QP/C Real-Time Embedded Framework/RTOS based on asynchronous, event-driven Active Objects (Actors) and Hierarchical State Machines
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Updated
Nov 2, 2024 - C
QP/C Real-Time Embedded Framework/RTOS based on asynchronous, event-driven Active Objects (Actors) and Hierarchical State Machines
QP/C++ Real-Time Embedded Framework/RTOS based on asynchronous, event-driven Active Objects (Actors) and Hierarchical State Machines
Simplified Version of 555 Timer for Capacitance Meter. Built in Parallel to Resistance Meter.
JTAG/SWD debugger + UART adapter based on the Black Magic Probe firmware
Shenanigans with LEDs on KL25z ARM Cortex M0 board, using lots of interrupts.
RSA encryption and decryption on ARM Cortex M0 Freedom KL25Z board using external keypad and display.
Gain an introductory knowledge to the basics of SoC design and key skills required to implement a simple SoC on an FPGA, and write embedded programs targeted at the microprocessor to control the peripherals
Controlled relay station.
Event-driven, preemptive, priority-based, hardware RTOS for ARM Cortex-M.
ARM Cortex M0+ Assembly code from CMPE-250 class at RIT. Written for FRDM-KL05Z. Developed using Keil uVision IDE
Task scheduler for Arm® Cortex®-M0+ processor on NXP FRDM-KL25Z board
QP-nano real-time embedded framework/RTOS for embedded systems based on active objects (actors) and hierarchical state machines
Code for IEEE Internet Computing Journal paper 'OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices'
Codes written in order to learn and improve my skills on embedded C programming of ARM Cortex-M microcontrollers.
Pico Toolkit for 2 inch display
Easy GUI for microcontrollers
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
Code for IoT paper 'Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices'
Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'
Embedded OS for IoT
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