diff --git a/docs/Network/Meshtastic_Network/meshtastic_intro.md b/docs/Network/Meshtastic_Network/meshtastic_intro.md
index b1adca6bb686..bc2bc51c4581 100644
--- a/docs/Network/Meshtastic_Network/meshtastic_intro.md
+++ b/docs/Network/Meshtastic_Network/meshtastic_intro.md
@@ -45,7 +45,7 @@ Click [here](https://meshtastic.org/docs/) to learn more about Meshtastic networ
## Supported Hardware
-* [Tracker Dev Kit for Meshtastic® – Wio Tracker 1110](hhttps://www.seeedstudio.com/Wio-Tracker-1110-Dev-Kit-for-Meshtastic.html)
+* [Tracker Dev Kit for Meshtastic® – Wio Tracker 1110](https://www.seeedstudio.com/Wio-Tracker-1110-Dev-Kit-for-Meshtastic.html)
* [SenseCAP Card Tracker T1000-E for Meshtastic](https://www.seeedstudio.com/SenseCAP-Card-Tracker-T1000-E-for-Meshtastic-p-5913.html)
* [SenseCAP Indicator for Meshtastic](https://www.seeedstudio.com/Indicator-for-Meshtastic.html)
@@ -53,4 +53,4 @@ Click [here](https://meshtastic.org/docs/) to learn more about Meshtastic networ
:::note
Meshtastic® is a registered trademark of Meshtastic LLC. Meshtastic software components are released under various licenses, see GitHub for details. No warranty is provided - use at your own risk.
-:::
\ No newline at end of file
+:::
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240422.md b/docs/Seeed_Elderly/weekly_wiki/wiki240422.md
index e0f279c82b26..a1bba4a300cf 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240422.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240422.md
@@ -67,7 +67,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/)
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/)
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240429.md b/docs/Seeed_Elderly/weekly_wiki/wiki240429.md
index d271234d12fd..e1ca5d340c98 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240429.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240429.md
@@ -61,7 +61,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/) -->
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/) -->
- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information.
- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us!
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240513.md b/docs/Seeed_Elderly/weekly_wiki/wiki240513.md
index 49c77eb43cfb..8ab83701cca7 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240513.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240513.md
@@ -85,7 +85,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/) -->
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/) -->
- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information.
- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us!
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240520.md b/docs/Seeed_Elderly/weekly_wiki/wiki240520.md
index 28515c5b52b7..f67337d260fa 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240520.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240520.md
@@ -91,7 +91,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/) -->
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/) -->
- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information.
- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us!
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240527.md b/docs/Seeed_Elderly/weekly_wiki/wiki240527.md
index ad1ea487d51d..e579bc520161 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240527.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240527.md
@@ -74,7 +74,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/) -->
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/) -->
- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information.
- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us!
diff --git a/docs/Seeed_Elderly/weekly_wiki/wiki240603.md b/docs/Seeed_Elderly/weekly_wiki/wiki240603.md
index a5153949f71a..afa2f63d1c82 100644
--- a/docs/Seeed_Elderly/weekly_wiki/wiki240603.md
+++ b/docs/Seeed_Elderly/weekly_wiki/wiki240603.md
@@ -72,7 +72,7 @@ This wiki covers Zephyr support for the Seeed Studio XIAOs. With the assistance
[XIAO SAMD21 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-SAMD21-Zephyr-RTOS/)
[XIAO RP2040 With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-RP2040-Zephyr-RTOS/)
[XIAO ESP32C3 with Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP32C3-Zephyr/)
-[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/XIAO-ESP3253-Zephyr-RTOS/) -->
+[XIAO ESP32S3(sense) With Zephyr(RTOS)](https://wiki.seeedstudio.com/xiao_esp32s3_zephyr_rtos/) -->
- Check on [GitHub](https://github.com/orgs/Seeed-Studio/projects/6) for more information.
