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All Journal TechComp Innovations: Journal of Computer Science and Technology Societal Serve: Journal of Community Engagement and Services Edu Spectrum: Journal of Multidimensional Education
Hasanov, Tofig
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Humanities Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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Federated Intelligence Architectures for Secure, Data-Driven Innovation Across AI, IoT, and Cloud Ecosystems Saidala, Ravi Kumar; Iftikhar, Umna; Hasanov, Tofig; Mammadli, Vüqar Ahmad
TechComp Innovations: Journal of Computer Science and Technology Vol. 2 No. 2 (2025): TechComp Innovations: Journal of Computer Science and Technology
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/techcompinnovations.v2i2.124

Abstract

This study examines the emerging paradigm of federated intelligence architectures as a secure, privacy-preserving, and scalable foundation for data-driven innovation across AI, IoT, and cloud ecosystems. With billions of interconnected devices generating massive heterogeneous data, traditional centralized machine-learning models face critical limitations, including privacy risks, regulatory constraints, latency, and single points of failure. Through a qualitative content-analysis approach, this paper synthesizes contemporary research on federated learning, blockchain integration, zero-trust governance, and edge intelligence to formulate a comprehensive understanding of distributed AI infrastructures. The findings highlight that federated learning enables collaborative model training without exposing raw data, significantly enhancing privacy, security, and compliance. Moreover, combining blockchain with federated learning strengthens auditability, model integrity, and trust, while zero-trust principles provide continuous verification and adaptive security enforcement across devices. Edge-AI integration further reduces latency and bandwidth consumption, enabling real-time analytics in resource-constrained IoT environments. Collectively, these elements contribute to the formation of cognitive ecosystems capable of autonomous, interoperable, and context-aware operations. The study underscores the transformative potential of federated intelligence while identifying critical gaps that inform future research trajectories.
Digital Innovation Strengthening Community-Centered Health Services through Technology Integration in Romanian Social Welfare Contexts Mansurzada, Asma Elmar; Azizli, Aytan; Hasanov, Tofig
SocietalServe: Journal of Community Engagement and Services Vol 2 No 2 (2025): Societal Serve: Journal of Community Engagement and Services
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/societalserve.v2i2.134

Abstract

This community engagement program aims to strengthen community-centered health services in Romania by integrating digital innovations into existing social welfare systems. The initiative responds to persistent challenges in accessibility, service coordination, and information flow between local health providers and underserved populations. Through a structured intervention—including digital literacy workshops, development of simple data-collection tools, and collaborative planning sessions with community health workers—the program seeks to enhance local capacity for technology-supported service delivery. A mixed set of participatory and data-driven strategies was employed to ensure that technological solutions align with community needs and institutional capacities. Results indicate significant improvements in digital readiness among participants, increased accuracy of health-service reporting, and stronger collaboration between social welfare actors and community members. Feedback collected from participants highlights a high level of satisfaction with the practicality and relevance of the training sessions. Overall, the program demonstrates that integrating accessible technological innovations into community-based health systems can contribute to more responsive, efficient, and inclusive social welfare structures in Romania. The findings further underscore the importance of continued investment in digital competencies and collaborative governance to support sustainable health-service improvements in socioeconomically diverse contexts.
Data-Informed Professional Development for Strengthening Teacher Assessment Literacy in the Digital Era Blbas, Hazhar Talaat Abubaker; Mansurzada, Asma Elmar; Hasanov, Tofig
Edu Spectrum: Journal of Multidimensional Education Vol. 2 No. 2 (2025): Edu Spectrum: Journal of Multidimensional Education
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/eduspectrum.v2i2.129

Abstract

This study examines how data-informed professional development can strengthen teacher assessment literacy amid the growing demands of the digital era. Using a qualitative design, the research combines library investigation and content analysis of scholarly literature published over the past decade related to digital assessment, teacher data literacy, and technology-supported instructional decision-making. Findings reveal that digital transformation in education requires teachers to master data interpretation skills, utilize technology-enhanced assessment tools, and develop ethical awareness regarding privacy and algorithmic bias. However, many teachers continue to face competency gaps, inadequate professional development, and challenges in integrating digital assessment practices effectively. The study highlights that meaningful professional development must be continuous, collaborative, evidence-based, and incorporate data literacy, AI literacy, and reflective pedagogical practice. Such an approach equips teachers to interpret complex data, design valid digital assessments, and make ethically responsible, evidence-driven instructional decisions. This research provides conceptual clarity and a foundation for designing comprehensive professional development frameworks aimed at enhancing teacher assessment literacy within rapidly evolving digital learning environments.
Co-Authors Azizli, Aytan Blbas, Hazhar Talaat Abubaker Iftikhar, Umna Mammadli, Vüqar Ahmad Mansurzada, Asma Elmar Saidala, Ravi Kumar