Programmable Microcontroller Research Articles

Research of neural network-based model for nonlinear temperature drift compensation of MEMS accelerometers.

Downhole instrumentation requires more and more accuracy of MEMS inertial sensors. However, in measurement while drilling, temperature drift phenomenon of the sensor will have a cumulative impact on the drill pipe attitude solution. After experimental testing, the output response of the accelerometer had strong local linear and global nonlinear characteristics. In this paper, we proposed a temperature compensation model based on tent chaotic mapping and sparrow search algorithm optimized back propagation (BP) neural network (Tent-SSA-BPNN). Sparrow search algorithm (SSA) was optimized by tent chaotic mapping, which was utilized to improve the uniformity and search ability of SSA populations. Then, the improved SSA was used to optimize the weight and bias parameters of the BP neural network for constructing the temperature compensation model. Finally, the trained compensation model is integrated into the microprogram control unit for real-time compensation testing. The experimental results show that after sacrificing a small amount of sampling frequency, the compensation model proposed in this article has good global compensation performance, and the mean absolute percentage error is reduced from 2% to 0.2% compared to the original output. The mean absolute error and root mean square error of the improved compensation model are all reduced compared to the pre-improved BP compensation model. This temperature-compensated modeling method has a reference value for low-cost and high-precision modeling in high temperature environments, while greatly saving time cost and measurement costs.

An inexpensive way to introduce students to gamma spectroscopy

This paper presents two ways to introduce the student to some basic experimental concepts of gamma spectroscopy, without the use of expensive professional measurement equipment. For one, the complete experiment was simulated through several computer programs. Using this simulation, students are tasked with performing all the operations that must be performed in a real experimental setup, to obtain the spectrum of gamma radiation, as the expected result. For the second approach, equipment has been designed that looks and functions like real experimental equipment, and students can use it to perform completely identical procedures in the measurement process as with the real one. The central part of each component of a system designed in this way is a programmable microcontroller, set to perform a function analogous to that of the actual components. By working in these two ways, with a virtual experiment or a setup designed to fully imitate real measurement equipment, students can be introduced to the field of gamma spectroscopy and acquire a routine that can be repeated in real experiments. The main advantage of these two described methods is that they only require small investments.

การพัฒนาชุดฝึกปฏิบัติการพื้นฐานการเขียนโปรแกรมไมโครคอนโทรลเลอร์และการควบคุมหุ่นยนต์เบื้องต้น สำหรับนักเรียนในโครงการความร่วมมือทางวิชาการ

การพัฒนาชุดฝึกปฏิบัติการพื้นฐานการเขียนโปรแกรมไมโครคอนโทรลเลอร์และการควบคุมหุ่นยนต์เบื้องต้น สำหรับนักเรียนในโครงการความร่วมมือทางวิชาการ

An Eco-Friendly and Low Cost IoT based Room Temperature Control by Fan Speed Regulation for Tropical Use

This work presents an Internet of Things (IoT) based room temperature monitoring and control system by fan speed regulation developed for use in rooms of tropical regions of West Africa. In this work, cutting-edge technologies were integrated, including IoT, and cloud- based monitoring to create a system capable of dynamically remote controlling fan speed based on real- time temperature data. The Dallas DS18B20 Waterproof Temperature Sensor serves as the cornerstone for accurate temperature monitoring. A Microcontroller (Node MCU ESP8266) with Wi-Fi Module facilitates IoT connectivity, allowing users to remotely monitor and control the system through the Blynk Cloud and the Blynk App. A 12V DC table fan, driven by a MOSFET which is being controlled through Pulse Width Modulation (PWM) by the microcontroller, enables fine- tuned speed adjustments. A 16x2 LCD display provides real-time feedback on current temperature and fan speed percentage, enhancing user awareness. The microcontroller programming involves the implementation of an adaptive algorithm for dynamic fan speed control based on the room temperature, user settings and some preset parameters conditioned for tropical region of West Africa. By dynamically adjusting fan speed based on real-time temperature data, the system optimizes energy consumption, providing sustainable and eco-friendly solutions. The circuit was designed and simulated in Proteus software, the code was written in Arduino IDE, tested on breadboard, implemented finally on Veroboard and all fitted inside a suitable box. After testing the system, it worked as expected and it was observed that the fan speed increases as the room temperature increases and vice versa. Also, the fan speed depends both on the room temperature and the set threshold value. It was also observed that the speed of the fan is at its maximum when the temperature is above 40°C. Thus, the developed system is good for room temperature control in the tropical region of West Africa.

