Hardware Integration Research Articles

Design and Test of Real-Time Detection System for Cleaning Loss of Rapeseed Harvester

Aiming to address the problem of low recognition accuracy in the current cleaning loss detection system of rapeseed harvesters, a rapeseed cleaning loss detection system was developed using the energy distinction method based on the principle of impact piezoelectricity. A signal processing circuit, centered around a hardware integral circuit and a triple voltage comparison circuit, was designed. The energy of the impact signals generated by rapeseed kernels and impurities was calculated through hardware integration. The distinction threshold for the energy of the impact signals generated by kernels and impurities under the operating wind speed of the cleaning system was found through experiments, and a fitting model relating the fan speed to the distinction threshold was constructed. A loss detection and counting system for rapeseed kernels was designed to realize the statistics and real-time display of rapeseed kernels regarding cleaning loss. Performance verification tests were conducted on mixtures of rapeseed kernels and impurities with different mixing ratios, and a field test was carried out on the platform of a 4LZY-5.0Z rapeseed combine harvester. The test results showed that the accuracy of the designed loss detection system for kernel identification was more than 91.6%. Under operating conditions of 700, 900 and 1200 r/min fan speeds in the combine harvester cleaning system, the relative errors of the loss detection system compared to manual detection were 5%, 4.7% and 3.8%, respectively. The developed loss detection system for rapeseed kernels has high detection accuracy and good overall performance, which means it can provide feedback information for the control of the harvester.

Social Distance Assessment and prevention system Based on Marker

IoT is quickly becoming a leading technology in healthcare. Early detection of health problems and preset protocols after patient recovery are all employed to decrease the chance of COVID-19 spreading to others in the event of COVID-19. Such wireless positioning devices can correctly remind individuals to maintain distance by sensing between people and then warning them if the people are close to each other. Motivated by this notion, in this paper we have proposed and implemented a model of the social distance assessment, monitoring, and marker system for prevention. The goal is to minimize the effects of the coronavirus outbreak while generating the least amount of economic harm possible, as well as to enable or even impose social distance. In the Monitoring System, users can easily access a web-based application that is integrated with the detection system by following the integration with the Raspberry Pi 4 and Pi Camera, in which they can monitor the detection of safe and unsafe people. Meanwhile, the marker system that is based on a laser will guide the user to stand in safer locations with the help of a laser marker module to eliminate violations. The proposed system is implemented using OPEN CV and Mobile NET SSD for object detection and uses the Euclidean Distance measurement method for measuring the distance between people. The hardware and software integration is also included in the system with an accuracy level, the system is an effective, low-cost, and user-friendly social spacing tool for preserving distance around people at a large gatherings.

WORK SAFETY PROTECTION SYSTEM BASED ON ARDUINO UNO

This research aims to develop an effective and reliable work safety protection system based on Arduino Uno. The system is designed to detect hazards in the workplace, such as suspicious movements that may cause accidents for industrial workers. Arduino Uno is used as the brain of the system, and sensors connected to the microcontroller serve as input devices that detect actions not in accordance with safety procedures. When the sensors detect a hazard, Arduino Uno will activate an alarm and automatically take the necessary control actions. This research involves programming the Arduino Uno, selecting the appropriate sensors, hardware integration, and thorough system testing. The developed system is expected to enhance workplace safety and provide better protection for workers. System testing is conducted using a simulated work environment that depicts different hazard scenarios. The test results show that the Arduino Uno-based work safety protection system functions as expected. The installed sensors accurately detect hazards such as excessive temperature, fire, toxic gases, excessive vibrations, and unwanted movements in the work area. Arduino Uno receives signals from these sensors and quickly responds by activating alarms and taking appropriate protective actions. Interpretation of the test results indicates that the developed system can effectively help identify potential hazards and provide the necessary protection for workers in the manufacturing industry

Growth-based monolithic 3D integration of single-crystal 2D semiconductors.

