Search Results (163)

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

The global coffee supply chain is a complex multi-stakeholder ecosystem plagued by fragmented records, unverifiable origin claims, and limited real-time visibility. These limitations pose risks to ethical sourcing, product quality, and consumer trust. To address these issues, this paper proposes a blockchain and IoT-enabled framework for secure and transparent coffee supply chain management. The system integrates simulated IoT sensor data such as Radio-Frequency Identification (RFID) identity tags, Global Positioning System (GPS) logs, weight measurements, environmental readings, and mobile validations with Ethereum smart contracts to establish traceability and automate supply chain logic. A Solidity-based Ethereum smart contract is developed and deployed on the Sepolia testnet to register users and log batches and to handle ownership transfers. The Internet of Things (IoT) data stream is simulated using structured datasets to mimic real-world device behavior, ensuring that the system is tested under realistic conditions. Our performance evaluation on 1000 transactions shows that the model incurs low transaction costs and demonstrates predictable efficiency behavior of the smart contract in decentralized conditions. Over 95% of the 1000 simulated transactions incurred a gas fee of less than ETH 0.001. The proposed architecture is also scalable and modular, providing a foundation for future deployment with live IoT integrations and off-chain data storage. Overall, the results highlight the system’s ability to improve transparency and auditability, automate enforcement, and enhance consumer confidence in the origin and handling of coffee products. Full article

Urban Air Mobility (UAM) is envisioned to revolutionize urban transportation by improving traffic efficiency and mitigating surface-level congestion. One of the fundamental challenges in implementing UAM systems lies in the optimal siting of vertiports, which requires a delicate balance among infrastructure construction costs, passenger access costs to their assigned vertiports, and the operational connectivity of the resulting vertiport network. This study develops an integrated mathematical model for vertiport location decision, aiming to minimize total system cost while ensuring UAM network connectivity among the selected vertiport locations. To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. The effectiveness of the proposed algorithm is demonstrated through numerical experiments conducted on both synthetic datasets and the real-world transportation network of New York City. The results show that the proposed hybrid methodology not only yields high-quality solutions but also significantly reduces computational time, enabling faster convergence. Overall, this study provides practical insights for UAM infrastructure planning by emphasizing demand-oriented vertiport siting and inter-vertiport connectivity, thereby contributing to both theoretical development and large-scale implementation in complex urban environments. Full article

This study analyzed the frequency control challenges within the West Africa Power Pool Interconnected Transmission System (WAPPITS) as it plans to incorporate variable renewable energy (VRE) resources, such as wind and solar energy. Concerns center on the ability of WAPPITS primary frequency control reserves to adapt to high VRE penetration given the synchronization and frequency control problems experienced by the three separate synchronous blocks of WAPPITS. Optimizing solutions requires a better understanding of WAPPITS’ current frequency control approach. This study used questionnaires to understand operators’ practical experience with frequency control and compared these observations to field tests at power plants and frequency response metrics during system events. Eight (8) of ten (10) Transmission System Operators (TSOs) indicated that primary frequency control service was implemented in the TSO, but nine (9) of ten TSOs indicated that the reserves provided were inadequate to meet system needs. Five (5) of ten (10) respondents answered “yes” to the provision of secondary frequency control service, while only one (1) indicated that secondary reserves were adequate. Three (3) TSOs indicated they have AGC (Automatic Generation Control) installed in the control room, but none have implemented it for secondary frequency control. The results indicate a significant deficiency in primary control reserves, resulting in a reliance on under-frequency load shedding for primary frequency control. Additionally, the absence of an AGC system for secondary frequency regulation required manual intervention to restore frequency after events. To ensure the effectiveness of battery energy storage systems (BESSs) and the reliable operation of the WAPPITS with a higher penetration of inverter-based VRE, this paper recommends (a) implementing and enforcing basic primary frequency control structures through regional regulation and (b) establishing an ancillary services market to mobilize secondary frequency control resources. Full article

