Engineering Proceedings

10 pages, 2018 KiB

Open AccessProceeding Paper

Data Protection in Brazil: Applying Text Mining in Court Documents

by Arnaldo Lucas Santos Duarte, Everton Reis de Souza, Marcos Paulo de Oliveira Silva, Madson Bruno da Silva Monte, Nathaly Oliveira de Almeida Correia, Victor Diogho Heuer de Carvalho and Fernando Henrique Taques

Eng. Proc. 2025, 87(1), 57; https://doi.org/10.3390/engproc2025087057 - 29 Apr 2025

Abstract

The rise of information technology and artificial intelligence has sparked debates on data protection in various fields. Data protection has been addressed in court rulings long before Brazil’s General Data Protection Law (LGPD). This study analyzes jurisprudence related to data protection by examining [...] Read more.

The rise of information technology and artificial intelligence has sparked debates on data protection in various fields. Data protection has been addressed in court rulings long before Brazil’s General Data Protection Law (LGPD). This study analyzes jurisprudence related to data protection by examining 10,009 documents from the Brazilian States’ courts collected through a web scraping process in an online juridical platform without restricting the period of publication. This analysis reveals document distribution among state courts, with the southeast and southern regions being the most productive, and identifies key terms in each state court. This provides a deeper understanding of the legal processes surrounding data protection issues in each Brazilian region. Full article

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7 pages, 8590 KiB

Open AccessProceeding Paper

Design and Implementation of Environmental Monitoring System Using Flask-Based Web Application

by Rong-Tai Hong

Eng. Proc. 2025, 92(1), 37; https://doi.org/10.3390/engproc2025092037 - 29 Apr 2025

Abstract

A low-cost, real-time environmental monitoring system is proposed in this study. The system integrates the Internet of Things (IoT) technology and a micro-framework Flask-based web application. The star topology of Bluetooth devices is adopted to connect the master server and multiple sensor nodes. [...] Read more.

A low-cost, real-time environmental monitoring system is proposed in this study. The system integrates the Internet of Things (IoT) technology and a micro-framework Flask-based web application. The star topology of Bluetooth devices is adopted to connect the master server and multiple sensor nodes. The system employs a Raspberry Pi 4 model B as the master server running a micro-framework web application and an Arduino UNO as the sensor nodes connected to multiple sensors and actuators. Since the sensor data need to be consecutively and continuous in real-time, multiple tasks are executed simultaneously to complete the process; therefore, thread-based parallelism is used. The proposed system enables real-time environmental monitoring with low maintenance costs by leveraging the micro-framework web application and ad hoc network. Furthermore, the proposed system is scalable, as its components are commercial off-the-shelf commodities available on the market, and the number of sensor nodes and sensors used can be increased based on the requirements of the desired system. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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11 pages, 2770 KiB

Open AccessProceeding Paper

Adaptive Smart System for Energy-Saving Campus

by Ziling Chen, Ray-I Chang and Quincy Wu

Eng. Proc. 2025, 92(1), 36; https://doi.org/10.3390/engproc2025092036 - 29 Apr 2025

Abstract

Due to the increasing severity of global warming and climate change, more attention is being paid to environmental problems caused by human activities. Although energy saving and carbon reduction have become a global ambition, the implementation of energy-saving mechanisms remains limited. To address [...] Read more.

Due to the increasing severity of global warming and climate change, more attention is being paid to environmental problems caused by human activities. Although energy saving and carbon reduction have become a global ambition, the implementation of energy-saving mechanisms remains limited. To address this, an adaptive smart energy-saving campus system is developed in this study to improve students’ electricity usage habits. In this system, the Internet of Things (IoT) with control interfaces is integrated to enhance convenience. Using expert system rules, the system regulates the operation of the IoT for the efficient energy-saving control of a classroom. Additionally, by incorporating a random forest classifier, the system learns users’ electricity usage habits to create a tailored energy-saving environment. Gamification is also introduced to create a reward system that stimulates users’ desire to achieve goals, thus promoting autonomous energy saving. An experiment was conducted on 62 students. In total, 59 out of 62 participants responded with a sampling error of ±2.8% at a 95% confidence level. The average system usability scale (SUS) score reached 84, surpassing the cross-industry average standard, indicating that the system is user-friendly. The average self-efficacy score for energy saving reached 4.28 (σ = 3). The system significantly impacted the participant’s motivation to enhance energy saving. The net promoter score (NPS) was 29. This indicated that, although users are generally satisfied with the system, there is still room for improvement. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 471 KiB

