Severe yellowing on screen
Touch , camera , everything else working perfectly
Bootloader unlocked (Currently Using Infinity X)
Asking ₹8000(negotiable)
Bill box available
Price :0000 (Highest offer in the comments will be accepted.🥲)
Condition: Fully functional and working perfectly.
8GB RAM + 128GB storage
Cosmetic issue: Back panel has cracks, clearly visible in the photos. This does not affect the phone's functionality.
Price: ₹10,000 (negotiable)
Can ship
It has esp32 8684(c2)
Made a custom WAD launcher for my ESP32 Doom Watch.
It scans the SD card for .wad files, detects IWADs/PWADs automatically, lets you choose, and launches directly from the watch. It also creates separate save folders for each WAD and includes settings for brightness, volume, and control sensitivity.
Basically, I got tired of reflashing the watch every time I wanted to play a different version of DOOM.
Now I can just drop WADs onto the SD card and launch them from the watch itself.
Github for doom launcher : https://github.com/Tsixom0/DOOM-Launcher-for-Waveshare-ESP32-S3-2.06-Touch-Amoled
Github for wad picker : https://github.com/Tsixom0/WAD-file-picker-for-waveshare-esp32-s3-2.06-amoled-touch
Next goal: gameboy or nes emulation for this watch
Made a custom WAD launcher for my ESP32 Doom Watch.
It scans the SD card for .wad files, detects IWADs/PWADs automatically, lets you choose, and launches directly from the watch. It also creates separate save folders for each WAD and includes settings for brightness, volume, and control sensitivity.
Basically, I got tired of reflashing the watch every time I wanted to play a different version of DOOM.
Now I can just drop WADs onto the SD card and launch them from the watch itself.
Github for doom launcher : https://github.com/Tsixom0/DOOM-Launcher-for-Waveshare-ESP32-S3-2.06-Touch-Amoled
Github for wad picker : https://github.com/Tsixom0/WAD-file-picker-for-waveshare-esp32-s3-2.06-amoled-touch
Next goal: gameboy or nes emulation for this watch
Made a custom WAD launcher for my ESP32 Doom Watch.
It scans the SD card for .wad files, detects IWADs/PWADs automatically, lets you choose, and launches directly from the watch. It also creates separate save folders for each WAD and includes settings for brightness, volume, and control sensitivity.
Basically, I got tired of reflashing the watch every time I wanted to play a different version of DOOM.
Now I can just drop WADs onto the SD card and launch them from the watch itself.
Github for doom launcher : https://github.com/Tsixom0/DOOM-Launcher-for-Waveshare-ESP32-S3-2.06-Touch-Amoled
Github for wad picker : https://github.com/Tsixom0/WAD-file-picker-for-waveshare-esp32-s3-2.06-amoled-touch
Next goal: gameboy or nes emulation for this watch
Inspired by Claude Desktop Buddy, I wanted to build a wrist-worn AI companion around an ESP32-S3 AMOLED watch board.
The watch handles:
Wake button and voice recording
Custom smartwatch-style UI
Animations and facial expressions
Wi-Fi communication
Conversation history and state management
The ESP32 records audio, sends it to a cloud AI service, receives the response, and displays/plays it back on the watch.
Hardware:https://www.waveshare.com/esp32-s3-touch-amoled-2.06.htm
Challenges:
Audio capture/playback on ESP32
Power management
Designing a responsive UI within ESP32 memory limits
Managing latency between voice input and AI responses
GitHub: https://github.com/Tsixom0/Tsixom-Watch-Buddy-for-waveshare-esp32-s3-2.06-touch-amoled
Inspired by Claude Desktop Buddy, I wanted to build a wrist-worn AI companion around an ESP32-S3 AMOLED watch board.
The watch handles:
Wake button and voice recording
Custom smartwatch-style UI
Animations and facial expressions
Wi-Fi communication
Conversation history and state management
The ESP32 records audio, sends it to a cloud AI service, receives the response, and displays/plays it back on the watch.
Hardware:https://www.waveshare.com/esp32-s3-touch-amoled-2.06.htm
Challenges:
Audio capture/playback on ESP32
Power management
Designing a responsive UI within ESP32 memory limits
Managing latency between voice input and AI responses
Future plans:
Offline wake-word detection
Local intent handling
Audio playback through the onboard speaker
More animations and expressions
Better battery life
GitHub: https://github.com/Tsixom0/Waveshare-esp32-s3-2.06-amoled-AI-Assistant (v1)
One of the biggest changes was power management. The watch now supports screen sleep, light sleep, deep sleep, automatic sleep timers, and smarter WiFi handling. WiFi is automatically disconnected when not needed and kept alive only during active tasks such as transcription. These changes significantly reduced idle power consumption and noticeably improved battery life during normal use.
I also added hardware brightness control which wasn't there in the previous version
Also added proper timekeeping with NTP synchronization and a hardware RTC (PCF85063). The watch now keeps accurate time across reboots, sleep states, and WiFi outages, with timezone support and automatic RTC synchronization.
The UI was completely reworked around a PSRAM-backed canvas renderer. This eliminated display flickering, reduced unnecessary redraws, improved animation smoothness, and made the interface feel much more responsive overall.
Posting again cuz it goes removed
Inspired by Claude Desktop Buddy, I wanted to build a wrist-worn AI companion around an ESP32-S3 AMOLED watch board.
The watch handles:
Wake button and voice recording
Custom smartwatch-style UI
Animations and facial expressions
Wi-Fi communication
Conversation history and state management
The ESP32 records audio, sends it to a cloud AI service, receives the response, and displays/plays it back on the watch.
Hardware:https://www.waveshare.com/esp32-s3-touch-amoled-2.06.htm
Challenges:
Audio capture/playback on ESP32
Power management
Designing a responsive UI within ESP32 memory limits
Managing latency between voice input and AI responses
Future plans:
Offline wake-word detection
Local intent handling
Audio playback through the onboard speaker
More animations and expressions
Better battery life
GitHub: https://github.com/Tsixom0/Waveshare-esp32-s3-2.06-amoled-AI-Assistant
[deleted]
The project is based on doomgeneric and runs entirely on the watch without a companion PC
Hardware:https://www.waveshare.com/esp32-s3-touch-amoled-2.06.htm
Challenges
The biggest issue was memory. Several doomgeneric renderer structures were too large for ESP32 DRAM, causing linker overflows and runtime crashes. I ended up patching the engine to move large rendering structures into PSRAM and fixing several rendering edge cases that would crash on the ESP32. I also modified the display backend to use an RGB565 rendering path, which removed a costly color conversion step and improved performance significantly.
Current Features
Shareware DOOM running from SPIFFS
Sound effects through ES8311(Sfx only)
Touch-drag movement controls
Physical buttons for fire/use
RGB565 display backend
Performance
320×200 native: 20+ FPS
400×250 scaled: ~16 FPS
410×502 fullscreen: ~10 FPS
410×256 wide mode: ~16–19 FPS (current default)
Still Working On
Save game support
SD card WAD loading
DOOM II support from SD card
Further control tuning
Save/load testing
Music support
The project runs entirely on the watch itself—no PC streaming or remote rendering.
GitHub: no plans yet