This article explores TinyML, a branch of machine learning run on microcontrollers like the ESP32. It details how TinyML can be used for local inference, anomaly detection, and efficient data processing with minimal power consumption, using an example of temperature and humidity monitoring.
A lightweight intelligent solution designed to monitor and identify abnormal vibration patterns in real-time. The project details the hardware (XIAO ESP32-S3, Grove Shield, LIS3DHTR accelerometer) and software (SenseCraft AI platform) used to detect vibration anomalies. It explains the GEDAD algorithm used for learning normal vibration patterns and identifying deviations.
Explore the powerful wireless capabilities of the Seeed Studio XIAO nRF52840 series, equipped with Nordic nRF52840 MCU, Bluetooth 5.0 connectivity, and options for embedded ML and advanced sensor integration.
