Search Results (5,076)

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

This study explores the complex interaction between the Internet of Things (IoT) and the new energy sector and analyzes how their integration can catalyze a transition toward a sustainable low-carbon economy. Through the full-sample and rolling sub-sample methods, we empirically examine the dynamic interrelationship between China’s IoT index (IoT) and the New Energy Index (NEI). Quantitative analysis reveals significant time-varying characteristics and bidirectional causal complexity in the interaction between the IoT and new energy. The IoT has a dual-edged impact on the development of new sources of energy. In the long run, the IoT plays a dominant role in incentivizing new energy, helping to enhance its stability and economic value. However, during stages characterized by technological bottlenecks or resource competition, the high energy consumption of IoT infrastructure may suppress the investment returns of new energy. Simultaneously, new energy has both positive and negative impacts on the IoT. On the one hand, new energy provides low-cost, sustainable power to support the IoT, driving the construction of the IoT ecosystem. On the other hand, it may threaten the continuity of IoT power supply, and the complexity of standardization and regulation in the sector may constrain the development of the IoT. This study provides a fresh perspective on promoting the integration of digital technology and green energy, uncovering nonlinear trade-offs between innovation-driven growth and carbon reduction goals, and offering policy insights for cross-sectoral collaboration to achieve sustainability. Full article

The digital wave, represented by new technologies such as big data, IoT, and artificial intelligence, is sweeping the globe, driving all industries toward digitalization and intelligent transformation. Digital twins are becoming an indispensable opportunity for new infrastructure initiatives. As geotechnical engineering constitutes a critical component of new infrastructure, its corresponding digital transformation is essential to align with these initiatives. However, due to the difficulty of modeling, the demand for computing resources, interdisciplinary integration, and other issues, current digital twin applications in geotechnical engineering remain in their nascent stage. This paper delineates the developmental status of geotechnical digital twin technology in China, and it focuses on the advantages and disadvantages of digital twins in five application fields, identifying key challenges, including intelligent sensing and interconnectivity of multi-source heterogeneous physical entities, integrated sharing of 3D geological models and structural models, unified platforms for lifecycle information management, standardization of digital twin data protocols, and theoretical frameworks for digital twin modeling. Furthermore, this study systematically expounds future research priorities across four dimensions: intelligent sensing and interoperability technologies for geotechnical engineering; knowledge graph development and model-based systems engineering; integrated digital twin entity technologies combining 3D geological bodies with engineering structures; and precision enhancement, temporal extension, and spatial expansion of geotechnical digital twins. This paper systematically reviews the application status of digital twin technology in geotechnical engineering for the first time, reveals the common technical challenges in cross-domain implementation, and proposes a theoretical framework for digital twin accuracy improvement and spatiotemporal expansion for geotechnical engineering characteristics, which fills the knowledge gap in the adaptability of existing research in professional fields. These insights aim to provide references for advancing digitalization, intelligent transformation, and sustainable development of geotechnical engineering. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

The objective of this research was to conduct a comprehensive review of rainbow trout (Oncorhynchus mykiss) culture in recirculating aquaculture systems (RAS), identify knowledge gaps, and propose strategies oriented towards intelligent and sustainable aquaculture. A systematic review and bibliometric analysis of 387 articles published between 1941 and 2025 in the Scopus database was carried out. Since 2011, there has been a sustained growth in scientific production, with the United States, Denmark, Finland, and Germany standing out as the main contributors. The journals with the highest number of publications were Aquacultural Engineering, Aquaculture, and Aquaculture Research. The conceptual analysis revealed the following three thematic clusters: experimental studies on physiology and metabolism; research focused on nutrition, growth, and yield; and technological developments for water treatment in RAS. This evolution reflects a transition from basic approaches to applied technologies oriented towards sustainability. There was also evidence of a thematic transition toward molecular tools such as proteomics, transcriptomics, and real-time PCR. However, there is still limited integration of smart technologies such as the IoT. It is recommended to incorporate self-calibrating multi-parametric sensors, machine learning models, and autonomous systems for environmental regulation in real time. Full article

