Search Results (2,675)

Driving assistance and autonomous driving are among the fastest-evolving domains of intelligent transportation systems (ITSs). However, visually impaired pedestrians (VIPs) remain weakly protected by roadsides or vehicle perception systems, especially when the right of way must be communicated in an accessible and auditable manner. In this paper, we describe a safety-constrained vehicle-to-pedestrian (V2P) architecture designed for VIP crossing assistance. The system creates a time-bounded interaction state between pedestrians, roadside infrastructure, and vehicles at the Fog level to avoid permissive instructions before all the safety conditions are satisfied. Our objective is not to design a new detector, tracker, or MLLM model. Instead, we combine edge tier descriptors, Fog-tier multi-view descriptors, and multi-camera multiple-object tracking (MC-MOT) within a latency-constrained V2P loop. Our main empirical focus is WildTrack multi-camera continuity with novel multi-camera consensus gating (MCCG), a geometric-support safety gate. The reproduced Fog-tier continuity branch reaches MOTA = 88.8%, IDF1 = 91.7%, and HOTA = 65.5%. MCCG with M = 4 retains 95% permissive eligibility while withholding permissive guidance in three of the four ID-switch frames (75%). These findings support component-level feasibility, while leaving field deployment, V2X stack validation, and user studies for future work. Full article

Contemporary cities face increasingly interconnected environmental, social, health, and geopolitical crises, requiring closer integration between long-term urban development and emergency preparedness. This study examines how spatial planning can support civil protection and strengthen urban and community resilience, using Poland as a case of a planning system undergoing substantial legislative change. The research combines a review of international resilience frameworks with comparative and critical analyses of Polish spatial planning, crisis management, and civil protection regulations, complemented by a research-by-design case study. The findings reveal persistent institutional and spatial fragmentation: crisis preparedness remains weakly embedded in planning instruments, while crisis management and civil protection regulations insufficiently address the spatial conditions necessary for effective implementation. Key gaps concern risk-sensitive land use, protective infrastructure, evacuation systems, multifunctional public spaces, and cross-sectoral coordination. The research-by-design component demonstrates how these requirements can be translated into adaptive and multifunctional urban environments. Based on the findings, an integrated planning framework is proposed that links risk assessment, protective infrastructure, adaptive spatial design, and coordinated governance. Embedding civil protection within spatial planning can reduce vulnerability, support continuity of essential urban functions, and strengthen community resilience while contributing to safer and more sustainable urban development. Full article

Peste des petits ruminants (PPR) is a highly contagious transboundary viral disease of sheep and goats that causes major economic losses and livelihood disruption across Africa, the Middle East, and Asia. Goats are often more severely affected than sheep, particularly in endemic smallholder systems, where high turnover, nutritional stress, and limited veterinary infrastructure sustain viral transmission. Despite effective live attenuated vaccines and the ongoing FAO–WOAH Global Eradication Programme, PPR remains widely distributed, indicating that vaccination alone is insufficient without understanding of host, viral, and environmental determinants of disease persistence. This review synthesizes current knowledge on three interrelated pillars of PPR prevention and control in goats: epidemiology, immunology, and host genetics. We summarize the epidemiological drivers of PPR transmission and how these factors shape disease burden in endemic settings. We review the immunobiology of PPR virus (PPRV) infection and vaccination, focusing on innate antiviral sensing, adaptive immune protection, virus-induced immunosuppression, and field determinants of vaccine performance. Finally, we examine the emerging evidence for host genetic resilience to PPR, with emphasis on immunogenomic and transcriptomic findings and the relevance of indigenous breeds such as the Black Bengal goat as genomic resources. Current evidence suggests that genetic resilience to PPR is likely polygenic and remains insufficiently characterized, though genomic and transcriptomic tools offer opportunities to identify markers of reduced susceptibility, milder disease, or improved vaccine response. Sustainable control of PPR in goats will require integrated strategies combining mass vaccination, surveillance, improved husbandry, and host-focused immunogenomic research to strengthen herd resilience and accelerate progress toward global eradication. Full article

