Computer-Aided Learning Management Suite (CALMS): An Offline-First, TV White SpaceEnabled Architecture for Equitable Education in Rural Zimbabwe

The Computer-Aided Learning Management Suite (CALMS) offers a transformative solution to educational disparities in low-connectivity regions by seamlessly integrating an e-learning hub, results management analytics, and a Virtual AI Classroom Board into a standalone ecosystem. Built upon Television White Spaces (TVWS) technology, CALMS delivers broadband-grade connectivity whilst maintaining strict offline-first functionality. This ensures data-driven performance tracking and real-time hardware integration even in the absence of upstream internet access. The system is underpinned by a custom embedded edge inference runtime -comprising a deterministic stack of Python-based libraries, including face_recognition, OpenCV2, and MediaPipe - which orchestrates biometric verification and gesture recognition entirely at the network edge. To circumvent the limitations of traditional web infrastructure, the architecture introduces CALMS-NET, a geographically structured routing protocol. By replacing the conventional Domain Name System (DNS) with the CALMS Name System (CNS), which derives a private IPv6 namespace from Zimbabwe’s telephone area codes, the system enables resilient local service discovery and peer-to-peer mesh networking among rural school clusters. This paper presents the design, architecture, and implementation strategy of CALMS, contextualised within the framework of the United Nations Sustainable Development Goal 4: Quality Education.