Skip to main content

Weekly Wiki

Greetings​

This is Frank in Seeed Studio and welcome to the Seeed Studio weekly wiki! Each Monday, I will introduce you our latest wiki, including the ones related to our new products, the interesting projects published by Seeed Studio, and the tutorials, introductions, etc... You name it.

✨ For each week, when a collaborator contributes a project or fixes something important, we put the stars at the end of title of "Weekly Wiki" for more people be able to see their efforts👍.

Today is December 16th, and a brand new week has begun! Check out what Seeed Studio did last week!

Latest Wiki Launched​

SenseCraft AI Overview​

The Overview section provides a high-level introduction to SenseCraft AI, explaining its purpose, key features, and benefits. It serves as a starting point for users to understand the platform and its capabilities. The overview also includes links to Getting Started guides and FAQs to help users quickly get up and running with SenseCraft AI.

Wio Terminal PC Monitor Tutorial - Cyberpunk Style​

This project uses the Wio Terminal to display real-time PC stats like CPU, RAM, and temperature in a cyberpunk style. Data is gathered with a Python script and shown on the terminal. The setup includes installing Python, VSCode, and PlatformIO, with options for customization and adding features. It also covers using Cursor AI for development and debugging.

Guide to Configuring Low Data Consumption Mode for M2 Multi-Platform Gateway (4G Version)​

This tutorial will guide users to configure the low data consumption mode for the M2 Multi-Platform Gateway 4G version. In this mode, the traffic per month is expected to be around 60M. The specific traffic depends on the nodes packets, etc.

Usage of Seeed Studio XIAO MG24 Sense built-in Sensor​

This document introduces the built-in sensors of the Seeed Studio XIAO MG24 Sense, including the 6-Axis IMU (LSM6DS3TR-C) for motion measurement and the MEMS Microphone (MSM381ACT001) for high-quality audio capture, with key features and functionalities outlined.

Configuring Model Output via MQTT on SenseCraft AI for XIAO ESP32S3 Sense​

This wiki article provides a step-by-step guide on how to configure model output using MQTT (Message Queuing Telemetry Transport) for the XIAO ESP32S3 Sense board on the SenseCraft AI platform. MQTT is a lightweight messaging protocol that enables efficient communication between devices. By following these instructions, you will learn how to set up MQTT communication and retrieve model inference results from your XIAO ESP32S3 Sense.

Getting Started with the Raspberry Pi 4G LTE HAT​

The 4G Raspberry Pi HAT is a powerful and versatile add-on designed for seamless integration with Raspberry Pi models, including A+, B+, Pi 2, Pi 3, Pi 4, Pi 5, and Zero, as well as PCs. Equipped with a 40-pin GPIO connector, it ensures easy plug-and-play compatibility. The HAT features the Quectel EG25-GL CAT4 LTE module, providing high-speed 4G communication, SMS functionality, and cloud platform integration for IoT and M2M applications.

Getting Started with ReSpeaker 2-Mics Pi HAT v2​

On the latest Raspberry Pi OS, the traditional method of driver installation (For v1 device) is no longer available. We have therefore re-released a new wiki on this issue, if you are using the more modern Raspberry Pi OS rather than previous releases, please follow these steps to get your ReSpeaker working.

Using XIAO ESP32S3 Sense as an AI Sensor with SenseCraft AI​

This wiki provides a step-by-step guide on how to configure the output of a model on SenseCraft AI and use the XIAO ESP32S3 Sense as an AI sensor. By following these instructions, you will learn how to connect the XIAO ESP32S3 Sense to your computer, select the appropriate output method, and retrieve the model data using different communication protocols such as UART, I2C, and SPI.

Configuring Model Output on SenseCraft AI for XIAO ESP32S3 Sense using SSCMACore Library​

This wiki provides a step-by-step guide on how to configure the model output on SenseCraft AI for the XIAO ESP32S3 Sense board using the SSCMACore (Seeed SenseCraft Model Assistant Core) library. By following these instructions, you will be able to set up your XIAO ESP32S3 Sense to work with a pre-trained model and utilize the SSCMACore library to process the model's output.

Convert and Quantize AI Models for reCamera​

The AI model conversion tool of reCamera currently supports frameworks such as PyTorch, ONNX, TFLite, and Caffe. Models from other frameworks need to be converted into ONNX format. For instructions on how to convert models from other deep learning architectures to ONNX, you can refer to the official ONNX website: https://github.com/onnx/tutorials. This article introduces how to use reCamera's AI model conversion tool through simple examples.

Getting Started with Raspberry Pi 4G HAT GNSS Functionalities​

The integration of GNSS into the 4G LTE module enhances its capabilities, enabling precise real-time positioning and reliable communication for IoT applications. With support for multi-constellation GNSS systems, the module delivers accurate and dependable location tracking, even in remote or underserved areas. These features make it ideal for scenarios like asset tracking, fleet management, and real-time remote monitoring.

Mobile Internet for Your Pi - RNDIS 4G LTE Setup​

RNDIS (Remote Network Driver Interface Specification) is a protocol that allows USB-connected devices, like the Quectel EG25-G 4G module, to act as network interfaces. By enabling RNDIS on a Raspberry Pi, the 4G module can provide cellular internet connectivity to the Pi. The Raspberry Pi communicates with the 4G module using AT commands to configure features like RNDIS mode, GNSS, and SMS. This approach simplifies internet access in scenarios where traditional wired or Wi-Fi connections are unavailable.

Sending and Receiving SMS Messages with Quectel 4G Raspberry pi Hat​

In rural and remote areas, where 4G coverage is sparse or unavailable, SMS communication through 2G networks becomes a vital tool for ensuring uninterrupted connectivity in IoT systems. For wildlife preservation, this technology enables automated alert systems to monitor environmental conditions, track animal movements, and report critical events in real-time. By leveraging 4G modules with SMS capabilities, devices can send automated alerts and receive instructions, ensuring that even in isolated regions, conservation efforts are not hindered by lack of modern network infrastructure.

Existing Wiki Updated​

Get Started with Indicator for Meshtastic​

We have refined the SenseCAP Indicator for Meshtastic example page.

The Efforts of Contributor​

Seeed Studio Round Display for XIAO Christmas Ball​

On this tutorial I'm going to show you how you can create a Christmas ball with falling snow and changing background images.

Past Weekly wiki​

Click here
Loading Comments...