Project Cynosura: Difference between revisions
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Latest revision as of 23:37, 10 August 2026
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Template:Displaytitle:Project Cynosura: Mobile Dual-Language Exchange Architecture
Project Cynosura is a self-hosted, edge-optimized educational framework and hardware/software pipeline designed for structured 1-hour bidirectional language exchange over video calls.
The system is engineered specifically for asymmetrical language proficiency levels (Beginner Vietnamese / Advanced Conversational English) and constrained over-the-road (OTR) mobile operating environments using VR edge display nodes, self-hosted sync engines, and custom MediaWiki tracking templates.
0. Phase 0: Minimal Viable Setup (KISS Protocol)
Before scaling to cloud-hosted containers and spatial VR setups, initial calls use off-the-shelf mobile redundancy:
- Video Stream: Google Meet / FaceTime over mobile hotspot.
- Asymmetrical Closed Captions:
- Student (Isidore): Runs Google Translate (VN -> EN) locally on iPhone.
- Instructor (Linh): Runs Google Translate (EN -> VN) locally on her device.
- Live Shared Workspace: Single shared Google Doc for real-time vocabulary and idiom typing.
- Flashcard Logging: Manual entry into Anki / AnkiWeb during post-call review.
1. Core Principles & Session Framing
To eliminate "language bleeding" (where the dominant shared language takes over conversation), calls operate under strict time-boxing:
| Block | Time | Focus Area | Target Output |
|---|---|---|---|
| Block 1: Vietnamese | 30 Mins | Tone contour accuracy, S-V-O mechanics, pitch shadow drills | Master 5 survival phrases & 6 tone contours |
| Block 2: English | 30 Mins | Idiom deconstruction, register/context selection, nuance | Practice 3 target idioms across 3 conversational registers |
30-Minute Internal Lifecycle
- 00:00â05:00 â Review & Anki deck audit (3â5 past items).
- 05:00â20:00 â Core topic output & pitch contour / idiom mapping.
- 20:00â30:00 â Guided roleplay with real-time, asynchronous wiki logging.
2. Technical Architecture & Stack
The system decouples compute heavy-lifting from mobile endpoints by hosting the desktop workspace on cloud infrastructure while leveraging a Meta Quest 2 inside the cab for multi-monitor spatial rendering.
+-----------------------------------------------------------------------+
| TRUCK CAB EDGE |
| |
| [ iPhone ] --------(5G Hotspot / USB Gateway) |
| | | |
| [ Quest 2 ] <---(Wi-Fi / Immersed)---> [ Raspberry Pi Node ] |
| (VR Headset) (Local Offline Buffer/Router) |
+-----------------------------------------------------------------------+
|
(WireGuard Tunnel)
v
+-----------------------------------------------------------------------+
| DIGITALOCEAN CLOUD CORE |
| |
| +------------------------+ +---------------------------------+ |
| | MediaWiki Box | | Kasm / XRDP Web Desktop | |
| | (Curriculum Engine + | | (Hosts Whiteboard, Video Call, | |
| | Anki Sync Server) | | & Shared Editing Workspace) | |
| +------------------------+ +---------------------------------+ |
+-----------------------------------------------------------------------+
Software Stack
- Knowledge Base & Curriculum Engine: Self-hosted MediaWiki.
- Flashcard Synchronization: Containerized
anki-sync-serverDocker instance running alongside MediaWiki. - Remote Workspace Display: DigitalOcean Droplet running Kasm Web / XFCE streaming to Immersed VR on the Quest 2.
- Interactive Whiteboard: Excalidraw / Mermaid extension embedded into wiki pages.
Hardware Stack
- Primary Node: Meta Quest 2 Headset (virtual multi-display spatial terminal).
- Gateway Node: iPhone (5G tethering & backup client).
- Auxiliary Node (Optional): Raspberry Pi 4/5 + OLED Touchscreen + Rii i8+ Handheld Keyboard running
kiwix-serve/ local MediaWiki offline buffer. - Audio: Closed-back headset microphone directly into Quest 2 for cab ambient noise cancellation.
3. Curriculum Structure & Namespaces
The system divides tracking into two dedicated namespaces on this wiki:
Vietnamese:Focuses on tone mapping ($Ngang, Huyá»n, Há»i, Ngã, Sắc, Nặng$), Southern vs. Northern dialect markers, and functional vocabulary.English:Focuses on idiom deconstruction matrices, tone of voice, formal vs. casual context, and American cultural idioms.
Structural Template: `Template:LessonBlock`
All individual lesson entries are generated using the following standard template call:
{{LessonBlock
| Session_ID = 001
| Date = {{CURRENTYEAR}}-{{CURRENTMONTH}}-{{CURRENTDAY2}}
| Instructor = Linh
| Student = Isidore
| Target_Language = Vietnamese
| Focus_Tones = Hoi / Nga
| Idioms_Reviewed = Hit the nail on the head; Under the weather
| Audio_Log = File:VN_Session_001_Tones.ogg
| Notes = Real-time corrections logged here
}}
4. OTR Operating Procedure
- Pre-Call (T-5 min): Park vehicle, establish 5G hotspot. Boot Quest 2, launch Immersed, connect to DigitalOcean desktop droplet.
- Display Layout (Virtual Space):
- Screen 1 (Left): Video Conference (Google Meet / Zoom).
- Screen 2 (Center): MediaWiki
LessonBlockworkspace for real-time async note logging. - Screen 3 (Right): Shared Anki Web / Drawing canvas for tone contours.
- Post-Call (T+5 min): Export audio clips recorded during the session, drop onto MediaWiki, and run Anki deck sync.
5. System Roadmap
- [x] Program conceptualization & schedule design.
- [ ] Spin up
anki-sync-serverDocker container on DigitalOcean. - [ ] Deploy
Template:LessonBlockand namespaces on MediaWiki. - [ ] Test Immersed latency over cellular hotspot in cab environment.
- [ ] (Optional) Flash Raspberry Pi image with offline local buffer mirror.
```
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