Open AccessProceeding Paper

Performance Analysis of Japanese Electric Vehicle Manufacturers in Environmental, Social, and Governance Using Text Mining and Predictive Methods

by Meihui Zhao

Eng. Proc. 2025, 92(1), 35; https://doi.org/10.3390/engproc2025092035 - 29 Apr 2025

Abstract

The value of environmental, social, and governance (ESG) has been increasingly emphasized across various industries, particularly in the automotive sector, where its importance has become especially prominent. In this study, the environmental initiatives of Japanese electric vehicle (EV) manufacturers were evaluated from an [...] Read more.

The value of environmental, social, and governance (ESG) has been increasingly emphasized across various industries, particularly in the automotive sector, where its importance has become especially prominent. In this study, the environmental initiatives of Japanese electric vehicle (EV) manufacturers were evaluated from an ESG perspective. Leading Japanese companies in EV production, such as Toyota, Nissan, and Honda, were included in the analysis. Using text mining techniques on sustainability and CSR reports from the past five years, key environmental keywords were extracted, and word clouds were generated to visualize the trends in each company’s environmental efforts. A correlation analysis was conducted between the frequency of environmental keywords and CO₂ emissions data. Based on past trends in keywords and emissions data, predictive analysis was performed to analyze the potential for future emissions reductions and the strategic direction of each company’s sustainability initiatives. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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11 pages, 584 KiB

Open AccessProceeding Paper

Evaluation and Enhancement of Power System Resilience Under Weather Events

by Yuan-Kang Wu, Duc-Tung Trinh and Chun-Hung Li

Eng. Proc. 2025, 92(1), 34; https://doi.org/10.3390/engproc2025092034 - 29 Apr 2025

Abstract

Extreme weather events might harm power system equipment. Although these events are infrequent, their impact is substantial, making the power system and its modern grids vulnerable to weather-related conditions. In this study, we reviewed weather-related resilience metrics and appropriate methods for assessing power [...] Read more.

Extreme weather events might harm power system equipment. Although these events are infrequent, their impact is substantial, making the power system and its modern grids vulnerable to weather-related conditions. In this study, we reviewed weather-related resilience metrics and appropriate methods for assessing power system resilience. These metrics were derived from various resilience curves. We also compiled data from different countries on resilience evaluation and methods to improve power system resilience. Potential metrics, evaluation methods, operational experiences, and strategies for enhancing power system resilience were proposed based on the results. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 2525 KiB

Open AccessProceeding Paper

High-Speed-Recognition Artificial Intelligence Chip Based on ARM+FPGA Platform

by Chin-Hsiung Shen, Yu-Hsien Wu, Shu-Jung Chen and Chuan-Yin Yu

Eng. Proc. 2025, 92(1), 33; https://doi.org/10.3390/engproc2025092033 - 29 Apr 2025

Abstract

We developed a license plate recognition platform based on the Zynq-7000 SoC. A field-programmable gate array (FPGA) was used to build a low-power, high-speed neural network. The system leveraged the ARM processor for initial image processing and used standard license plate characters as [...] Read more.

We developed a license plate recognition platform based on the Zynq-7000 SoC. A field-programmable gate array (FPGA) was used to build a low-power, high-speed neural network. The system leveraged the ARM processor for initial image processing and used standard license plate characters as a training dataset. After filtering and processing, the images were resized to 28 × 28 pixels in the grayscale format and then transmitted to the FPGA for high-speed recognition. The digital circuit in the FPGA was implemented using Verilog in a deep learning neural network architecture, with the neurons configured as (57, 12, 57, 36) in a hidden layer. The model was trained for 60 epochs. The neural network was also trained with a dataset consisting of 26 English alphabet characters and 10 digits, augmented using image dilation and erosion. Recognition accuracy was 83.33%. Using Vivado, the system was successfully deployed on the Zynq-7000 SoC, demonstrating its potential in intelligent applications. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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7 pages, 25197 KiB