The underlying potential of NLP for microcontroller programming education

AbstractThe trend for an increasingly ubiquitous and cyber‐physical world has been leveraging the use and importance of microcontrollers (C) to unprecedented levels. Therefore, microcontroller programming (CP) becomes a paramount skill for electrical and computer engineering students. However, CP poses significant challenges for undergraduate students, given the need to master low‐level programming languages and several algorithmic strategies that are not usual in “generic” programming. Moreover, CP can be time‐consuming and complex even when using high‐level languages. This article samples the current state of CP education in Portugal and unveils the potential support of natural language processing (NLP) tools (such as chatGPT). Our analysis of CP curricular units from seven representative Portuguese engineering schools highlights a predominant use of AVR 8‐bit C and project‐based learning. While NLP tools emerge as strong candidates as students' C companion, their application and impact on the learning process and outcomes deserve to be understood. This study compares the most prominent NLP tools, analyzing their benefits and drawbacks for CP education, building on both hands‐on tests and literature reviews. By providing automatic code generation and explanation of concepts, NLP tools can assist students in their learning process, allowing them to focus on software design and real‐world tasks that the C is designed to handle, rather than on low‐level coding. We also analyzed the specific impact of chatGTP in the context of a CP course at ISEP, confirming most of our expectations, but with a few curiosities. Overall, this work establishes the foundations for future research on the effective integration of NLP tools in CP courses.

Agriculture students’ use of generative artificial intelligence for microcontroller programming

AbstractMicrocontrollers are widely used in agriculture, yet most undergraduate agriculture students do not have the programming skills necessary to make use of these devices in their academic programs or careers. However, generative artificial intelligence (AI) chatbots, such as ChatGPT, have the ability to write complex microcontroller programs when properly queried. The study was conducted to determine the effects of undergraduate agriculture students’ (n = 22) use of ChatGPT to write a microcontroller program on their programming task performance, self‐efficacy, and attitudes toward generative AI. Nine of 11 (81.8%) student pairs were successful in the ChatGPT‐assisted programming activity, requiring between one (33.3%) and six (11.1%) queries to develop their programs. The two unsuccessful pairs used either one or two queries and produced somewhat functional programs that did not fully operate as specified. Pre‐ and posttest surveys indicated significant (p < 0.001) increases in self‐efficacy for writing microcontroller programs, for using ChatGPT to write microcontroller programs, and attitudes toward generative AI. This research confirmed that undergraduate agriculture students can successfully use generative AI chatbots to write microcontroller programs and that successful task completion increases student self‐efficacy. Further research is needed to determine best practices for using generative AI in teaching and learning microcontroller programming.

Аналіз технологій реконфігурації систем інтернету речей на рівні програмних модулів та завантажувачів

The subject of study and research in this article are the technology of programming and interaction of nodes, as well as individual small-sized components of embedded Internet of Things (IoT) systems. The goal is to increase the flexibility of IoT system components by simplifying the reconfiguration process of individual nodes and components. The task is: to analyze existing approaches to building configurable systems, analyze and describe existing solutions that implement joint approaches; to analyze the tools for implementing the selected approaches; to describe the method of building a living system based on the analysis approach; and to provide a technical example of the proposed programming method. According to the tasks, the following results were obtained. Possible ways of reconfiguration of IoT components are analyzed. Methods of reconfiguration at the network level and partial node reconfiguration are considered. Methods to ensure the flexibility of IoT components are analyzed and classified. A comparative analysis of the summary parameters of the loaders was carried out. The possibility of using software components as immutable blocks of code to modify the microcontroller program as a method of reconfiguration was analyzed. The idea of using variable software modules to represent the microcontroller program at a higher level of abstraction with a modified bootloader is thus proposed. Elements of a method for reprogramming variable software modules of microcontrollers as middleware are proposed. Conclusions. According to a review of the existing types of systems, they were classified according to the level of organization of their reconfigured parts. According to the obtained preliminary classifications, some architectural solutions were considered from the point of view of improving operational characteristics. The main advantages for each type of organization of the reconfigurable parts of the systems are highlighted. An analysis of practical solutions regarding the modification of the built-in components of microcontrollers for managing and updating their firmware was conducted. The practical significance of this study is the proposal of a method of programming with variable software modules for microcontrollers and the obtained results of a competitive analysis of methods of modifying components and loader characteristics.

