Architecture and Signaling Design for Real-Time Audio/Video Tutoring Services

This article explores the architectural design and signaling mechanisms behind a real-time audio/video tutoring service built for smart desk lamps, detailing the three-layer RTC middleware, classroom abstraction, interactive signaling workflows, and scalable extensions from one-on-one sessions to large virtual classrooms.

ByteDance Dali Intelligent Technology Team
ByteDance Dali Intelligent Technology Team
ByteDance Dali Intelligent Technology Team
Architecture and Signaling Design for Real-Time Audio/Video Tutoring Services

This article introduces the technical architecture and business implementation of an online homework tutoring service powered by ByteDance's Dali Smart desk lamp. The service addresses the challenges of offline after-school tutoring by leveraging smart hardware with dual cameras to replicate in-person tutoring experiences online, offering advantages in cost, scalability, flexibility, and safety.

The system architecture is structured into three core layers. The foundational RTC middleware integrates third-party and self-developed real-time communication providers, unifying their APIs and delivering platform-specific SDKs. Above it, the classroom middleware abstracts RTC rooms, manages teacher-student roles, and integrates teaching tools like whiteboards via signaling. The top layer handles business-specific implementations for teacher, student, and parent clients, alongside a comprehensive management backend.

Key operational scenarios revolve around real-time audio/video interactions. Teachers can initiate one-on-one tutoring sessions for homework review or behavioral correction, while students can raise their hands to request help. The signaling system is meticulously designed across four dimensions: business workflows, device control, classroom state management, and RTC stream control. Notable features include remote photo capture for high-resolution homework viewing, dynamic screen switching between whiteboard and video feeds, and camera toggling, all synchronized through a robust state machine that manages call initiation, acceptance, rejection, and timeouts.

Beyond basic one-on-one tutoring, the platform has been extended to support diverse educational models. These include fragmented-time real-time Q&A, small-group sessions accommodating up to six students, and large-scale virtual study rooms or classes supporting up to two hundred participants. The architecture's flexibility also enables SaaS deployment for offline tutoring institutions, demonstrating a scalable approach to modernizing educational technology.

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System Architecturereal-time communicationEdTechSignaling DesignVideo Tutoring
ByteDance Dali Intelligent Technology Team
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ByteDance Dali Intelligent Technology Team

Technical practice sharing from the ByteDance Dali Intelligent Technology Team

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