory environments.