Open AccessProceeding Paper

Identifying Barong Tagalog Textile Using Convolutional Neural Network and Support Vector Machine with Structural Pattern Segmentation

by Jeff B. Totesora, Edward C. Torralba and Cyrel O. Manlises

Eng. Proc. 2025, 92(1), 2029; https://doi.org/10.3390/engproc2025092029 (registering DOI) - 28 Apr 2025

Abstract

The Barong Tagalog is a formal attire traditionally worn by men for special occasions. Despite its cultural significance, distinguishing between the Cocoon silk, Jusi, and Piña-silk types of Philippine Barong Tagalog is challenging due to their similar colors. Although these textiles share similar [...] Read more.

The Barong Tagalog is a formal attire traditionally worn by men for special occasions. Despite its cultural significance, distinguishing between the Cocoon silk, Jusi, and Piña-silk types of Philippine Barong Tagalog is challenging due to their similar colors. Although these textiles share similar hues, their patterns and textures differ significantly, leading to potential misidentification by individuals. To identify structural patterns in textile classification, machine learning was used. Especially convolutional neural networks (CNNs) and support vector machines (SVMs) were used. The system employed a Raspberry Pi (RPI) V4 as the microprocessor and an RPI Camera V2 for image capture. The system performance was validated involving 30 sample images per classification and an additional 30 unknown samples. The system correctly classified 64 out of 90 sample images with an accuracy of 71.1%. For evaluation, a confusion matrix was determined. By combining CNN V1 and SVM V2, the textile analysis using image processing was conducted precisely to identify Barong Tagalog textiles. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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8 pages, 3697 KiB

Open AccessProceeding Paper

Pansharpening Remote Sensing Images Using Generative Adversarial Networks

by Bo-Hsien Chung, Jui-Hsiang Jung, Yih-Shyh Chiou, Mu-Jan Shih and Fuan Tsai

Eng. Proc. 2025, 92(1), 32; https://doi.org/10.3390/engproc2025092032 - 28 Apr 2025

Abstract

Pansharpening is a remote sensing image fusion technique that combines a high-resolution (HR) panchromatic (PAN) image with a low-resolution (LR) multispectral (MS) image to produce an HR MS image. The primary challenge in pansharpening lies in preserving the spatial details of the PAN [...] Read more.

Pansharpening is a remote sensing image fusion technique that combines a high-resolution (HR) panchromatic (PAN) image with a low-resolution (LR) multispectral (MS) image to produce an HR MS image. The primary challenge in pansharpening lies in preserving the spatial details of the PAN image while maintaining the spectral integrity of the MS image. To address this, this article presents a generative adversarial network (GAN)-based approach to pansharpening. The GAN discriminator facilitated matching the generated image’s intensity to the HR PAN image and preserving the spectral characteristics of the LR MS image. The performance in generating images was evaluated using the peak signal-to-noise ratio (PSNR). For the experiment, original LR MS and HR PAN satellite images were partitioned into smaller patches, and the GAN model was validated using an 80:20 training-to-testing data ratio. The results illustrated that the super-resolution images generated by the SRGAN model achieved a PSNR of 31 dB. These results demonstrated the developed model’s ability to reconstruct the geometric, textural, and spectral information from the images. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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11 pages, 4392 KiB

Open AccessProceeding Paper

Implementation of Autonomous Navigation for Solar-Panel-Cleaning Vehicle Based on YOLOv4-Tiny

by Wen-Chang Cheng and Xu-Dong Chen

Eng. Proc. 2025, 92(1), 31; https://doi.org/10.3390/engproc2025092031 - 28 Apr 2025

Abstract

We developed an autonomous navigation system for a solar-panel-cleaning vehicle. The system utilizes the YOLOv4-Tiny object detection model to detect white lines on the solar panels and combines the model with a proportional–integral–derivative (PID) controller to achieve autonomous navigation functionality. The main system [...] Read more.