- We will be really appreciate if you can [share your ideas](https://github.com/orgs/Seeed-Studio/projects/6?pane=issue&itemId=35179519) with us!
diff --git a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-Zephyr-RTOS.md b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-Zephyr-RTOS.md
index 6d259a541744..894c591a4108 100644
--- a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-Zephyr-RTOS.md
+++ b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-Zephyr-RTOS.md
@@ -4,7 +4,7 @@ title: XIAO ESP32S3(sense) With Zephyr(RTOS)
keywords:
- Sorftware
image: https://files.seeedstudio.com/wiki/wiki-platform/S-tempor.png
-slug: /XIAO-ESP3253-Zephyr-RTOS
+slug: /xiao_esp32s3_zephyr_rtos
last_update:
date: 3/20/2024
author: timo614
diff --git a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython.md b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython.md
index 08b10576ac26..3fdf655ab1da 100644
--- a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython.md
+++ b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython.md
@@ -1,8 +1,8 @@
---
-description: CircuitPython for ESP32S3
-title: CircuitPython for ESP32S3
+description: CircuitPython for XIAO ESP32S3
+title: XIAO ESP32S3 Project CircuitPython
image: https://files.seeedstudio.com/wiki/seeed_logo/logo_2023.png
-slug: /XIAO_ESP32S3_CircuitPython
+slug: /xiao_esp32s3_project_circuitpython
last_update:
date: 08/18/2024
author: Isaac, Djair Guilherme
@@ -14,9 +14,11 @@ This wiki has been updated: https://wiki.seeedstudio.com/xiao_esp32s3_with_micro
CircuitPython is an ideal programming language for XIAO ESP32S3 as it simplifies physical computing projects. Based on Python, it has beginner-friendly syntax and includes modules for accessing hardware like sensors and displays. Since CircuitPython already supports the ESP32S3 chip, this project attempts to compile CircuitPython on Seeed Studio XIAO ESP32S3 Board.
+## XIAO ESP32S3 with OLED Display
+
-## Hardware Preparation
+### Hardware Preparation
I am using Seeed Studio XIAO ESPS3 and Seeed Studio Grove OLED Display 0.96 as the hardware here.
@@ -45,7 +47,7 @@ I am using Seeed Studio XIAO ESPS3 and Seeed Studio Grove OLED Display 0.96 as t
-## Software Preparation
+### Software Preparation
I am using Thonny IDE software(Windows) and some related libraries and files.
@@ -73,14 +75,14 @@ I am using Thonny IDE software(Windows) and some related libraries and files.
-## Getting Started
+### Getting Started
-### Download XIAO ESP32S3 Circuitpyhton Firmware
+#### Download XIAO ESP32S3 Circuitpyhton Firmware
[Circuitpython Firmwares 9.1.1 and 9.20 Alpha for XIAO ESP32S3 Sense](https://github.com/djairjr/Seeed_Xiao_ESPS3_Sense_Circuitpython/tree/main/seeed_xiao_esp32s3_sense/seeed_xiao_esp32s3_sense)
-### Connect the XIAO ESP32S3 board to PC under the BootLoader Mode
+#### Connect the XIAO ESP32S3 board to PC under the BootLoader Mode
The specific method is:
@@ -92,7 +94,7 @@ The specific method is:
-### Open Thonny and Configure the options
+#### Open Thonny and Configure the options
1. After running Thonny, navigate "Tools -> Options" and click the "Options" selection
@@ -129,7 +131,7 @@ Eg. (seeed_xiao_esp32s3_911.bin or seeed_xiao_esp32s3_920.bin)
-### Add the related files(libraries) to the "CIRCUITPY" driver
+#### Add the related files(libraries) to the "CIRCUITPY" driver
Copy all the files from the [related files(library)](https://files.seeedstudio.com/wiki/wiki-ranger/Contributions/S3-CIRCUITPY/related-mpy.zip) to the "CIRCUITPY" driver.
@@ -142,11 +144,11 @@ The "adafruit_ssd1306.mpy" file and "adafruit_framebuf.mpy" file are necessary w
The adafruit_framebuf library uses a font file named font5x8.bin to render text. This file needs to be accessible within the environment where your code is executed.
