Search Results (1,421)

A principal factor of the fourth Industrial Revolution is the Internet of Things (IoT), a network of “smart” objects that communicate by exchanging helpful information about themselves and their environment. Our research aims to address the gaps in the existing literature regarding the educational and technological affordances of IoT applications in learning environments in secondary education. Our systematic review using the PRISMA method allowed us to extract 25 empirical studies from the last 10 years. We present the categorization of educational and technological affordances, as well as the devices used in these environments. Moreover, our findings indicate widespread adoption of organized educational activities and design-based learning, often incorporating tangible interfaces, smart objects, and IoT applications, which enhance student engagement and interaction. Additionally, we identify the impact of IoT-based learning on knowledge building, autonomous learning, student attitude, and motivation. The results suggest that the IoT can facilitate personalized and experiential learning, fostering a more immersive and adaptive educational experience. Based on these findings, we discuss key recommendations for educators, policymakers, and researchers, while also addressing this study’s limitations and potential directions for future research. Full article

The increase in the number of wildfires in recent years in different parts of the world has caused growing concern among the population, since the consequences of these fires go beyond the destruction of the ecosystem. With the growing relevance of the Internet of Things (IoT) industry, developing solutions for the early detection of fires is of critical importance. This paper proposes a low-cost network based on Long-Range (LoRa) technology to autonomously assess the level of fire risk and the presence of a fire in rural areas. The system consists of several LoRa nodes with sensors to measure environmental variables such as temperature, humidity, carbon monoxide, air quality, and wind speed. The data collected is sent to a central gateway, where it is stored, processed, and later sent to a website for graphical visualization of the results. In this paper, a survey of the requirements of the devices and sensors that compose the system was made. After this survey, a market study of the available sensors was carried out, ending with a comparison between the sensors to determine which ones met the objectives. Using the chosen sensors, a study was made of possible power solutions for this prototype, considering the expected conditions of use. The system was tested in a real environment, and the results demonstrate that it is possible to cover a circular area with a radius of 2 km using a single gateway. Our system is prepared to trigger fire hazard alarms when, for example, the signals for relative humidity, ambient temperature, and wind speed are below or equal to 30%, above or equal to 30 °C, and above or equal to 30 m/s, respectively (commonly known as the 30-30-30 rule). Full article

This study presents a compact and high-efficiency microstrip antenna integrated with a square electromagnetic band-gap (EBG) structure for radio frequency energy harvesting to power battery-less Internet of Things (IoT) sensors and medical devices in the 5.8 GHz Industrial, Scientific, and Medical (ISM) band. The proposed antenna features a compact design with reduced physical dimensions of 36 × 40 mm² (0.69λ_o × 0.76λ_o) while providing high-performance parameters such as a reflection coefficient of −27.9 dB, a voltage standing wave ratio (VSWR) of 1.08, a gain of 7.91 dBi, directivity of 8.1 dBi, a bandwidth of 188 MHz, and radiation efficiency of 95.5%. Incorporating EBG cells suppresses surface waves, enhances gain, and optimizes impedance matching through 50 Ω inset feeding. The simulated and measured results of the designed antenna show a high correlation. This study demonstrates a robust and promising solution for high-performance wireless systems requiring a compact size and energy-efficient operation. Full article

Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to support efficient city management and foster citizen engagement. Often referred to as digital cities, they integrate intelligent infrastructures and real-time data analytics to improve mobility, security, and sustainability. Ubiquitous sensors, paired with Artificial Intelligence, enable cities to monitor infrastructure, respond to residents’ needs, and optimize urban conditions dynamically. Given the increasing significance of Industry 4.0 in urban development, this study adopts a bibliometric approach to systematically review the application of these technologies within smart cities. Utilizing major academic databases such as Scopus and Web of Science the research aims to identify the primary Industry 4.0 technologies implemented in smart cities, assess their impact on infrastructure, economic systems, and urban communities, and explore the challenges and benefits associated with their integration. The bibliometric analysis included publications from 2016 to 2023, since the emergence of urban researchers’ interest in the technologies of the new industrial revolution. The task is to contribute to a deeper understanding of how smart cities evolve through the adoption of advanced technological frameworks. Research indicates that IoT and AI are the most commonly used tools in urban spaces, particularly in smart mobility and smart environments. Full article

In recent years, the Internet of Things (IoT) has experienced considerable developments and has played an important role in various domains such as industry, agriculture, healthcare, transportation, and environment, especially for smart cities. Along with that, wireless sensor networks (WSNs) are considered to be important components of the IoT system (WSN-IoT) to create smart applications and automate processes. As the number of connected IoT devices increases, privacy and security issues become more complicated due to their external working environments and limited resources. Hence, solutions need to be updated to ensure that data and user privacy are protected from threats and attacks. To support the safety and reliability of such systems, in this paper, security issues in the WSN-IoT are addressed and classified as identifying security challenges and requirements for different kinds of attacks in either WSNs or IoT systems. In addition, security solutions corresponding to different types of attacks are provided, analyzed, and evaluated. We provide different comparisons and classifications based on specific goals and applications that hopefully can suggest suitable solutions for specific purposes in practical. We also suggest some research directions to support new security mechanisms. Full article

