Journal of Information and Technology

The Changing Face of Librarianship: Navigating the Integration of Ai-Powered Virtual Assistants in Reference Services

Petronilla Omete — 2026-03-02

The reference services offered by libraries are being transformed quickly by the introduction of AI-based devices and virtual librarians. The systematic literature review combines academic research conducted between 2015 and 2024 to examine the technologies, applications, advantages, challenges, and professional implications of AI-driven reference services. In accordance with PRISMA, the necessary studies were selected in key academic databases and thematically analyzed. The review demonstrates that AI technologies, especially natural language processing, machine learning, and conversational agents, are becoming more prevalent in library systems to facilitate automated question answering, 247 virtual assistance, customized recommendations, and multilingual services. It has been indicated that AI increases accessibility, scalability, and response efficiency and decreases the number of routine tasks librarians have to complete. Nevertheless, there are still major issues regarding accuracy, algorithmic bias, data privacy, transparency, and governance. The research also points to the changing nature of the librarian as an AI supervisor, trainer, and ethical overseer as a mediator of technology. Instead of substituting professional skill, AI-enhanced reference services can be most effectively used as an addition in a human-AI collaborative framework. The research concludes with recommendations for institutional policy development, professional capacity building, and future empirical research to make AI integration in library reference services responsible, inclusive, and sustainable.

AI-Powered Traffic Management Systems for Kigali’s Urban Mobility

Jonathan Nturo — 2026-04-18

Kigali’s rapid growth has intensified congestion and degraded air quality along major corridors. This study designed and validated an AI-powered traffic management framework that fused multi-source real-time data—CCTV/YOLO counts, IoT detectors, GPS travel times, and near-road air-quality sensors—to optimize signal control in line with the City Development Strategy (CDS) smart-mobility goals. A Long Short-Term Memory (LSTM) model generated reliable short-term flow forecasts (R² = 0.91; RMSE = 8.6 vehicles/interval), which were used to train a Deep Q-Network (DQN) controller to adapt phase splits, cycles, and offsets across complex junctions. Over a six-month evaluation on priority corridors (e.g., CBD–Remera, Nyabugogo–Kacyiru), the AI system reduced average control delay by ~29%, increased intersection throughput by ~36%, and lowered corridor travel time by ~30%. Environmental co-benefits were observed, with fuel use declining by ~26% and near-road CO₂ and PM₂․₅ concentrations decreasing by ~25–30% during peak periods. These gains persisted across rainy conditions and demand variability and were confirmed by paired statistical tests and robustness checks. The results demonstrate deployment-ready potential: corridor-level coordination, incident-aware operating playbooks, and deep bus-priority integration (including headway stabilization) can be operationalized within the city’s control center. We outline a phased scale-up path to network coordination and propose aligning the controller with electric-bus expansion and charging strategies to maximize mobility and air-quality benefits. While coverage and sensor limitations remain, the evidence indicates that data-driven, adaptive control can materially advance Kigali’s goals for a smart, green, and resilient urban transport system.

Cybersecurity & Virtualization

Jonathan Ngugi — 2026-04-18

In today's digital landscape, organizations are increasingly exposed to sophisticated cyber threats that evolve at an alarming rate. The implementation of robust cybersecurity mechanisms has become essential to protect sensitive data and maintain operational integrity in an environment where traditional security measures are no longer sufficient. This paper explores how integrating virtualization technologies and advanced authentication mechanisms can significantly enhance an organization's security posture. Through a case-based methodology, we examine practical implementations and assess the effectiveness of combining virtualization with multi-factor authentication (MFA) in reducing vulnerabilities and mitigating cyber risks. Our findings demonstrate that a strategic fusion of these technologies leads to improved data protection, minimized attack surfaces, and increased user accountability. The research reveals that organizations implementing both technologies simultaneously experience substantially better security outcomes than those deploying either technology in isolation.