Electrical Engineering Degree Research Articles

Portable Air Quality Detector Using DSM501A Dust Sensor and Arduino Uno

Aims: The primary feature of this research is to design a circuit that can analyze the air around the system and determine the quality of the air.
 Study Design: This paper reports on the design and implementation of a portable air pollution analyzer using Arduino Uno, DSM501A dust sensor, LCD, switches, buzzer, and multiple LEDs. The air pollution analyzer system was designed using a combination of hardware and software techniques to measure air pollution properly.
 Place and Period of Study: The research was accomplished by the authors in a group of two students under the grasp of a professor as a part of one of his course capstone projects for the Bachelor of Science in Electrical and Electronic Engineering degree at the American International University Bangladesh (AIUB), Dhaka, Bangladesh. The authors performed their investigative tasks at AIUB from September 2023 to February 2024.
 Methodology: The air pollution analyzer was implemented using an Arduino Uno and dust sensor to generate and determine accurate air quality based on specific air contents. The system that was developed used a PM10 detection system that identified the amount of dust particles in the area. Based on PM10 readings, the air quality was identified. Moreover, the Air Quality Index (AQI) was determined using the PM10 readings. The LCD, buzzer, and multiple LEDs were used to display and indicate the air quality condition and levels.
 Results: The portable air pollution analyzer was successfully tested and found to be accurate and reliable in determining air quality. To indicate different hazardous states of air, red, green, and yellow color LEDs are used. The test outcomes were very satisfactory.
 Conclusion: This system demonstrates the use of a microcontroller in building a simple yet effective portable air quality detector. It can be scaled up for commercial production.

541 A Framework for Multicultural and Multidisciplinary Near-Peer Mentoring for Artificial Intelligence in Healthcare Education: A University of Florida Friend Group

OBJECTIVES/GOALS: This work aims to explore how citizen science serves as a transformative frame work to bridge scientific knowledge, focusing on its potential to enhance transdisciplinary learning in artificial intelligence (AI) biomedical and clinical sciences by facilitating near-peer mentoring. METHODS/STUDY POPULATION: Our group of eight friends comprise a multicultural and multidisciplinary cohort including students from the USA, Philippines, Indonesia, and Guatemala pursuing PhD degrees in electrical and computer engineering, epidemiology, physics, and MD, PharmD, and DMD degrees. We engage in shared online courses, collaborative projects, and abstract submissions. Employing our collective knowledge, we design interactive learning experiences, support each other’s initiatives, and collaboratively develop lectures and presentations. We in tend to expand collaborations in biomedical AI education while fostering principles of experiential and collaborativelearning, constructivism, and authentic inquiry. RESULTS/ANTICIPATED RESULTS: Our recent successes include submittedconference abstracts on data science and AI education in pharmacy and the facilitation of a guest lecture in health informatics. Additionally, we are currently collaborating on seven biomedical machine learning projects in radio frequency engineering, aiming for conference submissions. Moving forward, our goal is to expand our group, support the formation of similar communities, and promote data science and AI literacy in biomedical and clinical contexts. We aspire to extend this knowledge to families, classmates, and eventually patients, facilitating a broader understanding of the role of AI in healthcare. DISCUSSION/SIGNIFICANCE: We believe diverse expertise and pedagogical theories can help demonstrate the potential of citizen science to democratize scientific experience. By nurturing collaborative networks our efforts aim to bridge gaps between disciplines and enhance the broader public’s understanding of AI in healthcare.

Design, Simulation, Building, and Testing of a Microcontroller-Based Automatic Drowsiness Detection, Vehicle Braking, and Alert System

Aims: The premier practical aspect of this research drive is to propose, build, simulate, and evaluate an Arduino-built automatic vehicle driver drowsiness detection and alert system.
 Study Design: The pivotal role of a reliable braking system in vehicular safety cannot be overstated, particularly considering the escalating frequency of traffic accidents, notably prevalent in Indonesia where human factors take center stage as the primary accident catalyst. An insightful poll underscores physical fatigue or drowsiness while driving as the foremost concern. Acknowledging the nuanced disparities between conventional air systems and electric systems, this research strategically directs its attention toward crafting a new system characteristic that mirrors the efficiency of the existing systems.
 Place and Period of Study: The research action engaged by the authors in a bunch of two students under the command of a professor as a part of one of his course capstone projects for the Bachelor of Science in Electrical and Electronic Engineering degree at the American International University Bangladesh (AIUB), Dhaka, Bangladesh. The authors performed their investigative tasks at AIUB from June 2023 to January 2024.
 Methodology: Recognizing the imperative to fortify vehicular safety, the integration of artificial intelligence emerges as a vital solution to assist drivers in ensuring the safety of individuals both within and outside the vehicle. This focused study, tailored specifically for Electric Vehicles (EVs), centers on the innovative application of object and distance identification methodologies to provide a comprehensive braking action indicator. Leveraging a minicomputer and a sophisticated neural network approach, images captured by a stereo camera undergo meticulous machine learning processes. This facilitates the precise categorization and measurement of distances between objects, with subsequent priority decisions determining the optimal degree of braking action. Employing an intelligent methodology, specifically fuzzy logic, the study demonstrates a successful outcome by constructing a curve while concurrently enhancing the dynamics of the pre-existing system. Moreover, a finely tuned Pulse Width Modulation (PWM) signal for braking, lasting 10 milliseconds, is intricately devised based on the study's discerning results.
 Results: The system is simulated in Proteus and tested in real time to check its functionality. The outcomes of the test showed that the system can produce the appropriate signals based on the detection of any kind of driver’s drowsiness and can stop the car.
 Conclusion: This comprehensive approach ensures the seamless replacement of components while concurrently elevating the overall performance of the braking system

