Search Results (94)

Saudi Arabia has committed to one of the world’s largest urban greening programmes, yet whether its land administration system can hold, value, and sustain the resulting assets remains unexamined. This study assesses that readiness under Vision 2030 and SDG 11, with Riyadh as the delivery case. Forty-one legal, institutional and policy instruments were analysed against a purpose-built rubric, the NbS Land Administration Readiness Assessment, which crosses Land Management Paradigm functions with Framework for Effective Land Administration pathways and nature-based solution requirements. The indicator profile is uneven: capabilities for creating green infrastructure average 2.25 of 4; capabilities for recording, valuing and sustaining it average 1.38. The summary index is 41.7 percent, ranging 29.2 to 54.2 across scenarios, so the band label is less robust than the profile shape. No green-specific registrable interest, no green amenity adjustment and no statutory maintenance duty were identified in the analysed corpus, and the strengthened white land fee is hypothecated to housing. The corpus is English-language-only and scoring was performed by a single assessor, so these are non-identifications rather than demonstrated nonexistence. That states may build green infrastructure before becoming able to institutionalise it is offered as a proposition for comparative testing. Full article

This study reconstructs the agricultural landscape of Cyprus in the early 1830s, a time of extraordinary socio-economic pressures on the island and immediately prior to the economic and administrative transformations of the later nineteenth century, drawing on the Ottoman property survey of 1832/33, an island-wide register documenting over 20,000 households and their assets across 622 principal settlements. The records were converted into a geospatial database and analysed through GIS, spatial statistics, and a transparent, reproducible landscape classification framework, complemented by historical cartographic evidence. The reconstruction reveals distinct agricultural regions shaped by environmental conditions, settlement patterns, and the interplay between subsistence and market-oriented production, with marked concentrations of viticulture, olive cultivation, cotton, grain, sericulture, and pastoralism. A hierarchical classification assigns 471 settlements (77%) to a single-dominant landscape type, 92 (15%) to co-dominant zones, and 50 (8%) to diversified categories, collectively synthesised into a broader interpretation of the landscape as an integrated socioecological system. The findings demonstrate that Ottoman surveys offer considerable, albeit bounded, potential for historical landscape reconstruction, providing a dated baseline for the study of Mediterranean agricultural landscapes and a transferable methodological framework applicable to any region with comparable historical records. Full article

Higher education institutions operate complex digital environments that combine administrative services, research infrastructures, learning platforms, identity systems, and heterogeneous departmental IT. In the European Union, the NIS2 Directive increases the need for structured cybersecurity governance, while ISO/IEC 27001:2022 provides a mature information security management system standard that can support implementation. This paper proposes a design science artefact for aligning NIS2 obligations with ISO/IEC 27001:2022 clauses and Annex A controls in the context of higher education institutions. The framework organizes cybersecurity governance, asset and service scoping, risk management, incident handling, business continuity, supplier and cloud dependencies, access control, awareness, monitoring, and continual improvement into a staged maturity model. The artefact is instantiated for a Romanian public university context and assessed through internal traceability analysis, including mappings between NIS2 Articles 20, 21, and 23, Romanian NIS2 transposition requirements, and ISO/IEC 27001:2022 control areas. The institutional illustration identifies candidate assessment domains and evidence requirements but does not assign maturity levels because the internal records required by the scoring protocol were unavailable; it therefore does not constitute an audit, verified institutional measurement, or empirical validation. The contribution is therefore a structured and reusable compliance design artefact, together with a transparent mapping method that can support future expert validation, institutional pilots, and audit-oriented refinement. Full article

Tropical mid-size cities on alluvial floodplains face compounded flood challenges combining pluvial accumulation from intense convective storms, regulated river overflow, and aging drainage networks. This study presents an integrated framework for Monteria, Colombia (~450,000 inhabitants; Sinu River, Caribbean lowlands), within Colombian Decree 1807/2014 and structured in four phases. (1) Hazard: A Rain-on-Grid 2D HEC-RAS 6.6 model covering 4090 ha, calibrated against four gauged events, identifies three dominant pluvial mechanisms (poor hydraulic connectivity, limited evacuation capacity, downstream channel overflow), plus 17 critical fluvial erosion points affecting ~289 properties at 100-year return period. (2) Vulnerability: Depth-damage functions from 1465 household surveys yield 36.36% of 3015 assets in high risk and 57.77% in medium risk. (3) Measures: Scenario M2 (channel widening plus dikes, land-raising, retention lagoons) removes 80 ha of flooding while displacing 28 ha at COP 845 million pre-design cost. Non-structural measures include a Sustainable Urban Drainage Master Plan, IoT-based Early Warning System, minimum construction-elevation map, and land-management instruments. A Monte Carlo residual-risk model reduces baseline risk to 19.9% under full implementation. (4) Emergency: A February 2026 cold-front event was addressed with a 4300 m perimeter dike and six pump stations deployed jointly by the Regional Environmental Authority (CVS) and Municipal Administration. Full article