The demand for the three-dimensional (3D) integration of electronic components is steadily increasing. Despite substantial processing challenges, the through-silicon-via (TSV) technique emerges as the only viable method for integrating single-crystalline device components in a 3D format1,2. Although monolithic 3D (M3D) integration schemes show promise3, the seamless connection of single-crystalline semiconductors without intervening wafers has yet to be demonstrated. This challenge arises from the inherent difficulty of growing single crystals on amorphous or polycrystalline surfaces after the back-end-of-the-line process at low temperatures to preserve the underlying circuitry. Consequently, a practical growth-based solution for M3D of single crystals remains unknown. Here we present a method for growing single-crystalline channel materials, specifically composed of transition metal dichalcogenides, on amorphous and polycrystalline surfaces at temperatures low enough to preserve the underlying electronic components. Building on this developed technique, we demonstrate the seamless monolithic integration of vertical single-crystalline logic transistor arrays. This accomplishment leads to the development of unprecedented vertical complementary metal oxide semiconductor (CMOS) arrays composed of grown single-crystalline channels. Ultimately, this achievement provides opportunities for M3D integration of various electronic hardware in the form of single crystals.

Contemporary Software Modernization: Strategies, Driving Forces, and Research Opportunities

Software modernization is a common activity in software engineering, since technologies advance, requirements change, and business models evolve. Differently from conventional software evolution (e.g., adding new features, enhancing performance, or adapting to new requirements), software modernization involves re-engineering entire legacy systems (e.g., changing the technology stack, migrating to a new architecture style, or programming paradigms). Given the pervasive nature of software today, modernizing legacy systems is paramount to provide customers with competitive and innovative products and services, while keeping companies profitable. Despite the prevalent discussion of software modernization in gray literature, and the many papers in the literature, there is no work presenting a “big picture” of contemporary software modernization, describing challenges, and providing a well-defined research agenda. The goal of this work is to describe the state of the art in software modernization in the past 10 years. We collect the state of the art by performing a rapid review (searching five digital libraries), identifying potential 3,460 studies, leading to a final set of 127. We analyzed these studies to understand which strategies are employed, the driving forces that lead organizations to modernize their systems, and the challenges that need to be addressed. The results show that studies in the last 10 years have explored eight strategies for modernizing legacy systems, namely cloudification, architecture redesign, moving to a new programming language, targeting reuse optimization, software modernization for new hardware integration, practices to leverage automation, database modernization, and digital transformation. Modernization is triggered by 14 driving forces, with the most common ones being reducing operational costs, improving performance and scalability, and reducing complexity. In addition, based on the analysis of existing literature, we present a detailed discussion of research opportunities in this field. The main challenges are providing tooling support, followed by defining a modernization process and considering better evaluation metrics. The main contribution of our work is to equip practitioners and researchers with knowledge of the current state of contemporary software modernization so that they are aware of practices and challenges to be addressed when deciding to modernize legacy systems.

Accurate Indoor Localization with IoT Devices and Advanced Fingerprinting Methods

The Internet of things (IoT) has significantly impacted various sectors, including healthcare, environmental monitoring, transportation, and commerce, by enhancing communication networks through the integration of sensors, software, and hardware. This paper presents an accurate IoT indoor localization system based on IoT devices and fingerprinting methods. We explore indoor localization techniques using Bluetooth Low Energy (BLE) and a Radio Signal Strength Indicator (RSSI) to address the limitations of GPS in indoor environments. The study evaluates the effectiveness of iBeacon transmitters for indoor positioning, comparing the Weighted Centroid Localization (WCL) and Positive Weighted Centroid Localization (PWCL) algorithms, along with fingerprinting methods enhanced by outlier detection and mapping filters. Our methodology includes mapping a real environment onto a coordinate axis, collecting training data from 47 sampling points, and implementing four localization algorithms. The results show that the PWCL algorithm improves accuracy over the WCL algorithm, and hybrid methods further reduce localization errors. The HYBRID-MAPPED method achieves the highest accuracy, with an average error of 1.44 m.

Green Cloud Technologies for SAP-driven Enterprises

Green Cloud Technologies are rapidly transforming the landscape of enterprise IT solutions, particularly for SAP-driven businesses. As organizations increasingly turn to cloud computing for its scalability, flexibility, and cost-efficiency, the environmental impact of traditional data centers has raised significant concerns. Green Cloud Technologies aim to address these concerns by leveraging sustainable practices, renewable energy sources, and energy-efficient infrastructures in cloud data centers. For SAP-driven enterprises, which rely on complex, resource-intensive business processes, adopting green cloud solutions offers a dual benefit: reducing operational costs while supporting corporate sustainability goals. This paper explores the role of Green Cloud Technologies in SAP environments, highlighting the integration of energy-efficient systems, eco-friendly hardware, and sustainable cloud services. It also examines best practices for SAP-driven enterprises to optimize resource usage, minimize carbon footprints, and align with global environmental standards. By adopting Green Cloud solutions, businesses not only contribute to environmental conservation but also enhance their competitiveness by aligning with increasingly stringent regulatory requirements and stakeholder expectations for sustainability.