:::
-### Write code(IIC) and upload to achieve OLED display
+#### Write code(IIC) and upload to achieve OLED display
1. After adding the files, I can now import the adafruit_ssd1306 library into the code using the command import adafruit_ssd1306 and the environment is now configured to drive the OLED display. The code is shown below:
-```cpp
+```python
from board import *
from busio import I2C
import busio
@@ -175,19 +177,77 @@ display.show()
-:::note
-You allways could install CircuitPython libraries using the tool [circup](https://learn.adafruit.com/keep-your-circuitpython-libraries-on-devices-up-to-date-with-circup/install-circup), from Adafruit. When installed, you just type:
-```
+
+## XIAO ESP32S3 Sense with Using XIAO Round Display with Sense Camera
+
+### Hardware Preparation
+
+
+
+
+ | Seeed Studio XIAO ESP32S3 Sense |
+ Round Display for XIAO |
+
+
+ |
+ |
+
+
+ |
+ |
+
+
+
|
- |
+ |
|
diff --git a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_nRF52840-Sense/XIAO_BLE.md b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_nRF52840-Sense/XIAO_BLE.md
index ceb359b29011..d4e8fe51a428 100644
--- a/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_nRF52840-Sense/XIAO_BLE.md
+++ b/docs/Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_nRF52840-Sense/XIAO_BLE.md
@@ -183,23 +183,118 @@ If you are using the factory firmware of the Seeed Studio XIAO nRF52840 or have
-- **Step 3.** Upload the [deep_sleep demo](https://github.com/0hotpotman0/BLE_52840_Core/blob/main/libraries/Bluefruit52Lib/examples/Hardware/deep_Sleep/deep_Sleep.ino) here and run it with **Arduino**
+<<<<<<< HEAD
+- **Step 3.** Upload the [Low Power demo](https://files.seeedstudio.com/wiki/XIAO-BLE/PowerTests.zip) here and run it with **Arduino**
+=======
+- **Step 3.** Upload the deep_sleep demo here and run it with **Arduino**
-- **Step 4.** Adjust the voltage of the digital source meter to 3.6V constant voltage
-
-- **Step 5.** Touch the red test pen to BAT+ and black test pen to BAT-
-
-
-
-- **Step 6.** The output shows the current is at about **3 μA**
+```cpp
+// The MIT License (MIT)
+// Copyright (c) 2019 Ha Thach for Adafruit Industries
+
+#include "SdFat.h"
+#include "Adafruit_SPIFlash.h"
+
+// Uncomment to run example with custom SPI and SS e.g with FRAM breakout
+// #define CUSTOM_CS A5
+// #define CUSTOM_SPI SPI
+
+#if defined(CUSTOM_CS) && defined(CUSTOM_SPI)
+ Adafruit_FlashTransport_SPI flashTransport(CUSTOM_CS, CUSTOM_SPI);
+
+#elif defined(ARDUINO_ARCH_ESP32)
+ // ESP32 use same flash device that store code.
+ // Therefore there is no need to specify the SPI and SS
+ Adafruit_FlashTransport_ESP32 flashTransport;
+
+#else
+ // On-board external flash (QSPI or SPI) macros should already
+ // defined in your board variant if supported
+ // - EXTERNAL_FLASH_USE_QSPI
+ // - EXTERNAL_FLASH_USE_CS/EXTERNAL_FLASH_USE_SPI
+ #if defined(EXTERNAL_FLASH_USE_QSPI)
+ Adafruit_FlashTransport_QSPI flashTransport;
+
+ #elif defined(EXTERNAL_FLASH_USE_SPI)
+ Adafruit_FlashTransport_SPI flashTransport(EXTERNAL_FLASH_USE_CS, EXTERNAL_FLASH_USE_SPI);
+
+ #else
+ #error No QSPI/SPI flash are defined on your board variant.h !
+ #endif
+#endif
+
+Adafruit_SPIFlash flash(&flashTransport);
+
+
+/* If you want to use a specific flash device, for example for a custom built board, first look for it in Adafruit_SPIFlash\src\flash_devices.h
+ * If it isn't in there you need to create your own definition like the W25Q80DLX_EXAMPLE example below.
+ * These definitions need to be edited to match information on the data sheet of the flash device that you want to use.
+ * If you are not sure what the manufacture ID, memory type and capacity values should be, try running the sketch anyway and look at the serial output
+ * The flash device will report these values to you as a single hexadecimal value (the JDEC ID)
+ * For example, the first device on the list - the W25Q80DLX - will report its JDEC ID as 0xef4014, which is made of these three values:
+ * manufacturer_id = 0xef
+ * memory_type = 0x40
+ * capacity = 0x14
+ * With this macro properly defined you can then create an array of device definitions as shown below, this can include any from the list of devices in flash_devices.h, and any you define yourself here
+ * You need to update the variable on line 71 to reflect the number of items in the array
+ * You also need to uncomment line 84 and comment out line 81 so this array will be passed to the flash memory driver.
+ */
+//Example of a user defined flash memory device:
+//#define W25Q80DLX_EXAMPLE \
+// { \
+// .total_size = (1 << 20), /* 1 MiB */ \
+// .start_up_time_us = 5000, .manufacturer_id = 0xef, \
+// .memory_type = 0x40, .capacity = 0x14, .max_clock_speed_mhz = 80, \
+// .quad_enable_bit_mask = 0x02, .has_sector_protection = false, \
+// .supports_fast_read = true, .supports_qspi = true, \
+// .supports_qspi_writes = false, .write_status_register_split = false, \
+// .single_status_byte = false, .is_fram = false, \
+// }
+
+/*
+ * Create an array of data structures and fill it with the settings we defined above.