We developed an autonomous navigation system for a solar-panel-cleaning vehicle. The system utilizes the YOLOv4-Tiny object detection model to detect white lines on the solar panels and combines the model with a proportional–integral–derivative (PID) controller to achieve autonomous navigation functionality. The main system platform was built on Raspberry Pi, and the Intel Neural Compute Stick 2 (NCS2) was used for hardware acceleration, which boosted the model’s inference speed from 2 to 8 frames per second (FPS), significantly enhancing the system’s real-time performance. By tuning the PID controller parameters, the system achieved an optimal performance, with

K_{P}

= 11,

K_{i}

= 0.01, and

K_{d}

= 30, maintaining the average value of the error e(t) at −0.0412 and the standard deviation at 0.1826 and improving the inference speed. The system autonomously followed the white lines on the solar panels and automatically turned when reaching the boundaries. The system also autonomously cleaned itself. The developed autonomous navigation system effectively improved the efficiency and convenience of solar panel cleaning. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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11 pages, 4345 KiB

Open AccessProceeding Paper

Deep Learning Approach to Cassava Disease Detection Using EfficientNetB0 and Image Augmentation

by Jazon Andrei G. Alejandro, James Harvey M. Mausisa and Charmaine C. Paglinawan

Eng. Proc. 2025, 92(1), 28; https://doi.org/10.3390/engproc2025092028 - 28 Apr 2025

Abstract

Cassava, a vital crop in the Philippines and other tropical regions, is highly susceptible to various diseases that drastically reduce its yield. Traditional inspection methods for detecting these diseases are manual, time-consuming, expensive, and prone to inaccuracies. While recent advances enable improved detection, [...] Read more.

Cassava, a vital crop in the Philippines and other tropical regions, is highly susceptible to various diseases that drastically reduce its yield. Traditional inspection methods for detecting these diseases are manual, time-consuming, expensive, and prone to inaccuracies. While recent advances enable improved detection, many approaches focus primarily on leaves and stems, overlooking tubers—one of the most critical parts of the plant. Since tubers are the harvested portion of the cassava and a direct source of food and income, early disease detection in this part is crucial for preventing severe yield losses. Furthermore, symptoms often manifest in the tubers before becoming visible in other parts, making their monitoring essential for timely intervention. To address these challenges and improve accuracy, we employed EfficientNetB0 and data augmentation techniques to enhance disease detection across multiple parts of the cassava plant. The developed system integrates a Raspberry Pi 4B with a camera module LCD screen enclosed in a 3D-printed casing for ease of use by farmers, and this showed detection accuracies of 94% for leaves, 90% for stems, and 92% for tubers. The system’s reliability was validated with p-values at a 0.05 significance level. By reducing the need for expensive manual inspections, the system offers a robust solution for early disease detection, particularly in the tubers, to mitigate yield losses. Its proven accuracy and practical design support better disease management practices, thereby improving crop health while enhancing food security and supporting the livelihoods of cassava farmers. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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6 pages, 544 KiB

Open AccessProceeding Paper

Real-Time Super Resolution Utilizing Dilation and Depthwise Separable Convolution

by Che-Cheng Chang, Wen-Pin Chen, Yi-Wei Lin, Yu-Jhan Lin and Po-Jui Pan

Eng. Proc. 2025, 92(1), 27; https://doi.org/10.3390/engproc2025092027 - 28 Apr 2025

Abstract

Computer vision applications require high-quality reproductions of original images, typically demanding complex models with many trainable parameters and floating-point operations. This increases computational load and restricts deployment on resource-constrained devices. Therefore, we designed a new dilation depthwise super-resolution (DDSR) model that is composed [...] Read more.