The global expansion of interconnected edge network components requires immediate strategies for securing low-power computing nodes. Cryptographic algorithms executing over binary extension fields yield considerable computational benefits because their carry-free arithmetic significantly optimizes dynamic power consumption. However, general-purpose silicon architectures lack the dedicated hardware structures to run these finite-field operations efficiently, resulting in severe processing throughput bottlenecks. This study addresses this limitation by introducing a parallelized modular multiplier framework designed to integrate smoothly with the multicore execution environments of modern embedded platforms. Our approach deploys a progressive multiplier reduction (PMR) protocol that segments dense mathematical workloads into distributed structural thread groups. This architectural alignment allows multiplication matrices and spatial field reductions to take place concurrently, balancing localized workloads while decreasing intermediate data buffering demands. We present two distinct topological styles based on column division and row division techniques, deriving comprehensive analytical formulations to capture precise silicon area footprints, critical path delays, and total operational cycle counts. The resulting hardware metrics demonstrate that the parallel PMR design achieves a highly competitive area–delay product alongside optimized dynamic consumption characteristics. This structural paradigm delivers a scalable and robust security alternative for general edge hardware, ensuring system runtime stability while meeting tight environmental power constraints, protecting vital industrial assets, and sustaining emerging macroeconomic infrastructure. Full article

Climate change is intensifying challenges to microbial water quality and household water security across Saharan and Sahelian Africa, where water scarcity, variable infrastructure, and reliance on decentralized and informal water sources can increase vulnerability to contamination. This structured narrative review synthesizes evidence on how climatic stressors, including extreme heat, ultraviolet radiation, drought, flooding, rainfall variability, and dust events, influence microbial contamination, persistence, transport, and exposure across groundwater, surface waters, drinking-water distribution systems, and household storage. Heavy rainfall and flooding can mobilize fecal contamination and microbial hazards into water sources, whereas drought and water scarcity can increase dependence on marginal supplies, prolong household storage, and create conditions favorable to post-collection contamination and microbial regrowth. Climatic effects vary across microbial groups and water matrices: temperature, sunlight, turbidity, sediments, biofilms, and hydrological conditions can differentially influence bacterial, viral, and protozoan persistence and transport. Saharan dust also represents a potential pathway for long-range microbial dispersal and deposition, although direct evidence linking individual dust events to pathogen concentrations in drinking-water sources remains limited. The review further shows that microbial water quality is insufficiently integrated with broader dimensions of household water security, including availability, reliability, accessibility, and perceived safety. Strengthening the evidence base will require greater integration of microbial, climatic, hydrological, infrastructure, and household water-security data to support climate-resilient water management and public-health protection in Saharan and Sahelian communities. Full article

The increasing demand for sustainable outdoor lighting has accelerated the development of solar-powered lighting systems. However, conventional solar lamps typically employ fixed illumination levels and simple day–night switching mechanisms, resulting in inefficient battery utilization and limited adaptability to changing environmental conditions. This study proposes a TRIZ-guided intelligent solar-powered lighting system that integrates photovoltaic energy harvesting, adaptive pulse-width modulation (PWM)-based illumination control, ultrasonic sensing, wireless communication, and embedded control into a unified standalone platform. The TRIZ contradiction matrix was employed during the conceptual design stage to systematically resolve key engineering contradictions involving illumination performance, energy efficiency, hardware complexity, battery lifetime, and user convenience. The proposed prototype was developed using an AT89S51 microcontroller to coordinate battery charging protection, environmental sensing, adaptive brightness regulation, and manual wireless operation. Experimental validation demonstrated stable photovoltaic charging with a regulated battery charging voltage of 14.4 V, reliable execution of embedded control functions, seamless transition between manual and autonomous operating modes, and adaptive LED brightness regulation according to real-time environmental conditions. The integrated PWM control strategy reduced unnecessary energy consumption by dynamically adjusting illumination intensity based on object detection rather than maintaining constant full-power operation. The experimental results further verified the feasibility of combining software-driven adaptive control with renewable energy harvesting to achieve intelligent energy management without increasing hardware complexity. Overall, the proposed system demonstrates that the integration of TRIZ-based systematic innovation with embedded intelligent control provides a practical, energy-efficient, and cost-effective solution for autonomous outdoor lighting. The proposed architecture offers valuable engineering insights for future smart lighting applications in off-grid infrastructure, sustainable communities, and smart city environments. Full article