+ * We are using two devices, but more can be added if you want.
+ */
+//static const SPIFlash_Device_t my_flash_devices[] = {
+// W25Q80DLX_EXAMPLE,
+//};
+/*
+ * Specify the number of different devices that are listed in the array we just created. If you add more devices to the array, update this value to match.
+ */
+//const int flashDevices = 1;
+
+
+#include
+void setup()
+{
+ flash.begin();
+ Bluefruit.begin();
+ if(flash.deepPowerDown() == false){
+ pinMode(LED_BUILTIN, OUTPUT);
+ digitalWrite(LED_BUILTIN, LOW);
+ while(1)
+ {
+ yield();
+ }
+ }
+ flash.end();
+
+ sd_power_system_off();
+}
-
+void loop()
+{
+ // nothing to do
+}
+```
+>>>>>>> docusaurus-version
-### Accelerometer Examples and Low Power
+:::tip
+Here , We would like to express our special thanks to the author for providing the code -> ***daCoder*** <-
+:::
-We are very grateful to our community partner **[daCoder](https://forum.seeedstudio.com/u/daCoder)** for his contribution to the XIAO nRF52840 low power consumption mode.
+**If you want to know about this example more detail inforation , Click [Here](https://forum.seeedstudio.com/t/xiao-sense-accelerometer-examples-and-low-power/270801)**
-You can find out more about the content of the projects he has worked on by clicking **[HERE](https://forum.seeedstudio.com/t/xiao-sense-accelerometer-examples-and-low-power/270801)**.
## Battery Charging current
diff --git a/docs/Sensor/SenseCAP/SenseCAP_Watcher/Getting_Started/sensecap_watcher_software_service_framework.md b/docs/Sensor/SenseCAP/SenseCAP_Watcher/Getting_Started/sensecap_watcher_software_service_framework.md
new file mode 100644
index 000000000000..944e73e682cd
--- /dev/null
+++ b/docs/Sensor/SenseCAP/SenseCAP_Watcher/Getting_Started/sensecap_watcher_software_service_framework.md
@@ -0,0 +1,221 @@
+---
+description: This article provides a detailed setup guide for configuring the Watcher device in three different processing deployment flows,including Cloud Efficient Processing Flow, Hybrid Smart Processing Flow, and Local Secure Processing Flow. It offers an overview of the Watcher software service framework, illustrating the interactions between the user, SenseCraft Mate app, and Watcher device.
+title: 7# Watcher Software Service Framework
+image: https://files.seeedstudio.com/wiki/watcher_getting_started/50.jpg
+slug: /watcher_software_service_framework
+sidebar_position: 7
+last_update:
+ date: 10/09/2024
+ author: Evelyn Chen
+---
+
+
+# Framework Overview
+
+
+This is the software service framework for the Watcher, illustrating the interactions and task flow between the user, the SenseCraft Mate app, and the Watcher device. We offer multiple configuration options that allow users to customize their service deployment based on their data security and service quality requirements.
+
+The framework integrates cloud AI services and local AI deployments, combined with data services, device communication services, task orchestration, image analysis services, alert channel agents, and model training services.
+you can choose to deploy your LLM in the cloud or on-premises infrastructure.the original Data and result can also be chosen to be storage or transmit in cloud or on-premise device.
+Cloud compared to on-premise storage solutions as well as the need for higher-performance storage within GPU-enabled virtual machines.
+
+These components form three deployment options for users to choose from:
+
+1. **Cloud Efficient Processing Flow**
+2. **Hybrid Smart Processing Flow**
+3. **Local Secure Processing Flow**
+
+The following sections provide a detailed explanation of the framework and guide you through configuring each of the three deployment options.
+
+**Data Service**
+
+Watcher offers flexible data services, allowing you to connect to the SenseCraft data platform to upload alert data, device status, and preview images. The SenseCraft platform provides an MQTT broker address and token through an HTTP request. Alternatively, you can choose to upload data to third-party platforms via Bluetooth configuration on the app, bypassing the SenseCraft platform entirely.
+
+
+**Device Communication Service**
+
+For device communication, Watcher supports remote task flows and firmware OTA updates through MQTT. You can use the SenseCraft Mate app to create tasks and send them to the device through the SenseCraft platform. The app also checks for lastest firmware version, and when available, it will notify you. After confirming, the platform will send the update to the device.