Against the backdrop of rapid digital acceleration and a tightening UK labor market, Small and Medium-sized Enterprises (SMEs) are pressured to move beyond manual administrative processes to bridge the national productivity gap. This study investigates how Human Resource Information Systems (HRIS) transform HR functions from administrative burdens into strategic assets within resource-constrained UK SMEs. Adopting an interpretivist, multiple case study qualitative approach, data were collected through semi-structured interviews with 12 HR managers across the hospitality, retail, and recruitment sectors and analyzed using thematic analysis via NVivo 14. The findings reveal a three-stage, non-linear pathway of value creation: administrative liberation through automation, strategic visibility via data-driven insights, and digital friction stemming from cultural and structural barriers. While HRIS enhances operational efficiency and evidence-based decision-making, its strategic value is mediated by organizational readiness, digital literacy, and change management capabilities. This research contributes to strategic human resource management literature by conceptualizing “digital friction” as a key mediating construct between technology implementation and value realization under resource poverty. For practitioners, it provides a deployment roadmap highlighting that managing the socio-technical “human element” is as critical as the core technological infrastructure for long-term competitiveness. Full article

The ongoing evolution of Industry 4.0 technologies necessitates novel and effective modes of human–machine interaction within production environments. This work presents a modular approach to the design and implementation of graphical user interfaces (GUI) in mixed reality, leveraging the Asset Administration Shell (AAS) standard. The proposed method enables the dynamic rendering of GUI elements in a Mixed Reality setting based on structured data retrieved from an AAS server. Developed for the Microsoft HoloLens 2 using the Unity engine and the Microsoft Reality Toolkit 3 (MRTK3), the system allows for the spatial placement of interface components either at predefined coordinates or in relation to specific elements of a production line model. Additionally, it incorporates a real-time distributed architecture utilizing OPC UA PubSub and MQTT protocols for processing and visualising live data. The prototype demonstrates the viability of using AAS as a flexible framework for defining and generating GUI components in immersive environments and lays the groundwork for further research into standardised, easily deployable user interface solutions for industrial applications. Full article

Institutional adoption of blockchain technology in supply chains, healthcare, and public administration remains constrained. Organizations that manage digital assets on behalf of large numbers of non-technical users lack custody architectures suited to their scale. Existing approaches either require users to manage private keys directly; rely on centralized custodians that store encrypted keys; or depend on distributed protocols such as multi-party computation, which impose substantial infrastructure and coordination overhead. This paper presents CryptoVault, a stateless custody architecture for institutional blockchain deployments that derives private keys on demand from a single master seed using BIP-44 hierarchical deterministic (HD) wallets, eliminating persistent storage entirely. Only an AES-256-GCM-encrypted derivation index is persisted per wallet; the corresponding private key is re-derived at signing time and discarded immediately after use, ensuring no private key material ever rests on disk. The security model requires the simultaneous compromise of three independent components (the encrypted derivation index, the encryption key, and the master seed) for full key recovery, compared to two components in custody systems that persist encrypted private keys. An empirical evaluation under concurrent load demonstrates 13 to 22 ms steady-state signing latency on development hardware, with re-derivation accounting for approximately 4 to 7% of that total, confirming that on-demand derivation introduces negligible overhead. Thus, CryptoVault has been validated against an agricultural cooperative deployment as a representative institutional scenario, with an architecture that generalizes to any organization managing wallets on behalf of users who have no direct interaction with cryptographic material. A reference implementation is available as open-source software. Full article