This review investigates the application of Artificial Intelligence (AI), deep learning (DL), and the Internet of Things (IoT) in water resource management, focusing on distribution optimization, demand prediction, and water quality enhancement. The study synthesizes findings from 2015 to 2024, encompassing experimental and applied research published in English or French in recognized scientific outlets. By analyzing the prevalent algorithms, IoT technologies, and their impacts, this systematic review highlights research gaps and proposes directions for future work. The results show significant advancements in predictive analytics and real-time monitoring through AI and the IoT. However, challenges remain in scalability, interdisciplinary integration, and contextual adaptation. Full article

A novel approach to managing domestic heating systems through IoT technologies is introduced in this paper. The system optimizes energy consumption by dynamically adapting to electricity and fuel price fluctuations while maintaining user comfort. Integrating smart devices significantly reduce energy costs and offer a favorable payback period, positioning the solution as both sustainable and economically viable. Efficient heating management is increasingly critical amid growing energy and environmental concerns. This strategy uses IoT devices to collect real-time data on prices, consumption, and user preferences. Based on this data, the system adjusts heating settings intelligently to balance comfort and cost savings. IoT connectivity manages continuous monitoring and dynamic optimization in response to changing conditions. This study includes a real-case comparison between a conventional central heating system and an IoT-managed electric radiator setup. By applying automation rules linked to energy pricing and user habits, the system enhances energy efficiency, especially in cold climates. The economic evaluation shows that using low-cost IoT devices yields meaningful savings and achieves equipment payback within approximately three years. The results demonstrate the system’s effectiveness, demonstrating that smart, adaptive heating solutions can cut energy expenses without sacrificing comfort, while offering environmental and financial benefits. Full article

This study addresses the problem of agricultural waste utilization and nutrition for older adults by developing a food product based on a circular design approach. Pineapple core was used to produce a clean-label dietary powder without chemical or enzymatic treatment, relying on repeated rinsing and hot-air drying. The development process followed a structured analysis of physical, chemical, and sensory properties. The powder contained 83.46 g/100 g dietary fiber, 0° Brix sugar, pH 4.72, low water activity (aw < 0.45), and no detectable heavy metals or microbial contamination. Sensory evaluation by expert panelists confirmed that the product was acceptable in appearance, aroma, and texture, particularly for older adults. These results demonstrate the feasibility and safety of valorizing agri-waste into functional ingredients. The process was guided by the Transformative Circular Product Blueprint, which integrates clean-label processing, IoT-enabled solar drying, and decentralized production. This model supports traceability, low energy use, and adaptation at the community scale. This study contributes to sustainable food innovation and aligns with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production). 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

The article examines the application of collaborative robots (cobots) as a modern engineering tool for the transformation of the food industry following the principles of Industry 5.0. A conceptual engineering model has been developed that integrates collaborative robots with IoT systems, digital twins, and predictive analytics to increase the flexibility, safety, and sustainability of production processes. The proposed model is validated through a practical case study focused on a yogurt packaging line in the dairy sector, where cobot systems demonstrate a significant improvement in operational efficiency and process safety. A step-by-step strategic roadmap is presented to guide industrial enterprises through the various stages of implementation, from the initial assessment to the full-scale integration of solutions. Additionally, a comparative analysis has been performed between traditional automated systems and the integrated approach with collaborative robots, which highlights the technological, economic, and human-oriented advantages of the latter. The results of the study confirm that collaborative robotics offers an effective and applicable path for transforming the food and beverage industry towards a sustainable, adaptive, and human-centered manufacturing ecosystem characteristic of Industry 5.0. Full article