Timely Inference over Networks

Brief Biography: Md Kamran Chowdhury Shisher is a final-year Ph.D. candidate in the Department of Electrical and Computer Engineering at Auburn University, Auburn, AL, USA. He expects to graduate by May 2024. His Ph.D. works are advised by Yin Sun. Shisher's research interests include Information Freshness, Wireless Networks, Semantic Communications, and Machine Learning. His Ph.D. works focus on designing low-complexity optimal scheduling algorithms for remote inference systems. He also developed an information-theoretic tool to analyze the impact of freshness on the performance of real-time applications. He received his M.Sc. degree in Electrical Engineering at Auburn University in 2022. He completed his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology in 2017.

IoT-Based Automated Solar Panel Cleaning and Monitoring Technique

Aims: The objective of this research work is to design and develop an IoT-based automated solar panel cleaning and real-time monitoring system using a microcontroller to improve the output and efficiency of a solar module at a low cost.
 Study Design: Most of the time, dust over solar panels creates a barrier that obstructs the sun’s radiation and reduces their performance. As such, it is necessary to keep the solar panel clean to improve output power levels. We integrated the IoT technology along with a range of components, including a microcontroller, a NodeMCU, a servo motor, a DC motor-driven submersible pump, a Light Dependent Resistor (LDR), an LCD with driver IC, etc. to design the system. We developed the assembly language program for the microcontroller.
 Place and Duration of Study: The work was conducted individually under the supervisor of a faculty member as a part of the final project work of the Master of Engineering degree in Electrical and Electronic Engineering at American International University Bangladesh (AIUB), Dhaka, Bangladesh. The student conducted his research work at AIUB for two consecutive semesters from September 2022 to May 2023.
 Methodology: An LDR sensor detects the solar panel’s dirtiness and triggers the cleaning process through the microcontroller. The system monitors this continuously and real-time vital data is accessible to have some performance metrics, empowering timely maintenance actions to be triggered by the system and hence ensuring the maximum power output. The automated cleaning mechanism, driven by servo motors and mini submersible DC motor pumps, effectively removes dust and dirt from solar panels. An application was used to get real-time data through the internet to the user’s smartphone.
 Results: The server data is accessed to observe the system performance. The cost analysis shows that this system offers a cost-effective and sustainable solution for maintaining clean solar panels and optimizing power output.
 Conclusion: Such an automation system can contribute meaningfully to the progression of renewable power generation by significantly improving the efficiency and longevity of solar panels. Thus, we can have sustainable and efficient energy systems in the country by integrating IoT-based automation systems.

Evaluating Final-Year Student Classroom Communication at the Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia

Classroom communication is a very important and complex aspect in teaching and learning. The complexity of a communication process is attributed to a host of components that include the participants, messages, encoding, decoding, and transmission channels. Not much is currently known concerning classroom communication in the context of engineering education in Malaysian universities. This paper evaluates classroom communication of final-year students of the Electrical and Electronic engineering degree programs at Universiti Kebangsaan Malaysia. Four important aspects of classroom communication were investigated to understand student abilities and issues in classroom communication. One hundred and four students undertook the self-administered survey, yielding a response rate of 92.8%. The majority of the students exhibited good non-verbal communication practices, and scored favourably in the aspect of adapting the way they communicate to others. However, 42.3% of the respondents seemed to have difficulties to explain and express ideas confidently via classroom presentations. Additionally, 43 students (41.3%) appeared to be handicapped in participating actively in class discussions. Finally, at least 40 respondents (38.5%) reported difficulties to express ideas in English, but not to the extent of hindering them in participating in classroom discussions. Further studies are needed to uncover classroom communication issues in student learning among engineering students at Universiti Kebangsaan Malaysia.