Industry 4.0 and 5.0 technologies have made industrial environments data-rich, yet a persistent cognitive gap remains: operators face substantial difficulty interpreting and acting on this data in unstructured, time-critical situations. This paper presents an architecture that integrates the Asset Administration Shell (AAS), OPC UA, and a Large Language Model (LLM)-based agentic AI within a mandatory Human-in-the-Loop (HITL) framework. The AAS acts as a semantic grounding layer through Retrieval-Augmented Generation (RAG), supplying the LLM agent with ECLASS-referenced technical parameters that reduce the risk of hallucination. OPC UA Methods form a deterministic execution layer that keeps agent actions within PLC-validated safety boundaries. The HITL mechanism enforces a cryptographic approval gate so that no physical machine action can occur without documented human authorization. This requirement was motivated by an industrial survey ($n=117$), in which 47% of employees stated that human oversight is irreplaceable, combined with enterprise safety and accountability requirements and broader governance considerations for AI-driven actuation in safety-critical cyber-physical systems. Two proof-of-concept case studies evaluate the architecture under controlled laboratory conditions. Proof-of-concept results indicate system processing latencies of 1.7 s (maintenance) and ∼15 s (scheduling), with end-to-end latencies (including mandatory human approval) of 14.9 s and 62 s, respectively, representing estimated improvements of approximately 97% and 96% over expert-estimated manual baselines (∼8 min and 25–40 min). All figures derive from single scripted runs under controlled laboratory conditions and should be read as indicating architectural feasibility at Technology Readiness Level 4, not as statistically validated performance benchmarks: variability bounds and confidence intervals are unavailable, the manual baselines are expert estimates rather than instrumented measurements, and operator deliberation times derive from a single response per scenario. A structured comparison with related work shows that, to the authors’ knowledge, no published approach in the surveyed literature combines AAS semantic grounding, OPC UA deterministic execution, and mandatory cryptographic HITL within a single empirically grounded framework. Full article

Chaos engineering is currently being used by some of the largest software companies in the world to develop IT systems that can withstand turbulent production conditions. This study presents an approach for applying chaos engineering across manufacturing systems to improve system resilience. For this purpose, the proposed chaos twin framework includes a four-step process for the manufacturing and interlinked digital twin system. A case study is discussed based on a material flow simulation. The case study shows the example implementation of the chaos twin framework for improving the resilience of a manufacturing system. The research intends to enhance the field of designing and operating manufacturing systems by demonstrating novel perspectives on applying chaos engineering within the cyberspace. Additionally, the research intends to provide a more industry-oriented guide to facilitate the practical application of chaos engineering within the manufacturing industry. Full article

The real estate market is a complex and dynamic sector that plays a key role in economic stability and wealth generation. In many regions, real estate assets represent around 80% of household wealth, while rising housing prices have turned access to housing into a major social and economic challenge. In this context, the availability of accurate and accessible information is essential for decision-making by buyers, investors, and public administrations. This study proposes the development of an advanced technological tool based on Artificial Intelligence and Machine Learning techniques to predict and analyze real estate market dynamics within a specific geographic area. Using the city of Madrid as a case study, the research presents a digital application capable of estimating the market value of a property by analyzing comparable recently sold properties and incorporating key housing characteristics. By entering an address and a set of property features, the system generates a precise and data-driven valuation. The results demonstrate that AI-based approaches can significantly improve the accuracy and accessibility of real estate valuation processes. The proposed methodology enables real-time price estimation, graphical comparisons, and dynamic market analysis. Furthermore, the framework is scalable and can be extended to other geographic areas where relevant data are available, providing valuable insights for both academic research and practical decision-making in the real estate sector. Full article

Road safety barriers represent a core component of the road with relevant consequences on effective safety for users. Maintaining these components in adequate conditions, within the quality admissibility thresholds, in compliance with all economic and management constraints, is a primary need for road administrators. In this paper, the authors propose an original procedure to classify the state of efficiency of road safety barriers, at the network scale and relying on conventional administrative data, in an optimized BIM environment, to simplify evaluations and management procedures. Through purpose-built algorithms based on selected geometric and functional parameters of the different road barriers, the algorithm provides a preliminary classification of the various segments, evidencing attention class indicators, useful as preliminary alert signals and for anticipating detailed investigations that can ensure significant economic efficiencies. The method was tested on a 10 km long motorway segment in Italy, evidencing the potential advantages of such an innovative approach to support, as a final goal, a comprehensive infrastructure digital model for virtual inspections, evaluating road component “health” state and properly implementing maintenance strategies. This approach improves network-scale monitoring and maintenance-related activity prioritization phases for road safety barriers, leveraging administrative data. This methodology functions as a BIM-based asset screening tool, as it offers a digital decision support system that identifies critical segments, to optimize the allocation of physical resources and prioritize on-site inspections where they are most needed. Full article