Cruciferous vegetables are popular in Asian dishes. However, striped flea beetles prefer to feed on leaves, which can damage the appearance of crops and reduce their economic value. Due to the lack of pest monitoring, the occurrence of pests is often irregular and unpredictable. Regular and quantitative spraying of pesticides for pest control is an alternative method. Nevertheless, this requires manual execution and is inefficient. This paper presents a system powered by solar energy, utilizing batteries and supercapacitors for energy storage to support the implementation of edge AI devices in outdoor environments. Raspberry Pi is utilized for artificial intelligence image recognition and the Internet of Things (IoT). YOLOv5 is implemented on the edge device, Raspberry Pi, for detecting striped flea beetles, and StyleGAN3 is also utilized for data augmentation in the proposed system. The recognition accuracy reaches 85.4%, and the results are transmitted to the server through a 4G network. The experimental results indicate that the system can operate effectively for an extended period. This system enhances sustainability and reliability and greatly improves the practicality of deploying smart pest detection technology in remote or resource-limited agricultural areas. In subsequent applications, drones can plan routes for pesticide spraying based on the distribution of pests. Full article

The scope of this paper is the development of a cost-effective wireless torque measurement system for vehicle drivetrain shafts. The prototype integrates strain gauges, an HX711 conditioner, a Wemos D1 Mini ESP8266, and a rechargeable battery directly on the rotating shaft, forming a self-contained sensor node. Calibration against a certified dynamometric wrench confirmed an operating span of ±5–50 N·m. Within this range, the device achieved a mean absolute error of 0.559 N·m. It also maintained precision better than ±2.5 N·m at 95% confidence, while real-time data were transmitted via Wi-Fi. The total component cost is below EUR 30 based on current prices. The novelty of this proof-of-concept implementation demonstrates that reliable, IoT-enabled torque sensing can be realized with low-cost, readily available parts. The paper details assembly, calibration, and deployment procedures, providing a transparent pathway for replication. By aligning with Industry 4.0 requirements for smart, connected equipment, the proposed torque measurement system offers an affordable solution for process monitoring and predictive maintenance in automotive and industrial settings. Full article

The increased occurrence and severity of cyber-attacks on critical infrastructure have underscored the need to embrace systematic and prospective approaches to resilience. The current research takes as its hypothesis that the InfraGuard Cybersecurity Framework—a capability model that measures the maturity of cyber resilience through three functional pillars, Cyber as a Shield, Cyber as a Space, and Cyber as a Sword—is an implementable and understandable means to proceed with. The model treats the significant aspects of situational awareness, active defense, risk management, and recovery from incidents and is measured using globally standardized maturity models like ISO/IEC 15504, NIST CSF, and COBIT. The contributions include multidimensional measurements of resilience, a scored scale of capability (0–5), and domain-based classification enabling organizations to assess and enhance their cybersecurity situation in a formalized manner. The framework’s applicability is illustrated in three exploratory settings of power grids, healthcare systems, and airports, each constituting various levels of maturity in resilience. This study provides down-to-earth recommendations to policymakers through the translation of the attributes of resilience into concrete assessment indicators, promoting policymaking, investment planning, and global cyber defense collaboration. Full article

Agriculture 5.0 represents a shift towards a more sustainable agricultural model, integrating Artificial Intelligence (AI), the Internet of Things (IoT), robotics, and blockchain technologies to enhance productivity and resource management, with an emphasis on social and environmental resilience. This article explores how the evolution of wireless technologies to sixth-generation networks (6G) can support innovation in Colombia’s agricultural sector and foster rural advancement. The study follows three main phases: search, analysis, and selection of information. In the search phase, key government policies, spectrum management strategies, and the relevant literature from 2020 to 2025 were reviewed. The analysis phase addresses challenges such as spectrum regulation and infrastructure deployment within the context of a developing country. Finally, the selection phase evaluates technological readiness and policy frameworks. Findings suggest that 6G could revolutionize Colombian agriculture by improving connectivity, enabling real-time monitoring, and facilitating precision farming, especially in rural areas with limited infrastructure. Successful 6G deployment could boost agricultural productivity, reduce socioeconomic disparities, and foster sustainable rural development, contingent on aligned public policies, infrastructure investments, and human capital development. Full article