QP/C Real-Time Embedded Framework/RTOS for embedded systems based on active objects (actors) and hierarchical state machines
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Updated
Jul 5, 2024 - C
QP/C Real-Time Embedded Framework/RTOS for embedded systems based on active objects (actors) and hierarchical state machines
Event-driven, preemptive, priority-based, hardware RTOS for ARM Cortex-M.
Design and program Arm-based embedded systems and implement them in low-level hardware using standard C and assembly language.
Acoustic features (MFSCs and MFCCs) for edge AI
Specify, design, and program modern connected electronic systems in response to the ever-growing number of connected devices
What to do when Hard fault hits? Debugger and error reporter solution for ARM Cortex M3 and M4.
CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices
Code for IEEE Internet Computing Journal paper 'OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices'
Assignments and Examples from the MBSD Online Learning Program
For collaboration in ECSE 444
Handheld LCR Meter Implementation using Tiva launchpad evaluation Board
基于stm32-f4智能气象站及Wi-Fi开关,提供温度、气压、湿度及光强度测量、服务器上报,以及Wi-Fi控制下的GPIO口。Intelligent Weather Station and Wi-Fi switcher providing temperature ,atmosphere pressure ,humidity and lightness detecting and reporting .Also the control of GPIO in Wi-Fi.
Implements Mutex, Semaphore and exclusive ReadModifyWrite operations on ARM Cortex-M3 and Cortex-M4
GPIO Bare metal drivers for stm32 f4 family of microcontrollers written in C from scratch .The driver allows user to configure the gpio pins of stm32 microcontroller in Input Mode , Output mode , Alternate function mode , interrupt mode and configure interrupt priority . The driver also exposes apis to read and write data to and from gpio pins a…
CR-10 - SKR 1.4Turbo - Marlin 2.0
CubeSat OBC with ARM Cortex-M4 MCU.
Some attempts at cortex-m assembler programming.
LoRaWAN Camera with STM32WLE5JC & OV7670 📷
MCU board with RP2040 dual-core microcontroller.
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
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