Namazu: Low-Cost Tunable Shaking Table for Vibration Experiments Under Generic Signals

AbstractThis article presents Namazu, a low-cost tunable shaking table framework for uniaxial vibration experiments in engineering education and research. All components and corresponding assembly are detailed. The design is easy to use and requires minimum maintenance. Open-source software covering signal generation and microcontroller programming is proposed to prescribe the motion of the table. There is no restriction in the programming language used to interface with the table. Communication with the microcontroller is performed via a serial interface, which eliminates the need for additional software. Besides, any displacement signals, including random ones, can be chosen. Due to the open-source nature of the Namazu table, users can also implement custom methods for signal generation and modify the table hardware. Suggestions are given in the paper. Accuracy is analyzed through displacement measurements. In addition, the Shinozuka benchmark is proposed and applied to test the table accuracy in the frequency domain. The results show good consistency of the signals obtained with the setpoints. Thus, Namazu, including the shaking table and a software suite, offers a versatile, accessible, and accurate solution for vibration experiments.

Impact of Training Kit-Based Internet of Things to Learn Microcontroller Viewed in Cognitive Domain

This research aims to find out how effective the IoT microcontroller training kit learning media is and to analyze the effect of using the IoT microcontroller training kit compared to the common microcontroller training kit on students' cognitive learning outcomes in learning microcontroller and microprocessor programming techniques. The normalized gain method was used to determine the effectiveness of the IoT microcontroller training kit learning media. The ANOVA method was used to determine the effect of using the IoT microcontroller training kit and common microcontroller training kit on the average student cognitive learning outcomes. The research results show that the IoT microcontroller training kit learning media has a normalized gain value of 59.62% in the effective enough category. The average cognitive learning outcomes of students using the IoT microcontroller training kit are greater than those using the regular microcontroller training kit, according to the results of the study using one-way ANOVA, where the p-value is less than the α value of 0.05. This IoT microcontroller training kit can be used to improve students' cognition regarding microcontroller learning in vocational schools.

Design and Development of Self Balancing Two Wheeler

The Self-balancing robots represent a fascinating intersection of technology and practical application. This project aims to design and develop a self-balancing two- wheeler robot capable of maintaining stability and balance autonomously. Drawing inspiration from principles observed in human balance and locomotion, the robot employs a combination of sensors, actuators, and control algorithms to achieve its objective. The project begins with an in-depth literature survey, exploring existing research and methodologies in the field of self-balancing robotics. Leveraging insights from key publications, the project outlines fundamental principles, sensor fusion techniques, advanced control methodologies, and challenges inherent in self-balancing robot design. Key components including an Arduino Uno board, accelerometers, gyroscopes, DC motors, batteries, and optional reaction wheels are carefully selected and integrated into the robot's hardware architecture. A systematic approach to hardware selection, assembly, sensor integration, microcontroller programming, and motor control ensures a coherent and functional design. Throughout the development process, emphasis is placed on rigorous testing, calibration, and iterative improvement. The robot is subjected to various environmental conditions and scenarios to validate its stability and performance. Calibration procedures refine sensor accuracy and control algorithms, enhancing the robot's ability to maintain balance under dynamic conditions. The project culminates in the creation of a comprehensive documentation package, detailing schematics, code explanations, assembly instructions, and testing methodologies. Additionally, a presentation showcases the robot's functionality, design rationale, and potential applications. By meticulously following the outlined steps and leveraging insights from existing research, this project aims to contribute to the advancement of self-balancing robotics and serve as a foundation for future exploration and innovation in this exciting field

