LILYGO® T-LoRa Pager ESP32-S3 Handheld IoT Device, 2.33" Display, QWERTY Keyboard, GPS NFC/RFID, SX1262 LoRa Versions, Al Sensor
- Prix soldé
- $119.98
- Prix habituel
- $171.40
- Vous sauvegardez
- $51.42 (30%)
Les prix incluent la TVA et les droits applicables.

T-Lora PagerProduct Description:
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The LILYGO® T-Lora Pager is a handheld ESP32-S3-based programmable IoT development device designed for compact, stylish, and powerful wireless applications. Featuring a foldable antenna design, it ensures excellent RF performance while maintaining a clean and portable look.
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Available in multiple versions — LR1121, SX1262, or CC1101 — it offers flexibility for different IoT and wireless communication needs, from LoRa to sub-GHz connectivity.
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This versatile device integrates a 2.33-inch 222×480 display, full QWERTY keyboard, AI-enabled IMU (BHI260AP), U-blox GPS (MIA-M10Q), and NFC/RFID with RTC. For audio, it includes the ES8311 chip supporting microphone, speaker, and headset. Developers can expand further with the 2×8 GPIO header, encoder with push button, and NRF24L01 module compatibility. Power management is handled by TI monitoring chips for stability and efficiency.
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Out of the box, the T-Lora Pager comes with a LILYGO-designed UI demo, enabling smooth interaction through the encoder and offering a foundation for custom development. With mounting options including a 1/4-inch screw interface, four M2 standoff mounts, and an included branded lanyard, it is ideal for wearable devices, GPS trackers, smart terminals, and portable IoT prototypes.
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Whether you are building wireless communication systems, AIoT applications, or handheld IoT gadgets, the T-Lora Pager delivers a compact, powerful, and developer-friendly platform for innovation.
ℹ️Product Information
Check out our GitHub repository for sample code and more detailed information about this board.
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https://github.com/Xinyuan-LilyGO/LilyGoLib
Technical support
Visit our GitHub community, post a description of the problem and our engineers will help you directly.
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https://github.com/Xinyuan-LilyGo