The current paper presents a comprehensive intelligent system designed to optimize the performance of a barrier eddy current separator (BECS), comprising a conveyor belt, a vibration feeder, and a magnetic drum. This system was trained and validated on real-world industrial data gathered directly from the working separator under 81 different operational scenarios. The intelligent models were used to recommend optimal settings for drum speed, belt speed, vibration intensity, and drum angle, thereby maximizing separation quality and minimizing energy consumption. the smart separation module utilizes YOLOv11n-seg and achieves a mean average precision (mAP) of 0.838 across 7163 industrial instances from aluminum, copper, and plastic materials. For shape classification (sharp vs. smooth), the model reached 91.8% accuracy across 1105 annotated samples. Furthermore, the thermal monitoring unit can detect iron contamination by analyzing temperature anomalies. Scenarios with iron showed a maximum temperature increase of over 20 °C compared to clean materials, with a detection response time of under 2.5 s. The architecture integrates a Digital Twin using Azure Digital Twins to virtually mirror the system, enabling real-time tracking, behavior simulation, and remote updates. A full connection with the PLC has been implemented, allowing the AI-driven system to adjust physical parameters autonomously. This combination of AI, IoT, and digital twin technologies delivers a reliable and scalable solution for enhanced separation quality, improved operational safety, and predictive maintenance in industrial recycling environments. Full article

Radio frequency (RF)-based wireless systems are broadly used in communication systems such as mobile networks, satellite links, and monitoring applications. These systems offer outstanding advantages over wired systems, particularly in terms of ease of installation. However, researchers are looking for safer alternatives as a result of worries about possible health problems connected to high-frequency radiofrequency transmission. Using the visible light spectrum is one promising approach; three cutting-edge technologies are emerging in this regard: Optical Camera Communication (OCC), Light Fidelity (Li-Fi), and Visible Light Communication (VLC). In this paper, we propose a Multiple-Input Multiple-Output (MIMO) modulation technology for Internet of Things (IoT) applications, utilizing an LED array and time-domain on-off keying (OOK). The proposed system is compatible with both rolling shutter and global shutter cameras, including commercially available models such as CCTV, webcams, and smart cameras, commonly deployed in buildings and industrial environments. Despite the compact size of the LED array, we demonstrate that, by optimizing parameters such as exposure time, camera focal length, and channel coding, our system can achieve up to 20 communication links over a 20 m distance with low bit error rate. Full article

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0. Full article

Energy-intensive industries (EIIs) face mounting pressure to reduce greenhouse gas emissions while maintaining international competitiveness—a balance that is central to achieving the EU’s 2030 and 2050 climate objectives. In this context, energy management (EM) emerges as a strategic instrument to decouple industrial growth from fossil energy consumption. This study proposes a redefinition of EM to support carbon-neutral supply chains within the European Union’s EIIs, addressing critical limitations of conventional EM frameworks under increasingly stringent carbon regulations. Using a modified systematic literature review based on PRISMA methodology, complemented by expert insights from EU Member States, this research identifies structural gaps in current EM practices and highlights opportunities for integrating sustainable innovations across the whole industrial value chain. The proposed EM concept is validated through an analysis of 24 EM definitions, over 170 scientific publications, and over 80 EU legal and strategic documents. The framework incorporates advanced digital technologies—including artificial intelligence (AI), the Internet of Things (IoT), and big data analytics—to enable real-time optimisation, predictive control, and greater system adaptability. Going beyond traditional energy efficiency, the redefined EM encompasses the entire energy lifecycle, including use, transformation, storage, and generation. It also incorporates social dimensions, such as corporate social responsibility (CSR) and stakeholder engagement, to cultivate a culture of environmental stewardship within EIIs. This holistic approach provides a strategic management tool for optimising energy use, reducing emissions, and strengthening resilience to regulatory, environmental, and market pressures, thereby promoting more sustainable, inclusive, and transparent supply chain operations. Full article

As industrial companies transition from the Industry 4.0 stage to the more human-centric and resilient Industry 5.0 paradigm, there is a growing need for structured assessment tools to prioritize modern technologies. This paper presents an integrated multi-criteria decision analysis (MCDA) approach to support the strategic assessment of technologies from three complementary perspectives: economic, organizational, and technological. The proposed model encompasses six key transformation areas and 22 technologies representing both the Industry 4.0 and 5.0 paradigms. A hybrid approach combining the DEMATEL (Decision-Making Trial and Evaluation Laboratory) and PROMETHEE II (Preference Ranking Organization Method for Enrichment Evaluation) methods is used to identify cause–effect relationships between the transformation areas and to construct technology rankings in each of the assessed perspectives. The results indicate that technologies such as the Internet of Things (IoT), cybersecurity, and supporting IT systems play a central role in the transition process. Among the Industry 5.0 technologies, hyper-personalized manufacturing, smart grids and new materials stand out. Moreover, the economic perspective emerges as the dominant assessment dimension for most technologies. The proposed analytical framework offers both theoretical input and practical decision-making support for companies planning their transformation towards Industry 5.0, enabling a stronger alignment between implemented technologies and long-term strategic goals. Full article