AC PWM Control System in Induction Motor using Microcontroller

The demand for efficient and precise control of induction motors has led to the development of advanced control systems, among which AC PWM (Pulse Width Modulation) stands out as a prominent technique. This project focuses on the design and implementation of an AC PWM control system for an induction motor utilizing a microcontroller. The system employs a microcontroller to generate PWM signals, controlling the power electronics responsible for modulating the voltage supplied to the motor. The report details the architecture, components, and methodology employed in the project. A comprehensive discussion on the PWM control algorithm, motor drive circuitry, and sensor integration is presented. The microcontroller programming and experimental results showcase the effectiveness of the proposed system in achieving precise control over motor speed and efficiency. The challenges faced during the project are discussed, along with the corresponding solutions implemented. The report concludes with a summary of achievements and suggestions for future enhancements. Overall, this project contributes to the field of motor control systems, offering a reliable and efficient solution for induction motor control through AC PWM with microcontroller integration

Improving the systems for controlling ground-based sun orientation devices

The control system for terrestrial two-axis devices for orientation to the Sun has been improved with a high-speed microcontroller operation algorithm. A geomagnetic sensor was introduced into the system to increase the reliability of monitoring the positioning of solar cells. The basis of the algorithm is a simplified astronomical and geographical model of the movement of the Sun in the celestial sphere. The control system automatically tracks the trajectory of the Sun and calculates its angular coordinates for the current moment of time on any day of the year and for any point on the globe. The derived equations of the simplified mathematical model are suitable for calculations of orientation angles to the Sun in real time on 8-bit microcontrollers with low computing power. The control system by AVR-328 microcontrollers was studied. It was established that the use of the algorithm when programming microcontrollers for two-axis orientation systems ensures high stability and reliability of the tracker`s functioning process. The technical parameters of the AVR-328 microcontrollers in the case of using the developed algorithm ensure that the control system performs one reorientation step in a time interval of less than 2 seconds, which ensures the minimum technical period of the reorientation process by the tracker drive mechanisms which is about 5 seconds. Deviations of the calculated orientation angle from the exact value do not exceed 3°, which corresponds to the relative accuracy of recording the solar radiation intensity, which is less than 0.3 %. The microcontroller program written according to the developed simplified algorithm occupies about 35 % of its memory. Therefore, the use of the developed algorithm frees up the resources of AVR-328 microcontrollers for performing additional data processing operations and automatic control over various additional devices related to the process of orientation to the Sun. In the case of solar energy, the algorithm ensures the use of about 98 % of the power of solar radiation

Intersection of domains: Designing a remote-controlled dish antenna

The advent of technology has instigated rapid advances in the field of communications, a prime example being the remote-controlled dish antenna, which embodies a parabolic design intended to intercept and concentrate electromagnetic waves onto a common focal point. The modification towards remote control mandates a core understanding of diverse technological realms as it involves an amalgamation of com-ponents and knowledge. This discourse probes into the nuanced design and implementation of a remote-controlled dish antenna, conceived around the core touchstones of a microcontroller and an array of complementary components. The research work signifies a compounding of several technological do-mains, including microcontroller programming, power electronics, wireless communication, and motor control, necessitating extensive proficiency in these areas and consequently, offering an invaluable foundation to the broader control system applications. The overarching aim of this research is to enable users to effectively control a dish antenna's positioning remotely, leveraging a Bluetooth HC-05 module for optimal convenience and accessibility. This revolutionary project relies on a PIC18F2550 microcon-troller, a high-performance RISC CPU with integrated EEPROM and SRAM, which allows for flexible data storage and retrieval. Considering its compatibility with a variety of peripherals, the PIC18F2550 emerges as a logical choice, significantly enhancing the system's performance efficacy.

Continual Monitoring of Respiratory Disorders to Enhance Therapy via Real-Time Lung Sound Imaging in Telemedicine

This work presents a configurable Internet of Things architecture for acoustical sensing and analysis for frequent remote respiratory assessments. The proposed system creates a foundation for enabling real-time therapy and patient feedback adjustment in a telemedicine setting. By allowing continuous remote respiratory monitoring, the system has the potential to give clinicians access to assessments from which they could make decisions about modifying therapy in real-time and communicate changes directly to patients. The system comprises a wearable wireless microphone array interfaced with a programmable microcontroller with embedded signal conditioning. Experiments on the phantom model were conducted to demonstrate the feasibility of reconstructing acoustic lung images for detecting obstructions in the airway and provided controlled validation of noise resilience and imaging capabilities. An optimized denoising technique and design innovations provided 7 dB more SNR and 7% more imaging accuracy for the proposed system, benchmarked against digital stethoscopes. While further clinical studies are warranted, initial results suggest potential benefits over single-point digital stethoscopes for internet-enabled remote lung monitoring needing noise immunity and regional specificity. The flexible architecture aims to bridge critical technical gaps in frequent and connected respiratory function at home or in busy clinical settings challenged by ambient noise interference.