+
+**Task Orchestration Service**
+
+
+Watcher’s task orchestration service allows for direct voice interactions, where your dialogue is sent to the service via HTTP, processed, and the task flow is returned to the device. The SenseCraft Mate app can also retrieve task flows and send them remotely to the device.
+
+
+**Vision Analysis Service**
+
+In terms of vision analysis, Watcher offers a unified image analysis service. You can choose between SenseCraft, OpenAI or third-party AI agent through the Bluetooth configuration and input the relevant API keys. When the device sends an image, it will utilize the selected service, either the local llava or a third-party service like OpenAI.
+
+
+**Alert Notification Service**
+
+For alert notifications, Watcher allows multiple options, including app push notifications from the SenseCraft cloud, UART connections to other hardware, and HTTP connections to local servers or third-party platforms. Alerts can also be sent to platforms like Discord using standard data formats. Additionally, Watcher can forward these notifications to other platforms such as Home Assistant, IFTTT, or Webhooks, using compatible formats. For more details, refer to the HTTP Proxy Application.
+
+You have the flexibility to choose from multiple deployment options and easily configure your personalized Watcher assistant. Whether your priority is data security or processing efficiency, we offer three adaptable solutions: Cloud Efficient Processing Flow, Hybrid Smart Processing Flow, and Local Secure Processing Flow. Tailor your Watcher assistant to provide you with the best smart service experience!
+
+# Cloud Efficient Processing Flow
+
+
+
+This diagram provides an overview of the Cloud Efficient Processing Flow, illustrating interactions between the user, cloud services, and local applications. In this setup, all services are executed through the SenseCraft cloud to offer a streamlined and efficient workflow. After you get started and complete device binding, you can select the appropriate cloud or local services based on your needs.
+
+The following sections explain each part of the Cloud Efficient Processing Flow and provide guidance on configuring it:
+
+**Step 1**. Initial Setup:
+After completing the [setup](https://www.seeedstudio.com/getting_started_with_watcher/#device-binding-and-ota-upgrade) and selecting SenseCraft AI Services, you can begin using the Watcher’s cloud services.
+
+
+**Step 2**. User Interaction:
+There are two ways to activate SenseCraft services, and allocate task to Watcher, detailed as follows (refer to section XXX):
+* Option 1: Via the App: Users can enable SenseCraft AI services through the mobile application. Then sending task message in chat.
+* Option 2: Via Voice Commands: Users can assign task through voice chat directly with the Watcher.
+
+
+**Step 3**. Task Orchestration:
+Once SenseCraft is activated, it functions as a Platform-as-a-Service (PaaS) to provide task orchestration services. This includes three core elements:
+* SST (Speech-to-Text): Converts spoken commands into text.
+* TTS (Text-to-Speech): Converts text-based responses into spoken output.
+* AI Services: Responsible for understanding, processing, and orchestrating tasks. Based on the task’s content, the service selects the most suitable models from the SenseCraft model repository, including large language models (LLMs) and TinyML models.
+
+In addition to manually selecting local TinyML models in the manual configuration, tasks can also be processed automatically based on your input prompt. After the task orchestration model interprets your prompt, it can call the appropriate TinyML model from the SenseCraft library. For example, if a user requests, "Notify me when you see a bird," the task orchestration service will select a bird recognition model from the TinyML library to optimize response speed.
+
+In the *manual configuration*, you can choose between the **Vision LLM** (for higher accuracy) or the **TinyML model** (for faster processing).
+
+
+**Step 4**. Task Dispatch after Orchestration
+Once task orchestration is completed, the method for dispatching tasks will depend on the status of the SenseCraft Remote Control feature:
+
+* If remote control is enabled: The system will utilize the PaaS data service and device communication service to send task results to the Watcher via MQTT broker.
+* If remote control is disabled: Tasks will be dispatched to the Watcher via Bluetooth. If the device is out of Bluetooth range, you will need to enable remote control for task transmission.
+
+**Step 5**. Vision Analysis Task Processing
+
+After receiving the task from SenseCraft, the Watcher device will invoke the Visual Analysis Service. It will analyze the task using the AI model chosen by the user or determined by the task orchestration service.
+
+**Step 6**. System Notifications
+The Watcher can notify the user or a local system using various methods:
+* App push notifications
+* Serial port/UART output
+* HTTP push notifications
+
+Watcher can also send data to local servers, third-party applications, or alert services like Discord, Home Assistant, or IFTTT.