Computer vision applications require high-quality reproductions of original images, typically demanding complex models with many trainable parameters and floating-point operations. This increases computational load and restricts deployment on resource-constrained devices. Therefore, we designed a new dilation depthwise super-resolution (DDSR) model that is composed of dilation convolution, depthwise separable convolution, and residual connection, to overcome the predicaments. Compared with the well-known model, fast super-resolution convolutional neural network (FSRCNN), the developed DDSR shows better performance in evaluations and You Only Look Once (YOLO v8) confidence scores. Most importantly, the architecture of the developed DDSR has 55% trainable parameters, 19% floating-point operations per second (FLOPs) of one-channel FSRCNN, 27% of the trainable parameters, and 8% of the FLOPs of three-channel FSRCNN. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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8 pages, 1055 KiB

Open AccessProceeding Paper

Applying Artificial Intelligence in Software Development Education

by Emanuel S. Grant, Sicong Shao, Qinxuan Shi and Mark Arinaitwe

Eng. Proc. 2025, 92(1), 26; https://doi.org/10.3390/engproc2025092026 - 28 Apr 2025

Abstract

Artificial intelligence (AI) is applied at a pace that challenges the verification of its suitability to the domains of application. This situation arises from the proliferation of AI development being conducted from a data science point of view rather than a software engineering [...] Read more.

Artificial intelligence (AI) is applied at a pace that challenges the verification of its suitability to the domains of application. This situation arises from the proliferation of AI development being conducted from a data science point of view rather than a software engineering approach. The situation leads to the question of whether software development course curricula are addressing the necessary educational needs for graduates to respond to the challenges of applying AI development in emerging domains. The challenge has two parts: the first is the use of AI in developing software systems, and the second is the development of AI systems. By looking at the first part of this challenge, we propose a pedagogy for introducing AI tools in software engineering education and structuring a methodology for AI application development to establish software engineering principles. This article is exploratory. We reviewed the existing literature to identify the commonalities of approaches to select a required set of topics, course outcomes, and structure for a curriculum on AI in software development. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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9 pages, 3313 KiB

Open AccessProceeding Paper

Fuzzy Logic-Based Adaptive Droop Control Designed with Feasible Range of Droop Coefficients for Enhanced Power Delivery in Microgrids

by Mandarapu Srikanth, Yellapragada Venkata Pavan Kumar and Sivakavi Naga Venkata Bramareswara Rao

Eng. Proc. 2025, 87(1), 56; https://doi.org/10.3390/engproc2025087056 - 27 Apr 2025

Abstract

Power electronic converter-based microgrids generally suffer from poor power delivery/handling capability during sudden load changes, especially during islanded operations. This is due to the lack of transient energy support to compensate for sudden load changes. The literature has suggested the use of adaptive [...] Read more.

Power electronic converter-based microgrids generally suffer from poor power delivery/handling capability during sudden load changes, especially during islanded operations. This is due to the lack of transient energy support to compensate for sudden load changes. The literature has suggested the use of adaptive droop control to provide compensation during transient conditions, thereby improving the power delivery capability. In this context, fuzzy logic-based adaptive droop control is a state-of-the-art technique that was developed based on empirical knowledge of the system. However, this way of designing the droop coefficient values without considering the mathematical knowledge of the system leads to instability during transient conditions. This problem further aggravates when dominant inductive load changes occur in the system. To address this limitation, this paper proposes an improved fuzzy logic-based adaptive droop control method. In the proposed methodology, the values of droop coefficients that are assigned for different membership functions are designed based on the stability analysis of the microgrid. In this analysis, the feasible range of active power–frequency droop values that could avoid instability during large inductive load changes is identified. Accordingly, the infeasible values are avoided in the design of the fuzzy controller. The performance of the proposed and the conventional fuzzy logic methods is verified through simulation in MATLAB/Simulink. From the results, it is identified that the proposed method has improved the power delivery capability of the microgrid by 14% compared to the conventional method. Full article

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7 pages, 2079 KiB

Open AccessProceeding Paper

Antioxidant Activity of Ablated CeO₂ Nanoparticles with Narrow-Size Distribution

by Vladimir Mamontov, Maksim Pugachevskii, Petr Snetkov and Ratneshwar Kumar Ratnesh

Eng. Proc. 2025, 87(1), 55; https://doi.org/10.3390/engproc2025087055 - 27 Apr 2025

Abstract

A method for the synthesis of nanodispersed aqueous solutions based on ablated cerium dioxide nanoparticles with a narrow-size distribution has been developed, and their physicochemical properties have been investigated. The nanoparticle sizes of CeO₂ were analyzed using atomic force microscopy and small-angle [...] Read more.

