A Survey of Research in Microcontroller Education

Bolanakis, Dimosthenis E.

doi:10.1109/rita.2019.2922856

Cited by 36 publications

(20 citation statements)

References 53 publications

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“…The hardware structure was intentionally left in a low scale of integration to show memories, address decoders, and additional I/O ports, gates, and buffers. Those are all of the electronic components that students should be aware of, especially given that every modern microcontroller [15] or Programmable System on Chip (PSoC) [16] has hidden them inside a single chip.…”

Section: The Mkd-51 Didactic Systemmentioning

confidence: 99%

An Accurate State Visualization of Multiplexed and PWM Fed Peripherals in the Virtual Simulators of Embedded Systems

Radecki¹,

Rybicki²

2022

Applied Sciences

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A method of precise and real-like embedded systems peripherals visualization in virtual simulations is presented in the article. For high frequency peripheral inputs, blended graphics of real-look representations of peripherals are used, allowing for an accurate visualization with consideration of their input signal nature based on PWM and multiplexing schemes. An accurate simulator of a didactic embedded system called MKD-51 is introduced as a plug in for Keil μVision IDE. A comparison with a real microprocessor system using multiplexing seven-segment LED modules as well as LED bar fed by PWM is shown. The achieved quantity results are included to illustrate compliance with real devices and improvements in visualization accuracy due to applying additional blending mapping function. Brightness estimation differences of LED visualization compared to a real device are at a single percentage level for seven-segment multiplexed modules.

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Section: The Mkd-51 Didactic Systemmentioning

confidence: 99%

An Accurate State Visualization of Multiplexed and PWM Fed Peripherals in the Virtual Simulators of Embedded Systems

Radecki¹,

Rybicki²

2022

Applied Sciences

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“…The Argo Buzzer System is a buzzer system that features unparalleled user-repairability and upgradability. At the heart of the Argo, Buzzer System is the Arduino Mega; the Arduino Mega microcontroller can be easily reprogrammed by the user which allows for very good adaptability [12]. The default system provides 8 simple handheld buzzers which are individually replaceable, in addition, individual buzzers can be removed or added based on the individual needs.…”

Section: Solutionmentioning

confidence: 99%

User Repairable and Customizable Buzzer System using Machine Learning and IoT System

Huang¹,

Sun²

2022

Artificial Intelligence and Fuzzy Logic System

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The creation and sustainability of academic teams have long been unnecessarily difficult due to the exorbitant costs of purchasing and maintaining equipment [1][2]. These costs serve as a major barrier, especially in poorer areas where securing the funds for this equipment is difficult [3]. In addition, when the equipment eventually breaks, it is often difficult to repair, forcing academic teams to purchase a new set of equipment. This project attempts to provide a product that can drastically lower the equipment's costs and allow the user to modify and repair it as necessary. This project resulted in the development of the Argo Buzzer System which was created with input from experienced academic team members and it has proven that it is comparable to modern buzzer systems for a fraction of the cost [4]

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“…Modern microcontrollers are enhanced with higher processor's speed, Radio/Wi-Fi capability, sufficient memory, integrated Analog-Digital Converter (ADC), and a boot-loader (i.e., an embedded operating system) to facilitate OOP. These novel features have opened the possibility of implementing AI and Internet of Things (IoT) functions with the microcontroller [5].…”

Section: Literature Reviewmentioning

confidence: 99%

An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation

Benyeogor¹,

Nnoli²,

Olakanmi³

et al. 2018

EAI Endorsed Transactions on Context-aware Systems and Applicat

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A recent significant progress has been made in development of intelligent mobile robots that is capable of autonomous navigation using an edge-computing system. This could sense changes in its environment to control its mechanical behavior towards accomplishing preprogrammed motions. Several algorithms were used in developing the robot's control software. These include the moving average filter, the extended Kalman filter, and the covariance algorithm. Using these algorithms, the robot could learn from its sensors to estimate and control its position, velocity, and the proximity of obstacles along its path, while autonomously navigating to a predetermined location on the earth's surface. Results show that our algorithmic approach to developing software systems for autonomous robots using edge-computing devices is viable, cost-efficient, and robust. Hence, our work is a proof of concept for the further development of edge-based intelligence and autonomous robots.

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A Survey of Research in Microcontroller Education

Cited by 36 publications

References 53 publications

An Accurate State Visualization of Multiplexed and PWM Fed Peripherals in the Virtual Simulators of Embedded Systems

An Accurate State Visualization of Multiplexed and PWM Fed Peripherals in the Virtual Simulators of Embedded Systems

User Repairable and Customizable Buzzer System using Machine Learning and IoT System

An Algorithmic Approach to Adapting Edge-based Devices for Autonomous Robotic Navigation

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