The increasing integration of Artificial Intelligence (AI) in education (AIEd) and its dependence on contemporary communication infrastructures (5G/6G, the Internet of Things (IoT), and Multi-Access Edge Computing (MEC)) has prompted a surge of research into applications, infrastructural dependencies, and deployment constraints. This is giving rise to a new paradigm termed AI-Enabled Telecommunication-Based Education (AITE). This review synthesises the recent literature (2 022–2025) to examine how telecommunications and AI technologies converge to enhance educational ecosystems through adaptive learning systems, intelligent tutoring systems, AI-driven assessment, and administration.The findings reveal that low-latency, high-bandwidth connectivity, combined with edgedeployed analytics, enables real-time personalisation, continuous feedback, and scalable learning models that extend beyond traditional classrooms. In addition, persistent critical challenges are also reported, including issues with ethical governance, data privacy, algorithmic fairness, and uneven access to digital infrastructure, all affecting equitable adoption. By linking pedagogical transformation with telecom performance metrics—namely, latency, Quality of Service (QoS), and device interconnectivity—this work outlines a unified crosslayer framework for AITE. This review concludes by identifying future research avenues in ethical AI deployment, resilient architectures, and inclusive policy design to ensure transparent, secure, and human-centred educational transformation.

Ensuring the confidentiality, integrity and authenticity of transmitted data for single- and multi-agent systems is becoming crucial to protect these systems against potential threats. This is precisely the focus of this work that introduces a novel approach for securing communications between unmanned aerial vehicles (UAVs). In particular, to safeguard the data against attacks in UAV networks, implemented for military-grade or critical infrastructure operation scenarios, different security techniques are combined, including the employment of a chaotic synchronization-based communications architecture. The proposed chaotic-synchronized, secure communications system (UAV-CSCS) is applied onboard a UAV and comprised of three layers, namely a VPN server (initial security layer), a custom ROS-based framework (data collection and distribution layer), and a lightweight chaotic communications module (secondary security layer). UAV-CSCS’s main component is a transmitter-receiver communication architecture based on chaotic synchronization that successfully encodes and decodes information over a chaotic signal, enabling secure information exchange between agents. To validate the effectiveness of the proposed system, a prototype is designed, developed, and thoroughly tested in real-world multi-UAV experiments. The results demonstrate secure, real-time communication with low-power consumption and minimal resource allocation (in terms of CPU and RAM), validating the system’s efficiency and applicability.