Low-latency and robust beamforming are vital for sustaining signal quality and spectral efficiency in emerging high-mobility 5G and future 6G wireless networks. Conventional beam management approaches, which rely on periodic Channel State Information feedback and static codebooks, as outlined in 3GPP standards, are insufficient in rapidly varying propagation environments. In this work, we propose a Dominance-Enforced Adaptive Clustered Sliding Window Regression (DE-ACSW-R) framework for predictive beamforming in O-RAN Split 7-2x architectures. DE-ACSW-R leverages a sliding window of recent angle of arrival (AoA) estimates, applying in-window change-point detection to segment user trajectories and performing both Linear Regression (LR) and curvature-adaptive Support Vector Regression (SVR) for short-term and non-linear prediction. A confidence-weighted fusion mechanism adaptively blends LR and SVR outputs, incorporating robust outlier detection and a dominance-enforced selection regime to address strong disagreements. The Open Radio Unit (O-RU) autonomously triggers localised MUSIC scans when prediction confidence degrades, minimising unnecessary full-spectrum searches and saving delay. Simulation results demonstrate that the proposed DE-ACSW-R approach significantly enhances AoA tracking accuracy, beamforming gain, and adaptability under realistic high-mobility conditions, surpassing conventional LR/SVR baselines. This AI-native modular pipeline aligns with O-RAN architectural principles, enabling scalable and real-time beam management for next-generation wireless deployments. Full article

Walking and cycling, as active modes of transportation, play a vital role in advancing sustainable urban mobility by reducing emissions and improving public health. However, widespread adoption faces challenges such as inadequate infrastructure, safety concerns, socio-cultural barriers, and policy limitations. This study systematically reviewed 56 peer-reviewed articles from 2004 to 2024, across 30 countries across five continents, employing the Capability, Opportunity and Motivation-Behaviour (COM-B) framework to identify the main drivers of walking and cycling behaviours. Findings highlight that the lack of dedicated infrastructure, inadequate enforcement of road safety measures, personal and traffic safety concerns, and social stigmas collectively hinder active mobility. Strategic interventions such as developing integrated cycling networks, financial incentives, urban planning initiatives, and behavioural change programs have promoted increased engagement in walking and cycling. Enhancing urban mobility further requires investment in pedestrian and cycling infrastructure, improved integration with public transportation, the implementation of traffic-calming measures, and public education campaigns. Post-pandemic initiatives to establish new pedestrian and cycling spaces offer a unique opportunity to establish enduring changes that support active transportation. The study suggests expanding protected cycling lanes and integrating pedestrian pathways with public transit systems to strengthen safety and accessibility. Additionally, leveraging digital tools can enhance mobility planning and coordination. Future research is needed to explore the potential of artificial intelligence in enhancing mobility analysis, supporting the development of climate-resilient infrastructure, and informing transport policies that integrate gender perspectives to better understand long-term behavioural changes. Coordinated policy efforts and targeted investments can lead to more equitable transportation access, support sustainability goals, and alleviate urban traffic congestion. Full article

This paper introduces a configuration and integration model for mobile robots deployed in emergency and special operations scenarios. The proposed method is designed for implementation within the operational technology (OT) domain, enforcing security protocols that ensure both data encryption and network isolation. The primary objective is to establish a dedicated operational environment encompassing a command and control center where the robotic network server resides, alongside real-time data storage from network clients and remote control of field-deployed mobile robots. Building on this infrastructure, operational strategies are developed to enable an efficient robotic response in critical situations. By leveraging remote robotic networks, significant benefits are achieved in terms of personnel safety and mission efficiency, minimizing response time and reducing the risk of injury to human operators during hazardous interventions. Unlike generic IoT or IoRT systems, this work focuses on secure robotic integration within segmented OT infrastructures. The technologies employed create a synergistic system that ensures data integrity, encryption, and safe user interaction through a web-based interface. Additionally, the system includes mobile robots and a read-only application positioned within a demilitarized zone (DMZ), allowing for secure data monitoring without granting control access to the robotic network, thus enabling cyber-physical isolation and auditability. Full article

Traffic calming has emerged as a key urban strategy to reduce vehicle speeds and mitigate road traffic risks, with increasing recognition of its broader implications for public health, human behaviour, and urban liveability. This systematic literature review examines the multifaceted impacts of traffic-calming measures—from speed limit reductions to physical infrastructure and enforcement-based interventions—by synthesising findings from 28 peer-reviewed studies. Guided by the PRISMA framework, the review compiles research exploring links between traffic calming and outcomes related to public health, behaviour, and urban quality of life. Research consistently indicates that such interventions reduce both the frequency and severity of collisions, improve air and noise quality, and promote active mobility. These effects are shaped by user perceptions: non-motorised users tend to report higher levels of safety and accessibility, whereas motorised users often express frustration or resistance. Beyond safety and environmental improvements, traffic calming has been associated with greater use of public space, stronger social connections, and enhanced environmental aesthetics. The findings also show that key challenges may affect the effectiveness of traffic calming and these include negative attitudes among drivers, mixed outcomes for air quality, and unintended consequences such as traffic displacement or increased noise when interventions are poorly implemented. Overall, the findings suggest that traffic calming can serve as both a public health initiative and a tool for enhancing urban liveability, provided that the measures are designed with contextual sensitivity and supported by inclusive communication strategies. Full article