Special Issue Editorial “Deep Learning Technologies for Mobile Networks: A Themed Issue in Honor of Prof. Han-Chieh Chao”

Han-Chieh Chao received his MS and PhD degrees in Electrical Engineering from Purdue University, West Lafayette, Indiana, in 1989 and 1993, respectively [...]

An Alternative Method for Learning Microwave Filter Design Theory [Book/Software Reviews

Ayushman Raghuvanshi received his B.Tech. degree in electrical engineering from National Institute of Technology Rourkela. He is an analog design intern with Texas Instruments. He is also an intern with the Defense Research and Development Organization.

FPGA Digital Architecture for Multilevel Synchronous Optimal PulseWidth ModulationWith Seamless Pulse Pattern Transitions

received the B.S. degrees in electrical engineering from the University Center of Jaraguá do Sul (UNERJ), Jaraguá do Sul, Brazil, in 2009, and the M.S. and Ph.D degrees in electrical engineering from the Federal University of Santa Catarina (UFSC), Florianopólis, Brazil, in 2011 and 2015, respectively. From 2015 to 2016 he was a researcher at the Power Electronics Institute (INEP) of the Federal University of Santa Catarina (UFSC). He is currently a Professor with the Electrotechnical Department at the Federal Institute of Education, Science and Technology of Santa Catarina (IFSC). His research interests include power electronics and electrical machines drives. He is a member of the Brazilian Power Electronic Society (SOBRAEP).

Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks

Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks

Analysis and design of control systems via parameter‐based approach

Analysis and design of control systems via parameter‐based approach

Special issue on all‐electric and hybrid‐electric flight

Special issue on all‐electric and hybrid‐electric flight

In Memoriam Prof. Jeffrey E. Froyd

<fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="froyd-3234674.tif"/> </fig> It is with a mix of great sadness, respect, and gratitude that we reflect on the passing of Prof. Jeffrey E. Froyd in October of 2022. We would like to first recall Jeff’s many accomplishments for those who may not have had the privilege of knowing him. Jeff received the B.S. degree in mathematics from the Rose–Hulman Institute of Technology, Terre Haute, IN, USA, and the M.S. and Ph.D. degrees in electrical engineering from the University of Minnesota, Minneapolis, MN, USA. He was an Assistant Professor, an Associate Professor, and a Professor of Electrical and Computer Engineering with the Rose–Hulman Institute of Technology. At the Rose–Hulman Institute of Technology, he co-created the Integrated, First-Year Curriculum in Science, Engineering, and Mathematics, which was recognized in 1997 with a Hesburgh Award Certificate of Excellence. In November 2017, he joined the Department of Engineering Education, The Ohio State University, Columbus, OH, USA, first as a Professor and later as the Department Chair, a role he would hold until his death.

Alvin William Trivelpiece

An outstanding leader, physicist, and administrator, Alvin William Trivelpiece died on 7 August 2022 in Rancho Santa Margarita, California.Alvin William TrivelpieceAIP ESVA/PHYSICS TODAY COLLECTIONPPT|High resolutionBorn on 15 March 1931 in Stockton, California, Al put himself through California Polytechnic State College and graduated in 1953 with a degree in electrical engineering. He earned a PhD in electrical engineering in 1958 from Caltech under the guidance of Roy Gould. His dissertation was titled “Space charge waves in cylindrical plasma columns.”After spending a year in the Netherlands as a Fulbright scholar, Al became a professor of electrical engineering at the University of California, Berkeley. In 1966 he became a professor of physics at the University of Maryland, College Park, where he supervised 19 doctoral candidates and published more than 40 papers on plasma physics. Al also wrote, with Nicholas Krall, Principles of Plasma Physics, which remains a classic textbook 50 years after publication.Taking a leave of absence from the University of Maryland in 1973, Al served for two years with the Atomic Energy Commission as an assistant director for research in the division of controlled thermonuclear research. Among his achievements was the establishment of the national Controlled Thermonuclear Research Computer Center (CTRCC), which provided fusion researchers across the country with remote access to leading-edge computing resources. The idea was met with considerable skepticism, but it became a model used by other science agencies.In 1976 Al became vice president for engineering and research at Maxwell Laboratories, and in 1978 he was appointed corporate vice president of Science Applications Inc. Three years later Al was nominated by President Ronald Reagan and confirmed by the Senate as director of the Department of Energy’s Office of Energy Research (now the Office of Science), where he had responsibility for 5 research programs and 10 of DOE’s laboratories. He also served as the energy secretary’s science adviser.As director, Al developed a plan for construction of five major scientific research facilities: the Advanced Light Source, the Advanced Photon Source, the Relativistic Heavy Ion Collider, the Continuous Electron Beam Accelerator Facility, and the Spallation Neutron Source (SNS). Those facilities continue to sustain US leadership in many fields of science today. Al’s planning was informed by federal advisory committees that he established and the National Academy of Sciences, an approach that continues to serve DOE’s Office of Science well.Al and Charles DeLisi in 1986 initiated the Human Genome Project, which has had an enormous impact on the life sciences and medical research. Al was masterful in obtaining support for the project from DOE management, the Office of Management and Budget, and the US Congress. The National Institutes of Health joined the project two years later.Al expanded the scope of the CTRCC to form the National Energy Research Scientific Computing Center, which continues to serve the research programs in the Office of Science as well as other DOE programs.In 1987 Al became the executive officer of the American Association for the Advancement of Science and publisher of Science. Then in January 1989, he became director of Oak Ridge National Laboratory, where he was responsible for several initiatives. He created the Office of Laboratory Computing to enhance Oak Ridge’s ability to meet complex scientific challenges. Al led the development of a successful proposal for the Center for Computational Sciences, which brought together computational-science teams, computer scientists, and the hardware vendor Intel. It was designated as one of two DOE high-performance computing research centers in 1993.A second major achievement was the SNS. The lab had been designing a reactor-based neutron source. When the cost became unacceptable, Al took the lead in shifting to the accelerator-based SNS and gathered a multilab consortium to execute design and construction and broaden the project’s base of support. The SNS returned the US to a world-leading position in neutron-scattering research.Al was an advocate for international cooperation in science. His work behind the scenes with Evgeny Velikhov led to an agreement between the US and the Soviet Union on developing a magnetic-fusion demonstration model, which laid the groundwork for the ITER project.Al’s outstanding achievements extend across research, education, science administration, and national security. He was an innovator in the positions he held. Many of his accomplishments resulted from his understanding of science and politics and his ability to guide projects through government processes.Those of us who worked closely with Al have been fortunate to have had the opportunity. Al was a continuous source of ideas and wisdom. He had a great sense of humor and was quick to generate puns. He enjoyed playing poker, chess, and golf and was an avid runner. He piloted his own airplane to the age of 85. His wisdom, leadership, and friendship will be missed.© 2023 American Institute of Physics.