This study conducts a comprehensive systematic review of the economic impact of Digital Twin (DT) technology within the Architecture, Engineering, and Construction (AEC) industry, following the PRISMA methodology. While DT adoption has been accelerated by advancements in Building Information Modelling (BIM), the Internet of Things (IoT), and data analytics, significant challenges persist—most notably, high initial investment costs and integration complexities. Synthesising the literature from 2016 onwards, this review identifies sector-specific barriers, regulatory burdens, and a lack of standardisation as key factors constituting DT implementation costs. Despite these hurdles, DTs demonstrate strong potential for enhancing construction productivity, optimising lifecycle asset management, and enabling predictive maintenance, ultimately reducing operational expenditures and improving long-term financial performance. Case studies reveal cost efficiencies achieved through DTs in modular construction, energy optimisation, and infrastructure management. However, limited financial resources and digital skills continue to constrain the uptake across the sector, with various extents of impact. This paper calls for the development of unified standards, innovative public–private funding mechanisms, and strategic collaborations to unlock and utilise DTs’ full economic value. It also recommends that future research explore theoretical frameworks addressing governance, data infrastructure, and digital equity—particularly through conceptualising DT-related data as public assets or collective goods in the context of smart cities and networked infrastructure systems. Full article

The proliferation of Internet of Things (IoT) swarms—comprising billions of low-end interconnected embedded devices—has transformed industrial automation, smart homes, and agriculture. However, these swarms are highly susceptible to firmware anomalies that can propagate across nodes, posing serious security threats. To address this, we propose a novel Remote Attestation (RA) framework for real-time firmware verification, leveraging Relational Graph Neural Networks (RGNNs) to model the graph-like structure of IoT swarms and capture complex inter-node dependencies. Unlike conventional Graph Neural Networks (GNNs), RGNNs incorporate edge types (e.g., Prompt, Sensor Data, Processed Signal), enabling finer-grained detection of propagation dynamics. The proposed method uses runtime Static Random Access Memory (SRAM) data to detect malicious firmware and its effects without requiring access to firmware binaries. Experimental results demonstrate that the framework achieves 99.94% accuracy and a 99.85% anomaly detection rate in a 4-node swarm (Swarm-1), and 100.00% accuracy with complete anomaly detection in a 6-node swarm (Swarm-2). Moreover, the method proves resilient against noise, dropped responses, and trace replay attacks, offering a robust and scalable solution for securing IoT swarms. Full article

Amid the accelerated digital transformation and with the growing demand for smart manufacturing, the applications of the Internet of Things (IoT) and total quality management (TQM) have attracted increasing attention. Using R for bibliometric analysis, we explored research trends in IoT and TQM in terms of digital transformation and smart manufacturing. Data were gathered from the Web of Science from 1998 to 2025, with a total of 787 publications from 265 sources involving 2326 authors. A total of 31% of the authors collaborated internationally, indicating global interest in this topic. The publications had 33.65 citations on average, totaling 33,599 citations. Wang L.H. and Tao F. were identified as important authors. Keywords of “Industry 4.0”, “cyber-physical systems”, and “big data” underscore the technological significance of IoT and TQM. Major journals such as the Journal of Manufacturing Systems and IEEE Access had notable academic influence. Co-citation analysis results revealed that IoT and TQM played a significant role in driving digital transformation and enhancing production efficiency, offering references for enterprises in strategic planning for smart manufacturing. Full article

There is a growing pressure on industry to secure environments and demonstrate their commitment in taking right steps to secure their products. This is because of the growing number of security compromises in the IT industry, Operational Technology environment, Internet of Things environment and smart home devices. These compromises are not just about data breaches or data exfiltration, but also about unauthorised access to devices that are not configured correctly and vulnerabilities in software components, which usually lead to insecure authentication and authorisation. Incorrect configurations are usually in the form of devices being made available on the Internet (public domain), reusable credentials, access granted without verifying the requestor, and easily available credentials like default credentials. Organisations seeking to address the dual pressure of demonstrating steps in the right direction and addressing unauthorised access to resources can find a viable approach in the form of the zero trust concept. Zero trust principles are about moving security controls closer to the data, applications, assets and services and are based on the principle of “never trust, always verify”. As it stands today, zero trust research has advanced far beyond the concept of “never trust, always verify”. This paper provides the culmination of a literature review of research conducted in the space of smart home devices and IoT and the applicability of the zero trust five-step implementation process to secure them. We discuss the history of zero trust, the tenets of zero trust, the five-step implementation process for zero trust, and its adoption for smart home devices and Internet of Things, and we provide suggestions for future research. Full article

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article