Air pollution is a major problem in the modern world; although it particularly impacts developing countries, which are experiencing fast and often uncontrolled industrialization, its effects constitute a global burden on the environment and health. At the same time, the costs of effective air quality monitoring programs are prohibitive for emerging economies, thus making any correction difficult to assess. Emerging technologies, such as distributed networks of sensors organized in the Internet of Things, are under the lens of scientific and industrial communities as a valuable, low-cost alternative to standard techniques. In this paper, we report a review of current approaches to distributed air quality monitoring. Specifically, we (1) emphasize the role of crowdsensing in leveraging sensor-enabled mobile devices for large-scale environmental data collection and (2) discuss criticalities, open challenges, and future perspectives in enforcing data security when such approaches are deployed in real application scenarios. Full article

In the Netherlands, around 52,000 dairy cows die on the primary farm each year due to natural death, euthanasia, or on-farm emergency slaughter (OFES). The decision as to what is the best option is made by the farmer, often after consulting a veterinarian, a livestock trader, or a slaughterhouse operator. To determine which factors play a role in this decision-making process, semi-structured interviews were conducted with dairy farmers, private veterinary practitioners, livestock traders, and slaughterhouse operators in the Netherlands. Dairy cattle culling decisions are influenced and limited by strict enforcement of livestock transport regulations and limited options for on-farm killing methods. Requirements regarding mortality rates imposed by the dairy industry and private quality labels for raw milk also influence culling decisions in the Netherlands. Most participants stated that restrictive conditions regarding OFES and mobile slaughterhouses (MSHs) appear to have (unintended) negative effects on cow welfare and meat salvage in general. Different interests, such as cow welfare, food safety, economic concerns of various stakeholders, the reputational interests of the dairy and beef industries, and sustainability objectives such as meat salvage can be conflictive. The results of this study show that the decision-making process regarding culling or (prolonged) veterinary treatment of dairy cattle is complex because various factors, interests, and uncertainties must be weighed. This weighing can vary between individual dairy farms and individual dairy farmers. Full article

While digital religion and digital protest can ideally serve the common good, religious nationalist and fundamentalist movements have exploited these tools to disrupt the social fabric and create dangerous political outcomes. This paper examines how religious communicators within Tehreek-e-Labbaik Pakistan (TLP) and Alternative for Germany (AfD) perceive and enact their responsibility within digital spaces, leveraging the power of “networked communities” and the collective identity of the digital “crowd” to advance their agendas of religious fundamentalism and political conservatism. Bypassing traditional media, groups like the AfD and TLP exploit digital religion to build communities, spread propaganda that merges religion with national identity, frame political issues as religious mandates, and mobilize collective action. Campbell’s concept of the “networked community” demonstrates how digital technologies form decentralized, fluid, and global religious communities, distinct from traditional, geographically bound ones. Both the TLP and AfD have tapped into this new digital religious space, shaping and mobilizing political and religious identities across virtual borders. Gerbaudo’s idea of the “digital crowd” complements this by examining how collective action in the digital age reshapes mass mobilization, with social media transforming how political movements operate in the 21st century. Although the AfD’s platform is not overtly religious, the party strategically invokes ethno-Christian identity, framing opposition to Islam and Muslim immigration as a defense of German cultural and Christian values. Similarly, the TLP promotes religious nationalism by advocating for Pakistan’s Islamic identity against secularism and liberalism and calling for strict enforcement of blasphemy laws. Recognizing digital spaces as tools co-opted by religious nationalist movements, this paper explores how communicators in these movements understand their responsibility for the social and long term consequences of their messages. Using Luhmann’s systems theory—where communication is central to social systems—this paper analyzes how the TLP and AfD leverage individuals’ need for purpose and belonging to mobilize them digitally. By crafting emotionally charged experiences, these movements extend their influence beyond virtual spaces and into the broader public sphere. Finally, this paper will reflect on the theological implications of these dynamics both on and offline. How do religious communicators in digital spaces reconcile their theological frameworks with the social impact of their communication? Can digital religious communities be harnessed to foster social cohesion and inclusivity instead of exacerbating social divisions? Through this lens, the paper seeks to deepen our understanding of the intersection between digital religion, political mobilization, and theological responsibility in the digital age. Full article