A method for the synthesis of nanodispersed aqueous solutions based on ablated cerium dioxide nanoparticles with a narrow-size distribution has been developed, and their physicochemical properties have been investigated. The nanoparticle sizes of CeO₂ were analyzed using atomic force microscopy and small-angle X-ray scattering. The dependence of the electronic structure of ablated cerium dioxide nanoparticles on their size was established. The influence of the size factor on the antioxidant properties of the obtained particle size groups was investigated. Full article

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20 pages, 10024 KiB

Open AccessProceeding Paper

Evaluation of Seismic Effects on Atmospheric Pressure Liquid Storage Tanks

by Luca Chiappelloni, Francesco Serraino, Valerio Belardi, Simone Trupiano, Luca Gaetani and Francesco Vivio

Eng. Proc. 2025, 85(1), 54; https://doi.org/10.3390/engproc2025085054 - 27 Apr 2025

Abstract

As part of the seismic capacity assessment of thin-walled tanks containing liquid fuels, the appropriate modeling of hydrodynamic loads is required. The theory adopted in existing work requires the modeling of the hydrodynamic pressure contribution due to tank deformability, which, however, cannot be [...] Read more.

As part of the seismic capacity assessment of thin-walled tanks containing liquid fuels, the appropriate modeling of hydrodynamic loads is required. The theory adopted in existing work requires the modeling of the hydrodynamic pressure contribution due to tank deformability, which, however, cannot be calculated in closed form. The approach adopted in this work uses acoustic–structural modal analysis to obtain the deformation and response period required to calculate this contribution. The use of the proposed method, on a finite element model, allows the implementation of thickness variability and more geometric detail in the modal analysis. On the other hand, using the obtained load distributions, in non-linear static analyses, reduces the computational time compared to dynamic simulations. In addition, analyses can be performed by importing a pre-deformed surface derived from a three-dimensional scan of the real tank into the final model, thus including the effect of geometric imperfections. As a case study, an existing tank model was produced and analyzed, and the same damage patterns documented in real cases following seismic events were obtained. Therefore, due to the low computational cost, this method is appropriate to be reproduced for a statistically significant number of load cases. Full article

(This article belongs to the Proceedings of The 53rd Conference of the Italian Scientific Society of Mechanical Engineering Design)

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10 pages, 3195 KiB

Open AccessProceeding Paper

Evaluation of Peltier Cooling Vest

by Vin Klein A. Talamayan, Mharlon Jefferson S. A. Yalung and Jessie R. Balbin

Eng. Proc. 2025, 92(1), 25; https://doi.org/10.3390/engproc2025092025 - 27 Apr 2025

Abstract

We incorporated a Peltier cooling system into vests for personal comfort and applications in various workplaces. We tested the Peltier cooling vest using temperature sensors and evaluated the vest’s performance. The developed Peltier cooling vest included thermoelectric cooler modules to improve cooling efficiency [...] Read more.

We incorporated a Peltier cooling system into vests for personal comfort and applications in various workplaces. We tested the Peltier cooling vest using temperature sensors and evaluated the vest’s performance. The developed Peltier cooling vest included thermoelectric cooler modules to improve cooling efficiency and comfort by using water’s heat transfer and thermal conductivity. Through testing and subjective assessments, the effectiveness of the wearable cooling system and its potential for widespread adoption were validated. Furthermore, an intelligent control algorithm was developed to maintain target temperatures. The built-in temperature sensor enabled temperature stability in the set temperature range. The average cooling response time of the Peltier cooling vest was 9.42 min. In a lower temperature range of 16 to 24 °C, the vest maintained a stable temperature. A correlation between temperature and power consumption was observed. To improve the performance, built-in Bluetooth and a graphic user interface need to be integrated. Then, the Peltier cooling vest and its technology can be used in medical and industrial settings. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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7 pages, 1981 KiB

Open AccessProceeding Paper

Development of Proportional-Integral-Derivative Based Self-Balancing Robot Using ESP32 for STEM Education

by Cheng-Tiao Hsieh

Eng. Proc. 2025, 92(1), 24; https://doi.org/10.3390/engproc2025092024 - 27 Apr 2025

Abstract

A STEM education provides students with a friendly and efficient environment for learning science, technology, engineering, and math. According to the needs of STEM programs and activities, humanoid, biped, and quadruped robots have been developed. Those robots are used as a learning tool [...] Read more.