РОЗРОБКА СИСТЕМИ КЕРУВАННЯ КРОКОВИМ ДВИГУНОМ НАВЧАЛЬНОЇ ТРАНСПОРТНОЇ ЛІНІЇ

Stepper motors have long been successfully used in a variety of industrial and special equipment. The advantage of stepper motors is that a high degree of motion control can be achieved. Stepper motors are controlled using microprocessor systems. However, in this case, the stepper motor is controlled by the program loaded into the microcontroller. There is often a need to dynamically change the operation parameters of the stepper motor - speed of rotation, direction and magnitude of the angle of rotation, etc. The work is devoted to the development of the stepper motor control system of the educational transport line, implemented at the Department of Automation of Production Processes of the Ukrainian State University of Science and Technology. The system allows you to dynamically change system parameters using either a personal computer (PC) by sending the appropriate commands to the system via the COM port, or by using a tablet by sending the appropriate commands to the system via Bluetooth. Such a system can be used both in the educational process to practice standard stepper motor control techniques and microcontroller programming skills, and in industrial systems that require high-precision mechanism position control.

Design and Development of an Intelligent Connected Access Integrated Training and Assessment Platform

This study addresses the issues of poor interdisciplinary integration and misalignment between experimental content and industry demands in the construction of applied undergraduate laboratory facilities, based on the background of industry-academia collaboration. This paper presents the design and development of an intelligent connected access integrated training and assessment platform, utilizing a full-stack development approach that combines knowledge graph, sensor principles, communication protocol integration, microcontroller programming, networking, connected access, and cloud platform development. The platform adopts a topological hierarchical structure, facilitating layered instruction for teachers and helping students to understand the logical development of Internet of Things products. Furthermore, the platform utilizes equipment commonly used in enterprises to enhance students' technical application, practical, and innovative capabilities. Through teaching practice, students' engineering awareness and practical skills have significantly improved, effectively promoting the development of relevant courses and practical training.

HUMAN FOLLOWER ROBOT

The development of a Human Follower Robot incorporating IR and Ultrasonic Sensors represents an innovative venture in robotics and automation, aimed at creating a versatile machine capable of tracking and following targets while navigating obstacles. This project is fuelled by the vision of combining sensor technology, microcontroller programming, and robotic design to birth a robot capable of graceful traversal and intelligent target pursuit. At its core, the project relies on the integration of two essential sensor technologies: Infrared (IR) and Ultrasonic sensors. IR sensors, functioning akin to human eyesight, detect objects by emitting and receiving infrared light, enabling the robot to recognize the presence of a target within its line of sight. Concurrently, ultrasonic sensors enhance the robot's perception by determining distances through sound waves, facilitating obstacle avoidance and maintaining a safe tracking distance from the target. The project's foundation comprises key components working in tandem to fulfil the robot's objectives. A microcontroller, such as Arduino or Raspberry Pi, orchestrates actions by processing sensor data and regulating movements. IR sensors act as vigilant eyes, detecting the target, while ultrasonic sensors serve as the echolocation system, enabling seamless navigation in cluttered environments. Motors and wheels propel the robot, providing motion and directional control, while a reliable power supply, such as batteries, sustains its operations. Four pivotal milestones define the project's core goals. Firstly, the development of algorithms and code for effective object detection using IR sensors enables the robot to discern the presence of a target. Secondly, obstacle avoidance mechanisms are implemented through ultrasonic sensors, ensuring adept manoeuvring around barriers and hazards. Thirdly, proximity control is prioritized to maintain an optimal and safe following distance from the target, preventing collisions. Lastly, efforts focus on enabling smooth and precise movement to ensure accurate and responsive tracking behaviour. The potential applications of such a robot are diverse. Apart from assisting visually impaired individuals by guiding and avoiding obstacles, these robots can serve as automated tour guides, offering informative experiences in museums or exhibitions. Additionally, their utility extends to surveillance and security, where they can monitor areas and track intruders. Ultimately, this project holds promise for a future where intelligent robots seamlessly follow, guide, and protect, enriching lives with their remarkable capabilities. Key Words: Human Follower Robot, IR Sensors, Human Follower Robot, IR Sensors, Ultrasonic Sensors, Robotics, Automation, Sensor Technology etc

