EleTect seeks to safeguard lives, promote harmony, and aid in the preservation of animals by utilizing technology and ecological knowledge.
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DL and GenAI Hands-On with the Raspberry Pi
A tiny DIY cam built with Xiao ESP32S3 Sense. Captures images with a button press and saves them to an SD card.
Your personal doctor at your fingertips!
The trained LSTM model will be converted with TFLite-Micro and Edge Impulse Python SDK and deployed on an XIAO ESP32S3.
Exploring Computer Vision applications such as Image Classification, Object Detection, and Pose estimation.
Transforming air quality monitoring with cutting-edge technology. Our system combines advanced sensors and real-time analytics for proactive
Bridging the gap between training on synthetic data and real data in TinyML.
Computer Vision Exploration with the help of Edge Impulse and Arduino.
Motion classification and Anomaly Detection exploration with the help of Edge Impulse and Arduino Nicla Vision.
Computer Vision Exploration with the help of OpenMV, Edge Impulse, and Arduino.
Getting started with custom computer vision for your project is a snap using the Remyx Engine and Arduino Portenta H7
Creating a TinyML Anomaly Detection & Motion Classification project with the IMU MPU2060
Use machine learning to build a system that can recognize audible events, particularly your name through audio classification.
Exploring Machine Learning on the tiny device of the Seeed XIAO family, the ESP32S3 Sense and SenseCraft-Web-Toolkit
NMCS is a device that uses its hearing and seeing skills to make sure that your coffee doesn't spill when making your energy booster.
RP2040-based bling that changes its LED color when it detects one of three keywords: "Pi", "3.14", or "Irrational"
Measure the flow rate through a pipe and use machine learning to determine if a clog has formed.
Deploy a TinyML model to detect the states of a 3D printer and monitor those states by sending them over cellular to the cloud.
Collecting sensor data from an MCU, transmitting it via BLE, controlling it with an App, and logging it remotely on a spreadsheet.
Detecting short circuits, open circuits and missing holes in PCB boards with Object Detection and deploying to a Raspberry Pi
This project is a proof of concept to test the feasibility of using tinyML with ultra low cost microscopes to classify microorganisms