Monumental heritage sites must be protected as rigorously as critical infrastructures, but under aesthetic and architectural constraints that limit where protection technologies can be installed; the purpose of this study is to reconcile effective security with minimal impact on the historical fabric. The paper presents the integrated security and safety system realized for the Royal Palace and Gardens of Caserta, a UNESCO World Heritage Site visited by around one million people per year. This system includes an Internet of Things/Internet of Everything framework integrating a 3D supervision platform, a resilient park-wide network, video surveillance, emergency communications, an artificial-intelligence engine and visitor services. Perimeter video-surveillance design is formulated as a constrained multi-objective optimization problem (coverage, camera count, overlap, reuse of existing installation points) solved with a purpose-built genetic algorithm and characterized through 311 optimization runs and 216 baseline runs on synthetic perimeter instances. The algorithm reached 95–98% perimeter coverage while reusing 95–100% of existing installation points, converging within 120–410 generations. Two greedy baselines were respectively quantified: the price of the aesthetic objectives (a 29–41% camera overhead with respect to a coverage-only design) and the specific contribution of the joint optimization (an order-of-magnitude reduction in coverage redundancy at equal reuse of existing installation points). Sensitivity analysis exposed the coverage–cost trade-off. The framework and method provide a reproducible, quantitatively characterized approach to minimally invasive heritage security design that is transferable to comparable sites. Full article

By combining digital sensing, network connectivity, data-driven analyses, cloud services, and automated controls, smart farming has been increasingly adopted in agricultural production. Although these technologies have improved the precision and efficiency of farm management, they also increase cybersecurity exposure as agricultural facilities are connected to external networks, platforms, and remote-control environments. This review seeks to clarify why cybersecurity should be considered a fundamental requirement in smart farming and details the major system components, cybersecurity risks, and network design considerations required for secure operation. This review first explains the concept and application scope of smart farming, and then examines how sensors, communication networks, gateways, control systems, data platforms, user interfaces, cloud infrastructure, and physical support systems contribute to farm management and cybersecurity exposure. The review also emphasizes that smart farming differs from ordinary information systems because digital data and control commands can directly affect physical processes, such as irrigation, ventilation, heating, nutrient supply, and livestock management. Based on these cyber-physical characteristics, the review summarizes the key architectural considerations for reducing cybersecurity risks, including network segmentation, data and command flow mapping, gateway and wireless security, remote access management, cloud access control, device inventory, logging, monitoring, resilience, and local fail-safe operation. Overall, ensuring cybersecurity in smart farming requires an integrated approach that protects not only data and accounts but also the reliability and continuity of agricultural production. Full article

Sustainable Development Goal 6 (SDG 6) seeks to ensure the availability and sustainable management of clean water and sanitation for all by 2030. Despite notable policy and institutional reforms, many developing countries, including South Africa, continue to face complex and interconnected challenges related to water quality, governance, infrastructure, financing, and institutional capacity that impede progress towards achieving SDG 6. A systematic literature review methodology was applied using predefined eligibility criteria and data sources to identify evidence related to drinking water quality and SDG 6 implementation. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, 241 records were initially identified. After screening and eligibility assessment, 115 records were retained for detailed analysis, while studies not focused on South Africa, not directly related to drinking water quality, or lacking sufficient empirical evidence were excluded. The review reveals that drinking water quality in South Africa is increasingly threatened by various challenges that may hinder the achievement of SDG 6. The findings highlight the importance of integrated interventions that combine infrastructure renewal, technological innovation, strengthened regulatory compliance, improved wastewater management, ecosystem protection, institutional reform, and stakeholder participation. To address these interconnected challenges, the study proposes the Governance, Technology, Finance, Capacity and Institutions (GTFCI) Framework as an integrated implementation pathway for SDG 6. The framework positions governance, institutional capacity, technology, and financing as foundational enablers of water service delivery, while integrated water resources management (IWRM) serves as the coordinating mechanism linking water services, ecosystem sustainability, and long-term water security. International cooperation and community participation function as cross-cutting support mechanisms that reinforce implementation across all SDG 6 targets. The proposed GTFCI Framework provides a practical and strategic model for strengthening drinking water quality, enhancing water security, and accelerating progress towards the sustainable achievement of SDG 6 by 2030. Full article

Constructed wetlands (CWs) are increasingly used for decentralized wastewater treatment and reuse where conventional infrastructure is difficult to sustain. This review integrates evidence on hydraulic reliability, biogeochemical performance, reuse safety, sustainability trade-offs, and process-based modeling, and derives design implications for Neotropical settings. Organic-matter and suspended-solids removal is generally more robust than nitrogen, phosphorus, and pathogen control. More reliable performance is associated with controlled hydraulic loading, solids-limiting pretreatment, stable flow distribution and water levels, and protection against stormwater-driven short-circuiting and clogging. Reuse should therefore be evaluated against fit-for-purpose microbial, nutrient, salinity, and chemical endpoints rather than removal efficiency alone. We propose seasonal monitoring, tracer or residence-time-distribution assessment where decisions depend on hydraulic efficiency, locally calibrated design envelopes, and a minimum reporting set covering climate/season, flow and loading, HRT/HLR, configuration, pretreatment, media, monitoring duration, influent/effluent concentrations, and hydraulic indicators. This study is a structured narrative review with thematic synthesis; literature identification and corpus reporting were informed by applicable PRISMA 2020 principles. Three Scopus searches yielded 593 records; after removal of 37 duplicates, 556 unique records remained. The final thematic corpus comprises 80 reports, of which 30 are present in the Scopus exports and 50 were identified through complementary routes. Full article