A Moderna Aviônica – Um Desafio

The article explores the progress of avionics, emphasizing how microelectronics has enabled the development of advanced systems in military aircraft. With an increasing need to reduce space and weight while enhancing capacity and reliability, armed forces have adopted on-board computers to manage complex weapon and flight control systems. The application of new technologies has introduced logistical and operational challenges, requiring adaptations in both maintenance and personnel training. The integration of software and hardware has revolutionized the operation of aircraft like the F-15 and F-16, redefining the concept of "black boxes" in aviation.

Quantum Computing in Medicine.

Quantum computing (QC) represents a paradigm shift in computational power, offering unique capabilities for addressing complex problems that are infeasible for classical computers. This review paper provides a detailed account of the current state of QC, with a particular focus on its applications within medicine. It explores fundamental concepts such as qubits, superposition, and entanglement, as well as the evolution of QC from theoretical foundations to practical advancements. The paper covers significant milestones where QC has intersected with medical research, including breakthroughs in drug discovery, molecular modeling, genomics, and medical diagnostics. Additionally, key quantum techniques such as quantum algorithms, quantum machine learning (QML), and quantum-enhanced imaging are explained, highlighting their relevance in healthcare. The paper also addresses challenges in the field, including hardware limitations, scalability, and integration within clinical environments. Looking forward, the paper discusses the potential for quantum-classical hybrid systems and emerging innovations in quantum hardware, suggesting how these advancements may accelerate the adoption of QC in medical research and clinical practice. By synthesizing reliable knowledge and presenting it through a comprehensive lens, this paper serves as a valuable reference for researchers interested in the transformative potential of QC in medicine.

Real-Time Industrial Data Analysis and Visualization

In the era of Industry 4.0, real-time data monitoring and analysis have become essential for enhancing operational efficiency and decision-making in industrial environments. This project focuses on the development of a comprehensive system for visualizing and analyzing real-time industrial data using a DHT11 sensor, which measures temperature and humidity. The collected data is transmitted and visualized through a dynamic web interface built on MyPHPAdmin, enabling users to access and interpret data seamlessly. The visualization aspect of the project aims to present the data in an intuitive format, allowing stakeholders to monitor environmental conditions effectively. Following the visualization phase, the data will undergo thorough analysis using advanced tools like Tableau and Excel, providing insights into patterns, trends, and anomalies in the industrial setting. This project not only demonstrates the integration of hardware and software technologies for real-time data management but also emphasizes the importance of data visualization and analysis in optimizing industrial processes. Ultimately, it serves as a foundation for further research and development in the field of industrial automation and data-driven decision-making.

Upper instrumented vertebra pedicle screw loosening following adult spinal deformity surgery: incidence and outcome analysis.

Surgical correction of adult spinal deformity (ASD) is associated with a high rate of hardware complication that can be challenging to predict. Hardware integrity and alignment after surgery are typically followed with standing radiography, where pedicle screw loosening may be incidentally identified but the clinical significance of which is often unclear. This study aimed to identify the incidence and implications of pedicle screw loosening at the upper instrumented vertebra (UIV) after surgical correction of ASD. A single-institution retrospective analysis was performed on a cohort of 217 patients who underwent long-segment fusion with pelvic fixation for correction of ASD between September 2013 and November 2021. Cases with a minimum 1-year follow-up were included. UIV pedicle screws were graded on radiographs for evidence of loosening with a 0- to 3-point scale: 0, no loosening; 1, lucency within screw threads; 2, lucency around screw threads; and 3, screw dislodgment/backout. Need for hardware revision surgery was assessed as the primary outcome. Patient-reported outcome measures (PROMIS and Oswestry Disability Index scores) were assessed as secondary outcomes among the patients with available scores. Low-grade UIV screw loosening (grade 1) was identified in 37 patients (17.1%), and high-grade UIV loosening (grade 2 or 3) was identified in 23 patients (10.6%). Low-grade UIV loosening was not associated with eventual need for hardware revision (OR 0.52, 95% CI 0.17-1.61, p = 0.258); however, high-grade loosening was associated with increased odds of hardware revision (OR 5.17, 95% CI 1.74-15.36, p = 0.003), including specifically surgery for correction of proximal junctional kyphosis (OR 5.73, 95% CI 1.27-25.95, p = 0.024). Among patients with PROMIS T-scores, those requiring hardware revision reported worse Pain Interference (65.0 ± 5.1 vs 59.6 ± 7.7, p = 0.001) and Physical Function (33.3 ± 5.6 vs 37.4 ± 7.4; p = 0.011). Patients with high-grade UIV loosening reported higher Oswestry Disability Index scores than those without high-grade loosening (grade 0 or 1), although this failed to reach statistical significance (44.0 ± 8.5 vs 33.7 ± 18.5, p = 0.101). Grade 1 UIV pedicle screw loosening may represent a benign incidental finding, whereas high-grade loosening is associated with significantly increased odds of hardware revision surgery. High-grade loosening may also be associated with worse patient-reported disability. The authors' findings suggest that while low-grade UIV loosening may often be managed expectantly, identification of high-grade UIV pedicle screw loosening on follow-up imaging warrants increased attention and continued surveillance.