A STEM education provides students with a friendly and efficient environment for learning science, technology, engineering, and math. According to the needs of STEM programs and activities, humanoid, biped, and quadruped robots have been developed. Those robots are used as a learning tool supporting students in exploring the principles and theory of robotics and their related applications. In addition, those robots adapt open sources to provide free instructions for the students to build their own low-cost robots. To enhance the effects, a low-cost, two-wheel robot was created in this study. Unlike other robots, two-wheel robots usually require a gyroscope sensor and a motion controller to keep them balanced. The developed robot is an integrated system including hardware and software. Its hardware consists of an ESP32 microcontroller, a pair of DC motors, a gyroscope sensor MPU6050, and a driver for DC motors. The robot receives signals “angle” from the gyroscope, and then depends on the PID approach to drive the DC motors precisely in order to achieve balanced and smooth motions. The results of this study present the design of the robot, sensor calibration methods, and proportional-integral-derivative tuning. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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8 pages, 3671 KiB

Open AccessProceeding Paper

The Implementation of the Physical Unclonable Function in a Field-Programmable Gate Array for Enhancing Hardware Security

by Kuang-Hao Lin, Wei-Hao Wang and I-Chen Wang

Eng. Proc. 2025, 92(1), 23; https://doi.org/10.3390/engproc2025092023 - 27 Apr 2025

Abstract

The integrated circuit (IC) industry has rapidly developed, with chip hardware security assuming a critical role in IC design. The physical unclonable function (PUF) exploits semiconductor process variation differences to generate unique responses randomly. Due to its non-replicability, PUF has emerged as one [...] Read more.

The integrated circuit (IC) industry has rapidly developed, with chip hardware security assuming a critical role in IC design. The physical unclonable function (PUF) exploits semiconductor process variation differences to generate unique responses randomly. Due to its non-replicability, PUF has emerged as one of the most commonly employed methods in hardware security. We propose PUF implementation employing an automatic scan selector to toggle between eight sets of multiplexers. With an 8-bit selector, 256 state inputs are automatically generated, and the PUF architecture enables a 256-bit unique identification code for the chip. Finally, the generated identification code is outputted either serially or in parallel and implemented on a field-programmable gate array platform. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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5 pages, 1134 KiB

Open AccessProceeding Paper

vFerryman: An Artificial Intelligence-Driven Personalized Companion Providing Calming Visuals and Social Interaction for Emotional Well-Being

by Wei-Ji Wang

Eng. Proc. 2025, 92(1), 22; https://doi.org/10.3390/engproc2025092022 - 26 Apr 2025

Abstract

As awareness of mental health issues grows, there is an increasing demand for innovative tools that provide personalized emotional support. By introducing vFerryman, an AI-driven companion system was designed to enhance emotional well-being in this study. The system integrates advanced natural language processing [...] Read more.

As awareness of mental health issues grows, there is an increasing demand for innovative tools that provide personalized emotional support. By introducing vFerryman, an AI-driven companion system was designed to enhance emotional well-being in this study. The system integrates advanced natural language processing and machine learning technologies into the CrewAI framework. Multiple AI agents were used to deliver personalized, real-time emotional responses. By utilizing large language model operations (LLMOps), vFerryman optimizes the performance of large language models to dynamically adapt to users’ emotional feedback. A key feature of the system is its calming aquarium module, which offers a soothing visual environment to alleviate stress and anxiety. Additionally, vFerryman includes a social interaction platform that fosters emotional connections and shared experiences among users. The effectiveness of vFerryman in improving emotional well-being and facilitating social interaction was evaluated while identifying areas for further technical enhancement and practical applications in emotional support systems. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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Engineering Proceedings

Vol. 92

IEEE ECICE 2024

Vol. 90

EASN 2024

Vol. 89

IEEE ICKII 2024

Vol. 88

ENC 2024

Vol. 85

AIAS 2024

Vol. 84

MEST 2024

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