Transformer lifecycle data across organizations are typically vertically partitioned among material suppliers, manufacturers, logistics service providers, testing agencies, and operation and maintenance units. This study presents a reproducible multi-layer vertical federated learning (VFL) prototype that integrates salted-hash identifier matching, additive sharing of local score vectors over finite fields, and a local public key infrastructure with a signature-based audit verification mechanism. A deterministic synthetic dataset is first constructed, comprising 5200 aligned records and 31 predictor variables, which are partitioned among five participants with varying numbers of features per participant. Second, across five validation runs, the VFL models under both the standard block-wise and score-sharing paths achieved an AUC of 0.8825 ± 0.0119, an F1 score of 0.7367 ± 0.0249, and an accuracy of 0.8102 ± 0.0183 on the test set. The classification results of both paths were fully consistent with the centralized gradient-descent logistic regression baseline. Notably, the score-sharing path exhibited a maximum log-odds deviation of only 2.22 × 10⁻⁸ on the test set, with no prediction discrepancies observed. Third, across 10 independently generated synthetic populations, the nonlinear output mechanism highlights the limitations of linear models: the AUC of vertical federated learning (VFL) drops to 0.6457 ± 0.0171, while Extra Trees and HistGradientBoosting achieve 0.7731 ± 0.0149 and 0.7743 ± 0.0139, respectively. Finally, in a separate residual-sharing diagnostic test, when 1 to 4 participants jointly shared the residuals, the label inference AUC remained around 0.499–0.500; however, when all five participants shared or plaintext residuals were used, the labels could be fully recovered. Both simple membership inference diagnostic tests yielded results close to random. The local signature log verifier rejected all 700 injected faults and accepted the 400 clean control log events. These results validate the feasibility of numerical reproducibility and local audit functionality under synthetic data and single-process conditions, yet they are insufficient to demonstrate end-to-end label privacy protection, malicious security, effectiveness on real data, or real-time ledger performance. Full article

Mediterranean seagrass meadows, particularly Posidonia oceanica and Cymodocea nodosa, provide important ecosystem services including blue carbon storage, biodiversity support, sediment stabilization, and coastal protection, yet they continue to decline under multiple anthropogenic pressures. This article presents a SEEA EA-aligned natural capital accounting framework for seagrass restoration, developed within the INTERREG EuroMed ARTEMIS project and applied to four pilot sites in Crete, Menorca, Sardinia, and Monfalcone. The sites were selected to represent heterogeneous Mediterranean restoration contexts, including different seagrass species, degradation histories, pressure regimes, and restoration strategies. The methodology applies a seven-step marine natural capital accounting cycle combining ecosystem extent and condition accounts, physical blue carbon accounts, monetary ecosystem service accounts, impact statement accounts, and natural capital balance sheets. Two ecosystem service components are valued: global climate regulation, through blue carbon sequestration and storage, and biodiversity preservation, through a defensive cost approach. Results show strong site-specific variation. Biodiversity preservation dominates total asset values across all sites, while blue carbon is particularly relevant in Sardinia because of its high accumulation rate and carbon stock. A passive restoration scenario for Sardinia shows that pressure reduction and eco-mooring infrastructure can generate substantially larger aggregate values than small-scale active transplantation, mainly because of the larger area addressed. Compared with previous service-specific or broad-scale seagrass valuation studies, this article contributes by linking site-specific ecological monitoring, SEEA EA-compatible accounting outputs, and natural capital balance sheet values within a single framework relevant to marine restoration finance and future nature credit design. Full article