+For more details, refer to section HTTP Proxy Application.
+
+# Hybrid Smart Processing Flow
+
+
+
+
+This diagram illustrates the Hybrid Smart Processing Flow, which involves user interactions, some cloud services, and local applications. The hybrid approach balances data security, user experience, and efficiency by combining cloud-based task orchestration with local visual models.
+
+**Step 1**. Initial Setup
+After [getting started and device binding](https://wiki.seeedstudio.com/getting_started_with_watcher/#device-binding-and-ota-upgrade), users can select the appropriate local services based on their needs, enable the private Watcher service, and enter the Watcher server URL.
+
+
+
+**Step 2**. User Interaction:
+Users can send tasks via the SenseCraft app, which will initiate the task orchestration service within the platform.
+
+**Step 3**. Task Orchestration:
+Once a task is received, the SenseCraft platform, functioning as a PaaS (Platform-as-a-Service), will orchestrate the task using three core services:
+* SST (Speech-to-Text service)
+* TTS (Text-to-Speech service)
+* AI services for understanding, processing, and task orchestration.
+
+The task orchestration service interprets the task and selects the appropriate model from the SenseCraft model library or LLM (Large Language Model), depending on the task requirements.
+
+In addition to manually selecting local TinyML models in the manual configuration, tasks can also be processed automatically based on your input prompt. After the task orchestration model interprets your prompt, it can call the appropriate TinyML model from the SenseCraft library. For example, if a user requests, "Notify me when you see a bird," the task orchestration service will select a bird recognition model from the TinyML library to optimize response speed.
+
+In the *manual configuration*, you can choose between the **Vision LLM** (for higher accuracy) or the **TinyML model** (for faster processing).
+
+**Step 4**. Task Dispatch after Orchestration
+After task orchestration, the system will choose the method of dispatch depending on the status of the SenseCraft Remote Control:
+
+* If remote control is enabled: The system will use PaaS data service and device communication service to send task results to Watcher via MQTT broker.
+* If remote control is disabled: Tasks will be dispatched to Watcher via Bluetooth. If the device is out of Bluetooth range, remote control must be enabled for continued operation.
+
+
+**Step 5**. Vision Analysis Task Processing
+Once the Watcher receives the task, it will invoke the local visual analysis service deployed on a local server. The task will be analyzed using the AI model selected by the user or orchestrated by the SenseCraft task service.
+
+**Step 6**. System Notifications
+The Watcher can notify the user or a local system using various methods:
+* App push notifications
+* Serial port/UART output
+* HTTP push notifications
+
+Watcher can also send data to local servers, third-party applications, or alert services like Discord, Home Assistant, or IFTTT.
+For more details, refer to section HTTP Proxy Application.
+
+# Local Secure Processing Flow
+
+
+
+This diagram outlines the “Local Secure Processing Flow”, which focuses on complete user interaction with locally deployed applications. To ensure data privacy, task orchestration and image analysis services are deployed entirely on the local server, offering full privacy protection. However, this method limits functionality, as SenseCraft cloud services are not available. Tasks can only be initiated via in-field voice commands, and users must configure notification services to view historical data.
+
+**Step 1**. Initial Setup
+After [getting started and device binding](https://wiki.seeedstudio.com/getting_started_with_watcher/#device-binding-and-ota-upgrade), users can select the appropriate local services based on their needs, enable the private Watcher service, and enter the Watcher server URL.
+
+
+
+**Step 2**. User Interaction:
+Users can issue tasks by pressing the wheel button on the Watcher device and sending commands through voice chat.
+
+**Step 3**. Task Orchestration:
+
+The Watcher server hosted on the local server provides task orchestration services, similar to the SenseCraft task orchestration system. This local system consists of three core services:
+
+* SST (Speech-to-Text service)
+* TTS (Text-to-Speech service)
+* AI services for understanding, processing, and orchestrating tasks.
+
+After interpreting the task, the local task orchestration service dispatches tasks to the Watcher.
+
+**Step 4**. Vision Analysis Task Processing
+Once the Watcher receives the task, it will call the local visual analysis service deployed on the local server. The task will be analyzed using the AI model selected during task orchestration.
+
+**Step 5**. System Notifications
+Watcher can notify users or local systems using the following methods:
+
+* Serial port/UART output
+* HTTP push notifications
+
+Additionally, Watcher can send data to local servers, third-party applications, or alert services such as Discord, Home Assistant, and IFTTT.