Designing a Compact Portable Electro-Cardio Device Enhanced by Machine Learning for Early Detection of Myocardial Infraction

Cardiovascular diseases remain one of the leading causes of death globally, underscoring the need for accessible, efficient, and accurate methods of heart health monitoring. Traditional heart monitoring tools, often confined to clinical settings, limit the ability to perform continuous, real-time assessments of heart function. This challenge has driven the demand for innovative, portable solutions that enable early detection and proactive management of heart conditions. The Heart Box project aims to revolutionize cardiac health monitoring through a portable, AI-integrated system that provides real-time analysis of electrocardiogram signals. Leveraging precision healthcare technology, this device enables early detection of heart conditions by continuous monitoring. Our ground breaking project encountered two primary challenges: establishing reliable hardware connections for data capture and sourcing appropriate datasets to train our Convolutional Neural Network model. Overcoming the intricacies of hardware integration demanded meticulous troubleshooting and innovative solutions to ensure seamless data acquisition. Additionally, identifying and curating high-quality datasets posed a significant hurdle, requiring exhaustive research and data pre-processing efforts. Despite these challenges, our perseverance and dedication led to the successful development of a robust Convolutional Neural Network model, revolutionizing cardiac assessment by leveraging cutting-edge technology and data-driven insights.

Rancang Bangun Sistem Pengontrol PH Air Minum dari Water Treatment Kapal Menggunakan Micro Controller ESP 32

In order for life to exist on Earth, water is required and is particularly important on ships. Concerns about water scarcity arise because water resources cannot always meet demand. pH has an impact on the quality of drinking water, with an ideal range between 6.5-8.5. Alkaline water with a pH of 8.8 has health benefits, including helping to lower stomach acid and improve body oxygenation. The pH of drinking water recommended by the EPA is between 6.5-8.5 to ensure safe consumption. pH is a measure of the acidity or basicity of water, on a scale of 0-14, where 7 is considered neutral. The research plans to make a drinking water pH control system using an ESP 32 microcontroller. This research aims to control also monitor the pH of drinking water efficiently using ESP 32 microcontroller. This research uses the Research and Development (R&D) method to design pH control in drinking water solutions. The phases of the research include using a pH sensor to detect pH values, using an ESP 32 microcontroller to control pH, and validating and improving the product model. Overall system testing in the design of a drinking water pH controller system from water treatment is an important stage to ensure successful integration between all components and desired functionality. This testing process includes several main stages, Hardware Integration Testing: All hardware is physically connected and integrated, including ESP32, relays, solenoid valves, and pH sensors. This test is taken to ensure that all components are properly installed and interact with each other correctly. Software Integration Testing: This type of testing verifies that all features and functions of the system function as intended by the software program responsible for it. This includes testing Wi-Fi connections, integration with the Blynk platform, and programming logic as an automatic water controller. Testing System Functionality: to ensure that the intended features can be run properly, the system is tested in various usage scenarios. This includes testing the water controller automatically. the designed system can function normally and adjust appropriately to the designed controller system. From the data obtained regarding the performance results of the system built, it was found that the pH controller system can be run automatically based on the water that has been set as the set point of the system created. The monitoring system with IoT is also able to run well. The time needed will be more to control the pH in the range of 6.5-8.5.