In the field of cybersecurity, malicious website classification plays a crucial role in protecting industrial systems. For this reason, research has been undertaken to analyze cybersecurity threats, with the long-term objective of developing methods for the effective detection and classification of malicious websites. This article evaluates the use of domain features for classifying malicious websites with machine learning methods. The feature vector consisted of 44 infrastructural, lexical, structural, and reputation-related characteristics. The model comparison included Logistic Regression, Support Vector Machine, Random Forest, AdaBoost, and XGBoost. Experiments were conducted on 247,730 URLs from the malicious_phish dataset (2021), with features extracted as part of this study in April 2026. The most predictive features were related to domain registration history, DNS infrastructure, and reputation-based rankings, as confirmed by ANOVA F-test, SHAP values, XGBoost gain, and permutation importance. Validation of the best-performing model on 1000 active phishing domains from the PhishDestroy list dated 30 May 2026, achieved a recall of 70%, while the application of a three-tier risk scale allowed 84.9% of domains to be flagged as malicious or suspicious. Full article

The increasing interconnection of smart-grid operational technology, industrial-edge services, and utility information systems creates a critical need for resilient and continuously monitored industrial cyber-physical communication. Although quantum key distribution (QKD) can strengthen session-key establishment for advanced metering infrastructure, distributed energy resources, substation automation, supervisory control, and utility-core services, practical QKD deployments remain vulnerable to implementation-level side-channel attacks that can compromise the cryptographic protection layer without directly targeting conventional network packets. This paper presents a QKD-secured industrial smart-grid cyber-physical system framework for simulating and detecting adaptive side-channel attacks. The proposed 36-node industrial communication architecture integrates AMI devices, DER controllers, PMU and substation automation components, industrial-edge gateways, QKD modules, key-management services, SCADA and utility-core servers, security-operation-center components, and adversarial access points. A 100,000-record cyber-quantum dataset is generated across 12 operating conditions comprising normal communication and 11 adaptive QKD side-channel attacks: detector blinding, time shift, wavelength switching, Trojan-horse probing, photon-number splitting, decoy-state spoofing, RNG bias, calibration manipulation, local-oscillator manipulation, synchronization spoofing, and combined adaptive quantum hacking. Each scenario introduces coupled primary and secondary perturbations across optical, detector, timing, synchronization, randomness, calibration, photon-statistical, leakage, key-generation, encryption, and industrial-network-performance features. To support intelligent industrial security monitoring, the proposed Quantum-aware Mamba–Kolmogorov–Arnold Network (Q-MambaKAN) organizes device, network, QKD, side-channel, encryption, and risk evidence into an ordered cyber-quantum representation processed through selective state-space learning, side-channel attention, nonlinear KAN mapping, adaptive fusion, and multi-task prediction heads. Results show that the QBER increases from 0.071 during normal operation to 0.426 under combined adaptive quantum hacking, while encryption success decreases from 98.1% to 0%. Q-MambaKAN achieves a 99.48% binary detection accuracy, a 99.70% binary F1-score, a 97.60% multiclass macro-F1, and a risk RMSE of 0.021. Full article

Sustainable urban infrastructure increasingly relies on blockchain-secured energy digital twins to improve energy-data verification, transparency, traceability, and trust across construction, operation, certification, and compliance. Yet the prevailing literature still treats these systems primarily as descriptive mirrors of physical infrastructure, emphasizing their ability to capture, verify, and protect data on energy production, consumption, storage, and exchange. Verified records can underpin institutional outcomes such as certification and compliance—but this framing ignores a deeper change: blockchain-secured digital twins may help automate the constitution of those outcomes, rather than only representing infrastructure performance. This conceptual study develops the Automated Constitution Model (ACM), which explains the conditions under which blockchain-secured energy digital-twin records transition from epistemic verification to institutionally recognized outcomes and how accountability is redistributed across the socio-technical actors involved in that transition. The model defines seven interconnected layers: physical infrastructure, measurement, digital representation, cryptographic attestation, rule interpretation and execution, institutional outcome, and legitimacy/accountability. Lower layers are epistemic—they measure, represent, and validate physical energy events. The shift occurs when encoded rule systems, such as smart contracts, certification logic, compliance frameworks, and market-governance protocols, interpret cryptographically attested records to generate recognized institutional outputs such as renewable energy certificates, settlement claims, compliance statuses, payment rights, and ownership records, rendering the higher layers ontological and normative. This study contributes to blockchain governance, digital twins, and sustainable infrastructure research by theorizing blockchain-secured digital twins as systems of automated institutional constitution rather than mere information-integrity tools. It also surfaces a growing accountability gap: as institutional outcomes increasingly rely on encoded rules, platform designers, data modelers, authors of smart contracts, certifiers, and regulators may share accountability with physical actors. Full article