Towards a Supervised Remote Laboratory Platform for Teaching Microcontroller Programming

As it concerns remote laboratories (RLs) for teaching microcontroller programming, the related literature reveals several common characteristics and a common architecture. Our search of the literature was constrained to papers published in the period of 2020–2023 specifically on remote laboratories related to the subject of teaching microcontroller programming of the Arduino family. The objective of this search is to present, on the one hand, the extent to which the RL platform from the Hellenic Mediterranean University (HMU-RLP) for Arduino microcontroller programming conforms to this common architecture and, on the other hand, how it extends this architecture with new features for monitoring and assessing users’ activities over remote labs in the context of pervasive and supervised learning. The HMU-RLP hosts a great number of experiments that can be practiced by RL users in the form of different scenarios provided by teachers as activities that users can perform in their self-learning process or assigned as exercises complementary to the theoretical part of a course. More importantly, it provides three types of assessments of the code users program during their experimentation with RLs. The first type monitors each action users perform over the web page offered by the RL. The second type monitors the activities of users at the hardware level. To this end, a shadow microcontroller is used that monitors the pins of the microcontroller programmed by the users. The third type automatically assesses the code uploaded by the users, checking its similarity with the prototype code uploaded by the instructors. A trained AI model is used to this end. For the assessments provided by the HMU-RLP, the experience API (xAPI) standard is exploited to store users’ learning analytics (LAs). The LAs can be processed by the instructors for the students’ evaluation and personalized learning. The xAPI reporting and visualization tools used in our prototype RLP implementation are also presented in the paper. We also discuss the planned development of such functionalities in the future for the use of the HMU-RLP as an adaptive tool for supervised distant learning.

Fault tolerant micro-programmed control unit for SEU and MBU mitigation in space based digital systems

The Micro-Programmed Control Unit (MPCU) offers an alternative to conventional hardwired control circuits by employing a control store for transmitting control signals through stored control bits. Traditionally, Hamming codes are used for Single-Event Upset (SEU) protection in memory components. However, these Error Control Codes (ECC) encounter challenges, such as inconsistent code rates and limited adaptability for Multiple Bit Upsets (MBU). To address MBU protection, ECC codes with soft decoding logic are commonly utilized, leading to increased hardware complexity. This paper introduces a lightweight encoding and hard-decoding logic capable of detecting and correcting up to n2∗ upsets, achieving a code rate of ≈ 0.37. Through evaluations against both traditional and recent ECC methods, the proposed approach demonstrates enhanced fault correction capabilities compared to Hamming codes. Furthermore, it maintains a consistent code rate, incurs lower area overhead, and exhibits less hardware complexity than MBU codes by employing hard decoding logic. The suggested methodology effectively mitigates both MBU and SEUs in control stores, providing reduced delay and making it well-suited for ensuring reliability in high-speed memory applications like MPCUs.

SIMUCERT: MICROCONTROLLER PROFICIENCY CERTIFICATION THROUGH SIMULATION

SimuCert presents a cutting-edge simulation software tailored for microcontroller application proficiency certification. This software offers a practical and immersive environment for learners to develop and test their skills in microcontroller programming and application design. With a user-friendly interface and comprehensive features, SimuCert enables educators to assess and certify learners' abilities in real-world scenarios without the need for physical hardware. Through simulated exercises and challenges, learners can gain hands-on experience in coding, debugging, and optimizing microcontroller applications, preparing them for the demands of modern technology industries. SimuCert represents a significant advancement in educational technology, bridging the gap between theoretical knowledge and practical application in microcontroller engineering.