Hackster.io competition (to build you'll need the version of tensorflow provided in the tflm branch)

Speech Recognition using STM32 and Machine Learning

Edge and gateway connectivity

An Energy-Efficient Stream Join for the Internet of Things

Code for IoT paper 'Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices'

LoRa Peer to Peer link (Network layer)

Official Github repository for the CCS '23 paper "Using Range-Revocable Pseudonyms to Provide Backward Unlinkability in the Edge"

Edge Computing using Tensorflow Lite

Testing and setting up MaixDuino M1 development board

Basic setup for managing Edge nodes and devices, and is designed to meet Fluidos project requirements

Distributed Volunteer Computing with IOT

TurboVNC enhancement on user-input and display

Progetto di strumenti per la gestione di architetture fog/edge computing attraverso SDN

Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing

EdgeDevX for Edge devices on POSIX compatible systems.

Decentralized stackable aeroponic system for optimal yields. 2nd place in Smarter Sustainable World Challenge with Nordic Semiconductor

Mobilenet v1 (3,160,160, alpha=0.25, and 3,192,192, alpha=0.5) on STM32H7 using X-CUBE-AI v4.1.0

AtomML™ is an AI engine that can operate on low power edge and endpoint devices. It can learn the pattern of any and all time series data and can be used to detect anomalies or abnormalities, make one step ahead predictions/forecasts, and calculate the remaining life of entities (whether it is industrial machinery, small devices or the like).

Mobilenet v1 (3,128,128, alpha=0.25) on STMH7 using STMCube AI