Cyberbullying is a pervasive social issue that has gained increasing attention due to its serious consequences, such as cyberbullicide, which is suicide resulting from cyberbullying. Researchers have called for various interventions and the involvement of multiple stakeholders, including psychologists and law enforcement agencies, to address the problem. Recent studies have shown that the majority of cyberbullying incidents occur on mobile devices, referred to as mobile bullying. Therefore, there is a need to focus intervention efforts on mobile bullying, which is a subset of cyberbullying. The objective of this study was to develop a framework that could guide the creation of an awareness intervention aimed at raising awareness of mobile bullying. Although several meta-analyses have been conducted over the years on intervention effectiveness. There is a gap from the lack of frameworks and requirements to guide the development of awareness interventions. As such, a PRISMA (preferred reporting items for systematic reviews and meta-analyses) systematic literature review was conducted to identify the theories that could inform the development of such an intervention. Based on the review, a theoretical framework was developed that incorporated the basic elements identified as guiding principles for the development of awareness interventions. In the same way, theory, specifically SAT was used to inform the development of an instrumental framework for designing context-sensitive awareness interventions, incorporating the basic elements that practitioners can use to develop context-sensitive awareness interventions. The findings from the study indicate that the social context, which encompasses the social issue at hand; available media content; the proximal and distal environments; and the choice of awareness tool, which is informed by the marketing mix (i.e., price, product, people, promotion, and place), affect the reach or distribution of the intervention. The theoretical framework contributes to the body of knowledge on the subject, while the instrumental framework provides a practical approach to building customizable interventions that can be tailored to specific contexts and available resources for awareness. Full article

Road traffic accidents pose a significant global public health and economic challenge. In Saudi Arabia, rapid motorization and urbanization have contributed to one of the world’s highest traffic fatality rates. This study evaluates the effectiveness of the Saher traffic enforcement system in the Dammam Metropolitan Area (DMA) by gathering insights from road safety experts through structured questionnaires and interviews. Findings indicate that Saher has improved traffic law compliance and enhanced perceptions of road safety. Key accident causes include driver distractions, speeding, and sudden lane changes, with younger drivers being disproportionately involved. Experts recommend expanding Saher’s capabilities by addressing violations like aggressive driving and increasing coverage of cameras, with responses of 21% and 25%, respectively. They also stress the need for better highway coverage, with a response of 32%. Proposed strategies include integrating the Saher system into urban planning, combining automated enforcement with public education, and enhancing traffic infrastructure, such as signage and signal systems. This study offers actionable insights for policymakers to improve road safety and promote sustainable urban mobility in Saudi Arabia. Full article

The global population is aging, and many countries face the daunting challenge of improving their social service systems to accommodate the shift. As global aging increases, the travel needs of older persons are becoming more pronounced. Given this, there is now an urgent need to create and enforce efficient actions to reconcile the incompatibility of the current transportation networks with the growing demand for travel by the elderly. In light of this context, the United States, the United Kingdom, Japan, and China are used as examples in this study. It adopts a literature review analysis method based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to systematically review and analyze the efforts of the four countries to address the challenges of aging mobility in five dimensions, namely, laws and regulations, planning and design, policy measures, transportation infrastructure and services, and technology development. This review illustrates the similarities, distinctions, and difficulties that each nation faces in advancing the development of an age-friendly transportation environment by contrasting and evaluating the real-world experiences of the four nations. Accordingly, countermeasures and recommendations, such as stepped fare concessions and attention to the psychological adaptation of older persons in technological innovations, are proposed. Full article

As the use of personal mobility (PM) devices continues to rise, regulatory violations have become more frequent, highlighting the need for technological solutions to ensure efficient enforcement. This study addresses these challenges by proposing an AI-based enforcement platform. The system integrates the You Only Look Once version 5 (YOLOv5) object detection model, a deep-learning-based framework, with Global Positioning System (GPS) location data, Raspberry Pi 5, and Amazon Web Services (AWS) for data processing and web-based implementation. The YOLOv5 model was deployed in two configurations: one for detecting electric scooter usage and another for identifying legal violations. The system utilized AWS Relational Database Service (RDS), Simple Storage Service (S3), and Elastic Compute Cloud (EC2) to store violation records and host web applications. The detection performance was evaluated using mean average precision (mAP) metrics. The electric scooter detection model achieved mAP50 and mAP50-95 scores of 99.5 and 99.457, respectively. Meanwhile, the legal violation detection model attained mAP50 and mAP50-95 scores of 99.5 and 81.813, indicating relatively lower accuracy for fine-grained violation detection. This study presents a practical technological platform for monitoring regulatory compliance and automating fine enforcement for shared electric scooters. Future improvements in object detection accuracy and real-time processing capabilities are expected to enhance the system’s overall reliability. Full article