Exploring the Fundamentals of Radio Wave Propagation [Book/Software Reviews

Dr. Artem Saakian, the book’s author, graduated with degrees in electrical engineering from the National Polytechnic University of Armenia (SEUA); the University of Telecommunications in St. Petersburg, Russia; and the University of Massachusetts Lowell. Dr. Saakian’s professional career began in the academic environment at SEUA; there, he was the chair of radio technology and communication systems and the director of the graduate school. His engineering and scientific research experience includes RF antenna and propagation projects funded by the U.S. Navy as well as by the former Soviet Navy and Soviet Space Administration. Dr. Saakian served in the U.S. Navy and Naval Air Systems Command (NAVAIR) as an electronics engineer beginning in 2005. He is currently retired and supports the U.S. Navy as an electronics engineering consultant. He is the author of more than 25 publications, including peer-reviewed articles, conference materials, and encyclopedia articles.

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Exploring the Past, Present, and Future of In-Band Full-Duplex Wireless Systems [Book/Software Reviews

Kenneth Kolodziej is a technical staff member in the RF Technology Group at the Massachusetts Institute of Technology (MIT) Lincoln Laboratory, where he is a principal investigator on wideband electronics and in-band full-duplex (IBFD), commonly known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">simultaneous transmit and receive</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">STAR</i> ) systems. He has conducted research on RF, microwave, and photonic circuits, including antenna, radar, and communications systems. He received his B.E. and M.E. degrees in electrical engineering from the Stevens Institute of Technology in Hoboken, NJ. He has published numerous journal articles and conference papers and holds several patents in the field of antennas and RF systems. He is also an IEEE Member and is very actively serving the IEEE Society.

The Cup Whisperer

The Cup Whisperer

Meet the Editors

Meet the Editors

Graduate education in acoustic engineering, transduction, and signal processing University of Massachusetts Dartmouth

The University of Massachusetts Dartmouth has an established graduate program of study with a concentration in Applied Acoustics leading to the M.S. and Ph.D. degree in Electrical Engineering. The program offers courses and research opportunities in the area of electroacoustic transduction, underwater acoustics, and signal processing. Courses include the Fundamentals of Acoustics, Random Signals, Underwater Acoustics, Introduction to Transducers, Electroacoustic Transduction, Medical Ultrasonics, Digital Signal Processing, Detection Theory, and Estimation Theory. The ECE department established the university’s indoor underwater acoustic test and calibration facility which is one of the largest academic facilities supporting undergraduate and graduate thesis and sponsored research. The department has collaborations with many marine acoustic related companies including nearby Naval Undersea Warfare Center in Newport, RI and Woods Hole Oceanographic Institute in Cape Cod, MA. The presentation will highlight recent theses and dissertations, course offerings, and industry and government collaborations that support acoustical engineering, transduction, and signal processing.