Agricultural enterprises serve as the cornerstone of food security. However, they operate under significant resource constraints and environmental risks. Adopting a systems lens, this study examines digitalization as a critical variable reshaping the input–output logic of agribusinesses. Using a longitudinal panel dataset of Chinese listed agricultural firms from 2013 to 2022 and Ordinary Least Squares regression, the study empirically identifies the mechanisms driving ESG performance. The results demonstrate that digitalization significantly enhances overall ESG performance, functioning as a governance mechanism that improves internal resource integration and transparency. Critically, the moderation analysis reveals a dynamic substitution relationship among system elements. Traditional inputs, specifically management expenses, financial slack, and intangible assets, exert significant negative moderating effects. This confirms the logic of factor substitution, suggesting that as digitalization advances, traditional governance modes relying on high administrative costs face diminishing marginal returns. In the environmental dimension, digitalization facilitates a transition from post-event remediation to whole-process control through intelligent traceability, effectively internalizing external constraints and reducing waste emissions. Additionally, heterogeneity analysis highlights significant structural variations. The ESG-enhancing effect of digitalization is more pronounced in firms characterized by high financial leverage, low long-term debt, and low industry concentration. Spatially, the marginal improvement is stronger in Western regions compared to the East, underscoring the Hu Huanyong Line as a critical structural boundary. Ultimately, digitalization serves as a core governance element that drives the structural transformation from traditional operating paradigms to digital governance architectures, thereby providing a robust pathway for corporate sustainability. Full article

To enhance the measuring capabilities of modern Non-Destructive Evaluation (NDE) devices, it has become essential to integrate standardized digitization services and industry-compliant functionalities. This perspective paper examines approaches for improving NDE systems by incorporating key Industry 4.0 technologies, specifically digital representations such as the Asset Administration Shell (AAS) and OPC UA (Open Platform Communications Unified Architecture). We discuss requirements for interoperable, semantically rich descriptions of NDE systems, outline how OPC UA information models and AAS submodels can be combined with MQTT-based transport, and illustrate these concepts through representative prototype implementations, including predictive maintenance and chatbot assistant use cases. By leveraging these technologies, NDE devices can be transformed into interoperable, data-rich, and intelligent components within smart industrial ecosystems. Compared with previous studies, this Perspective is the first to systematically bring together the requirements, architectural patterns, and evaluation criteria for digital representations designed specifically for NDE systems. It also provides, in a practical and accessible way, NDE-focused OPC UA and AAS-based architectures that support both predictive maintenance and LLM-assisted operator guidance. The presented implementations are at an early stage and serve as illustrative examples, while systematic quantitative validation is ongoing and is outlined as future work. Full article

Manufacturing enterprises face increasing complexity in managing the complete life cycle of production systems, requiring integration of information from diverse sources to support timely maintenance, diagnostics, and operational decisions. This paper presents a comprehensive service-oriented architecture (SOA) for decision support in industrial life-cycle management, integrating real-time monitoring, predictive maintenance, and collaborative problem-solving across extended manufacturing enterprises. The architecture implements a three-layer service model comprising eight core collaborative services, three application services, and six life-cycle management services, orchestrated through a risk assessment module that monitors life-cycle parameters and triggers appropriate maintenance, diagnostics, or hazard prevention actions. The system was developed in the context of a European research project and validated in two industrial settings: automotive assembly lines at a German SME and air conditioning manufacturing at a Portuguese company. Results demonstrated substantial operational improvements, including reduced problem resolution time, lower diagnostic travel requirements, reduced spare-parts consumption, and increased structured problem registration. The original SOAP-based web-services implementation is further contextualized within the contemporary Industry 4.0 landscape through comparison with microservices architectures and discussion of integration paths involving OPC UA, Asset Administration Shells, and digital twins. The paper contributes a validated reference architecture for service-based industrial life-cycle management and clarifies its relevance as an early precursor of contemporary smart manufacturing approaches. Full article

Complex products and production processes are intertwined and demand expressive, lifecycle-wide digital representations. The Asset Administration Shell emerged as a standard for Digital Twins (DTs), structuring heterogeneous data across cloud-based Industrial Internet of Things (IIoT) infrastructures. However, today’s deployments predominantly realize passive or reactive DTs, while intelligent behavior remains underexploited. This paper addresses this gap, proposing an end-to-end architecture operationalizing the DT Reference Model through the integration of machine-interpretable granulated industrial skills, which are semantically accumulated into a knowledge graph enabling discovery and reasoning, while a multi-agent system provides autonomous, utility-based negotiation via machine-to-machine interactions within a federated marketplace. The approach is applied in a real smart manufacturing demonstrator, combining order processes, production orchestration, and lifecycle documentation into a unified execution pipeline spanning IIoT-connected shopfloor assets and cloud-based services. Quantitative experiments evaluating negotiation latency, renegotiation robustness, and utility variation demonstrate stable, predictable behavior even under concurrent demand and failure scenarios. The architecture lays a foundation for interoperable, sovereign collaboration across value chains to realize shared production. The results underline the effectiveness of the tightly coupled enabler technologies realizing proactive, reconfigurable, and semantically enriched intelligent DTs. Full article