+For more details, refer to section HTTP Proxy Application.
+
+## Resources
+
+- [Getting Started with SenseCAP Watcher](https://wiki.seeedstudio.com/getting_started_with_watcher/)
+
+- [Watcher Quick Start Series 1# : How to assign tasks to Watcher](https://wiki.seeedstudio.com/getting_started_with_watcher_task/)
+
+- [Watcher Quick Start Series 2# : Watcher Looks & SenseCraft Tools](https://wiki.seeedstudio.com/getting_started_with_watcher_look_tool)
+
+- [Watcher Quick Start Series 3# : As a sensor & Use Grove](https://wiki.seeedstudio.com/watcher_as_grove)
+
+- [Watcher Quick Start Series 4# : Deploy Watcher's AI capabilities locally](https://wiki.seeedstudio.com/watcher_local_deploy)
+
+- Watcher Quick Start Series 5# : Training a model for Watcher
+
+- [Watcher Quick Start Series 6# : What does Watcher do](https://wiki.seeedstudio.com/what_does_watcher_do)
+
+- [Watcher Quick Start Series 7# : Watcher software service framework](https://wiki.seeedstudio.com/watcher_software_service_framework)
+
+- Watcher Quick Start Series 8# : Watcher http proxy application
+
+## Tech Support & Product Discussion
+
+Thank you for choosing our products! We are here to provide you with different support to ensure that your experience with our products is as smooth as possible. We offer several communication channels to cater to different preferences and needs.
+
+
+
diff --git a/docs/Sensor/mmWave_radar_sensor/mmwave-for-XIAO/mmwave-for-xiao-connect-to-HA.md b/docs/Sensor/mmWave_radar_sensor/mmwave-for-XIAO/mmwave-for-xiao-connect-to-HA.md
index cbfac1e3c7d1..73b677e58f5c 100644
--- a/docs/Sensor/mmWave_radar_sensor/mmwave-for-XIAO/mmwave-for-xiao-connect-to-HA.md
+++ b/docs/Sensor/mmWave_radar_sensor/mmwave-for-XIAO/mmwave-for-xiao-connect-to-HA.md
@@ -1,14 +1,14 @@
---
description: Introduction of how the mmWave Sensor connect to HA.
-title: mmWave for XIAO to Home Assistant via Bluetooth
+title: mmWave for XIAO to Home Assistant via Bluetooth or Wifi
keywords:
- mmwave
- radar
image: https://files.seeedstudio.com/wiki/seeed_logo/logo_2023.png
slug: /mmwave_for_xiao_to_ha_bt
last_update:
- date: 12/06/2023
- author: Allen
+ date: 09/14/2024
+ author: Allen, Djair
---
# mmWave for XIAO to Home Assistant via Bluetooth
@@ -119,6 +119,213 @@ Finally, click **overview** in the upper left corner, you will see the mmwave-fo
Next, you can get creative with your automation!
+# mmWave for XIAO to Home Assistant via Wifi using ESPHome
+The following yaml file connects a Seeed XIAO ESP32S3 Sense with Radar module to Home Assistant, using the ESPHome firmware:
+
+```
+# Configuration for ESPHome
+esphome:
+ # Name of the ESP32-S3 device
+ name: "seeed-xiao-esp32s3-cam"
+
+ # PlatformIO build options
+ platformio_options:
+ build_flags: -DBOARD_HAS_PSRAM
+ board_build.arduino.memory_type: qio_opi
+ board_build.f_flash: 80000000L
+ board_build.flash_mode: qio
+
+# Configuration for ESP32 board
+esp32:
+ board: esp32-s3-devkitc-1
+ framework:
+ type: arduino
+
+# Enable logging
+logger:
+
+# Enable Home Assistant API - use your api and password
+api:
+ encryption:
+ key: ""
+
+ota:
+ - platform: esphome
+ password: ""
+
+# Wi-Fi configuration - fill with your data
+wifi:
+ ssid: ""
+ password: ""
+
+ # Enable fallback hotspot (captive portal) in case wifi connection fails
+ ap:
+ ssid: "Xiao-Esp32s3 Fallback Hotspot"
+ password: ""
+
+# Captive portal configuration
+captive_portal:
+
+# Configuration for the ESP32 Camera
+esp32_camera:
+ id: espcam
+ name: Xiao Cam
+ external_clock:
+ pin: GPIO10
+ frequency: 20MHz
+ i2c_pins:
+ sda: GPIO40
+ scl: GPIO39
+ data_pins: [GPIO15, GPIO17, GPIO18, GPIO16, GPIO14, GPIO12, GPIO11, GPIO48]
+ vsync_pin: GPIO38
+ href_pin: GPIO47