Standardized research on multifunctional beacon multi-sensor data acquisition and transmission

Abstract This paper discusses the research on the standardization of data acquisition and transmission for multifunctional beacon systems. The multifunctional beacon system integrates various types of sensing devices and can provide real-time, comprehensive and accurate marine environment and navigation information for ships and shore-based users. However, the system currently faces challenges such as non-uniform data formats and communication protocols, low hardware standardization and integration, and data and network security risks. In order to solve these problems, this paper puts forward the solution of “standard terminal for data acquisition and transmission”, which achieves the compatibility of equipment interface, unified data format, and reliable information security. It lays the foundation for the standardization of multi-purpose beacon system. Through modular design and standardized packaging, the performance, reliability and efficiency of the hardware of multi-purpose beacons are improved, the development and maintenance costs are reduced, and the flexibility of the system is enhanced. The “Standard Terminal for Data Acquisition and Transmission” is applied to the multi-purpose beacon system, and interfaces and integrates with the existing “Operation Management System for Navigation Guarantee” to realize a unified platform for multi-purpose beacons. This research helps to promote the formulation of multi-purpose beacon data format and communication protocol standards at the national or industrial level, provides important reference for the formulation of international standards, and is of great significance in promoting the standardized development and application promotion of multi-purpose beacon technology.

Quantum Machine Learning: Bridging Quantum Computing and Artificial Intelligence

Abstract: This comprehensive article explores the burgeoning field of Quantum Machine Learning (QML), examining its foundational principles, key algorithms, and potential applications. We delve into the fundamentals of quantum computing, including qubits, quantum gates, and the challenges of quantum measurement and decoherence. The article provides an indepth analysis of Quantum Support Vector Machines (QSVM) and Quantum Neural Networks (QNN), comparing them with their classical counterparts and highlighting their unique advantages and limitations. We investigate the promising applications of QML in material science, cryptography, and optimization problems, showcasing its potential to revolutionize drug discovery, secure communication, and complex problem-solving. The review also addresses the significant challenges facing QML, including hardware constraints, error correction, algorithm development, and integration with classical systems. By synthesizing current research and identifying future directions, this article offers a comprehensive overview of QML's transformative potential in artificial intelligence and computational science, while acknowledging the hurdles that must be overcome to fully realize its capabilities.

High-coherence parallelization in integrated photonics

Coherent optics has profoundly impacted diverse applications ranging from communications, LiDAR to quantum computations. However, developing coherent systems in integrated photonics comes at great expense in hardware integration and energy efficiency. Here we demonstrate a high-coherence parallelization strategy for advanced integrated coherent systems at minimal cost. By using a self-injection locked microcomb to injection lock distributed feedback lasers, we achieve a record high on-chip gain of 60 dB with no degradation in coherence. This strategy enables highly coherent channels with linewidths down to 10 Hz and power over 20 dBm. The overall electrical-to-optical efficiency reaches 19%, comparable to that of advanced semiconductor lasers. This method supports a silicon photonic communication link with an unprecedented data rate beyond 60 Tbit/s and reduces phase-related DSP consumption by 99.99999% compared to traditional III-V laser pump schemes. This work paves the way for realizing scalable, high-performance coherent integrated photonic systems, potentially benefiting numerous applications.

Optimising structural health monitoring systems: A 2D numerical investigation on impedance matching for FML with integrated sensors

AbstractFibre metal laminates (FML) represent an innovative class of advanced composite materials that integrate the mechanical properties of both metals and fibre‐reinforced composites (FRP). Combining the strength and ductility of metals with the lightweight and high stiffness of FRP and FMLs have emerged as new material compositions for applications in chemical, nuclear, automobile, and aerospace engineering disciplines. Structural health monitoring (SHM) using guided ultrasonic waves (GUW) is the state‐of‐the‐art for non‐destructive testing of thin‐walled structures. When applied to FML, SHM plays a crucial role in monitoring the integrity over time and detecting potential damage such as delamination, fibre breakage, or other structural anomalies. In SHM with GUW, a wave‐field is emitted by actuators. This wave‐field can be affected by damage in the structure, thereby changing its propagation characteristics. Sensors monitor the interaction between damage and GUW, which can be utilized to locate and classify the damage and ascertain the overall health state of the structure. In this study, an advanced integration of measurement hardware, that is, sensors and actuators, within the laminate structure is investigated. Sensor integration into FML allows for improved and more sophisticated monitoring capabilities in comparison to measuring techniques like laser vibrometers, which are limited to measuring displacements on the surface of the structure. However, the integration of sensors and actuators yields the technical difficulty of distorting the wave‐fields and may result in an over‐ or underestimation of the damage. Similar to damage, the distortion of the wave‐field is caused by the changes in acoustic impedance resulting from different material properties. In a previous study, incorporating a functionally graded artificial interphase through acoustic impedance matching between the sensor and host material showed notable and significant outcomes. The current contribution extends the prior graded artificial interphase for an isotropic homogeneous material to an FML structure. This paper presents a comprehensive numerical simulation study on a two‐dimensional model of FML with integrated sensors. The interphases are designed based on impedance matching, which improves signal transmission and reduces disturbing reflections. The conducted investigations hold for several interphase configurations for a wide frequency range. The optimised integration of sensors demonstrates promising results for enhancing the reliability and accuracy of SHM systems. This research serves as a foundation for further experimental validation and the development of advanced sensor‐integrated FML structures with improved monitoring capabilities.

Wearable bio-adhesive metal detector array (BioMDA) for spinal implants

Dynamic tracking of spinal instrumentation could facilitate real-time evaluation of hardware integrity and in so doing alert patients/clinicians of potential failure(s). Critically, no method yet exists to continually monitor the integrity of spinal hardware and by proxy the process of spinal arthrodesis; as such hardware failures are often not appreciated until clinical symptoms manifest. Accordingly, herein, we report on the development and engineering of a bio-adhesive metal detector array (BioMDA), a potential wearable solution for real-time, non-invasive positional analyses of osseous implants within the spine. The electromagnetic coupling mechanism and intimate interfacial adhesion enable the precise sensing of the metallic implants position without the use of radiation. The customized decoupling models developed facilitate the precise determination of the horizontal and vertical positions of the implants with incredible levels of accuracy (e.g., <0.5 mm). These data support the potential use of BioMDA in real-time/dynamic postoperative monitoring of spinal implants.

Curved HSIW: an affordable performance for non-planar millimeter-wave applications

This paper introduces a Curved Hollow Substrate Integrated Waveguide (CHSIW) to address the growing demand for millimeter-wave applications, including communication, sensing, imaging, radar, and wireless power transfer systems. Leveraging advancements in integrated circuits and system-in-package (SiP) technology, the CHSIW tackles the challenges associated with hardware integration into curved structures. The design utilizes MultiJet Printing (MJP) for the M3 crystal dielectric substrate and a water laser cutter system for copper sheets, streamlining the fabrication process by eliminating complex via manufacturing steps through prefabricated through-hole vias. Operating in the frequency range of 21.7 GHz to 32 GHz, the CHSIW exhibits outstanding performance on curved surfaces, with measured average attenuation constants of 1.89 Np m−1 (16.42 dB m−1) and 1.95 Np m−1 (16.94 dB/m) for samples with radii of curvature of 166.8 mm and 125.1 mm, respectively. Beyond addressing technical challenges, the CHSIW presents a cost-effective and simplified fabrication process, positioning it as a breakthrough solution for diverse millimeter-wave applications, including future robotic and UAV communications. Furthermore, the proposed design and fabrication technique hold promise for the realization of conformal and free-form Hollow Substrate Integrated Waveguide (HSIW) devices in the future.

Lógica de programação através da robótica: Uso do Scratch e Arduino para criação de robôs e projetos interativos

This article investigates the teaching of programming logic through robotics, using Scratch and Arduino for the creation of robots and interactive projects. Through a literature review, we examine the advantages and challenges of this approach, highlighting how the integration of visual programming tools and hardware can enrich student learning. The integration of Scratch and Arduino in education emerges as an innovative approach to teaching programming logic. Scratch, a visual programming language, and Arduino, an open-source electronics platform, provide students with a dynamic and interactive learning environment. Through hands-on projects and real-time feedback, students can explore abstract concepts in a tangible way, enhancing their understanding and knowledge retention. Despite the challenges, such as teacher training and the availability of resources, the benefits of using Scratch and Arduino outweigh the difficulties, providing students with engaging and meaningful learning experiences. This article reviews the literature on the use of Scratch and Arduino in education, highlighting their contributions to programming education and project-based learning. The results indicate that the use of Scratch and Arduino promotes a dynamic and engaging learning environment, facilitating the understanding of programming and electronics concepts. Future research should focus on strategies to improve teacher education and expand access to these tools, ensuring that all students have the opportunity to develop essential digital literacy skills. By empowering students to become creators and innovators, Scratch and Arduino pave the way for a future where technology is not only understood, but is also actively shaped and utilized for positive change.