+ pixel_clock_pin: GPIO13
+ resolution: 800x600
+
+# Configuration for the ESP32 Camera Web Server
+esp32_camera_web_server:
+ - port: 8080
+ mode: stream
+ - port: 8081
+ mode: snapshot
+
+# Configuration for the 24GHz mmwave XIAO Radar
+ld2410:
+ id: ld2410_radar
+
+uart:
+ tx_pin: GPIO4
+ rx_pin: GPIO3
+ baud_rate: 256000
+ parity: NONE
+ stop_bits: 1
+
+number:
+ - platform: ld2410
+ timeout:
+ name: Radar Timeout
+ max_move_distance_gate:
+ name: Radar Max Move Distance
+ max_still_distance_gate:
+ name: Radar Max Still Distance
+ g0:
+ move_threshold:
+ name: g0 move threshold
+ still_threshold:
+ name: g0 still threshold
+ g1:
+ move_threshold:
+ name: g1 move threshold
+ still_threshold:
+ name: g1 still threshold
+ g2:
+ move_threshold:
+ name: g2 move threshold
+ still_threshold:
+ name: g2 still threshold
+ g3:
+ move_threshold:
+ name: g3 move threshold
+ still_threshold:
+ name: g3 still threshold
+ g4:
+ move_threshold:
+ name: g4 move threshold
+ still_threshold:
+ name: g4 still threshold
+ g5:
+ move_threshold:
+ name: g5 move threshold
+ still_threshold:
+ name: g5 still threshold
+ g6:
+ move_threshold:
+ name: g6 move threshold
+ still_threshold:
+ name: g6 still threshold
+ g7:
+ move_threshold:
+ name: g7 move threshold
+ still_threshold:
+ name: g7 still threshold
+ g8:
+ move_threshold:
+ name: g8 move threshold
+ still_threshold:
+ name: g8 still threshold
+
+binary_sensor:
+ - platform: ld2410
+ has_target:
+ name: Radar Target
+ id: radar_has_target
+ has_moving_target:
+ name: Radar Moving Target
+ has_still_target:
+ name: Radar Still Target
+
+sensor:
+ - platform: ld2410
+ moving_distance:
+ name: Radar Moving Distance
+ id: moving_distance
+ still_distance:
+ name: Radar Still Distance
+ id: still_distance
+ moving_energy:
+ name: Radar Move Energy
+ still_energy:
+ name: Radar Still Energy
+ detection_distance:
+ name: Radar Detection Distance
+ id: radar_detection_distance
+ g0:
+ move_energy:
+ name: g0 move energy
+ still_energy:
+ name: g0 still energy
+ g1:
+ move_energy:
+ name: g1 move energy
+ still_energy:
+ name: g1 still energy
+ g2:
+ move_energy:
+ name: g2 move energy
+ still_energy:
+ name: g2 still energy
+ g3:
+ move_energy:
+ name: g3 move energy
+ still_energy:
+ name: g3 still energy
+ g4:
+ move_energy:
+ name: g4 move energy
+ still_energy:
+ name: g4 still energy
+ g5:
+ move_energy:
+ name: g5 move energy
+ still_energy:
+ name: g5 still energy
+ g6:
+ move_energy:
+ name: g6 move energy
+ still_energy:
+ name: g6 still energy
+ g7:
+ move_energy:
+ name: g7 move energy
+ still_energy:
+ name: g7 still energy
+ g8:
+ move_energy:
+ name: g8 move energy
+ still_energy:
+ name: g8 still energy
+```
+
## Tech Support & Product Discussion
Thank you for choosing our products! We are here to provide you with different support to ensure that your experience with our products is as smooth as possible. We offer several communication channels to cater to different preferences and needs.
diff --git a/sidebars.js b/sidebars.js
index 895d9ab47d15..540c49bedb84 100644
--- a/sidebars.js
+++ b/sidebars.js
@@ -1287,10 +1287,10 @@ const sidebars = {
label: 'Programming Language',
items: [
'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-Zephyr-RTOS',
- //'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython',
+ 'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-FreeRTOS',
'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_with_MicroPython',
+ 'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_CircuitPython',
'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO_ESP32S3_Micropython',
- 'Sensor/SeeedStudio_XIAO/SeeedStudio_XIAO_ESP32S3/XIAO-ESP32S3-FreeRTOS',
],
},
{
