Search Results (422)

The proliferation of IoT deployments has exposed critical vulnerabilities in MQTT-based systems, particularly ciphertext-repetition leakage in telemetry encryption, where identical plaintext blocks under a fixed key—common for static sensor readings—collapse ciphertext entropy and expose traffic patterns. We present a parallel multibroker MQTT framework with two encryption variants: a hybrid AES-ChaCha20 cipher (NeoCipher) and an 8D chaotic system-enhanced variant (Chaos-NeoCipher). While AES-128 and base NeoCipher exhibit leakage (entropy falling to 3.9–4.0 bits/byte), Chaos-NeoCipher mitigates it entirely (7.996 bits/byte) through chaotic key schedule advancement on each invocation. Across 100+ nodes, 10 brokers, and five attack scenarios, consensus-based detection achieves near-ceiling performance governed by protocol logic rather than cipher choice. Chaotic tuning via Lyapunov sweep ($\mathrm{\lambda }$ ≈ 0.54 bits/iteration) and batched key-schedule optimization reduce overhead from +39.9 to +17.6%. Our results satisfy key IoT requirements: sub-millisecond cryptographic processing latency (measured as encryption/decryption time only, not including network transmission, broker queuing, or TCP overhead), near-complete detection across five attack classes under controlled simulation conditions, and mitigated single-point-of-failure vulnerability. Full article

A digital twin (DT) of an underground utility tunnel is valuable only if it remains synchronized with the physical asset. The objective of this study is to maintain this synchronization for an operational tunnel by automatically detecting displacements of linear and point assets, using only the fixed sensors already deployed in the tunnel. However, most DT research emphasizes design and construction, rather than operational-phase change detection. The BIM–GIS-based framework of our previous study was limited to relative-coordinate reporting, offline updating, and indoor mock-up validation. To this end, this study introduces a multimodal displacement detection framework with an automated, event-driven update workflow, which addresses these limitations and is demonstrated in an operational tunnel. Linear-object sag (power cables) is extracted from sparse, fixed fiber-scan LiDAR by adapting a recursive terrain-fragmentation ground filter into a wall-as-ground context. Point-object displacement (fire extinguishers) is detected using a single fixed CCTV camera, combining a YOLOv5 detector with a perspective transform to recover absolute coordinates in a GNSS-denied corridor and differentiate between moved and toppled assets. Detected displacements are serialized as JSON and streamed via a Kafka broker into the DT service environment, integrating heterogeneous events into a unified synchronization workflow. Field validation against a co-located survey-grade scanner confirmed agreement within the 0.10 m operational validation tolerance for nominal sags of 7, 10, and 15 cm, with the largest residual at the smallest deflection. The framework maintains the virtual model consistent with a physical tunnel without additional instrumentation, enhancing disaster prevention and response. Full article

Recent studies demonstrate growing interest in supervisory systems based on open architectures, but existing implementations report fragmented combinations of functions and validation evidence. This study developed and functionally validated an open four-layer SCADA-based supervisory architecture for an experimental reverse osmosis (RO) system. Eleven commercial off-the-shelf sensors were integrated through ESP32-based acquisition, MQTT communication, a Raspberry Pi/Flask edge server, SQLite persistence, and a browser-based human–machine interface (HMI). Validation combined historian analysis, controlled functional scenarios, bidirectional configuration tests, service-recovery trials, and a 600 s edge-resource assessment. The historian contained 190,840 records covering all eleven tags, with values, states, units, and timestamps. Controlled tests verified coherent measurement-state processing, alarm persistence and acknowledgment, thermal-dependency handling, stopped-state logic, diagnosis, and HMI presentation. Valid configuration changes were confirmed by the ESP32, whereas an out-of-range coefficient was rejected without changing the active value. All backend, broker, communication-path, and edge-server recovery trials met predefined criteria, with median recovery times of 6.384, 1.312, 1.517, and 90.604 s, respectively. During the controlled workload, 6600 MQTT publications and 480 HTTP requests were processed without errors, and SQLite integrity was preserved. The results demonstrate integrated cross-layer operation under the tested conditions. The architecture did not implement automatic closed-loop control of pumps or valves. Metrological performance, cybersecurity, usability, and scalability were outside the validation scope. Full article

This article examines the dual-brokerage regimes governing Vietnamese labour migration to South Korea, situating migration governance within broader debates on Asian capitalism and developmental state transformations. Drawing on the Employment Permit System (EPS) as a paradigmatic case of state-led migration management, we analyse how public brokerage mechanisms—embodied in Vietnam’s Department of Overseas Labour (DOLAB) and licensed sending organisations—intersect with private intermediaries to shape migration pathways. The analysis reveals structural tensions between Korea’s developmental state ambitions to regulate low-skilled labour flows and Vietnam’s export-oriented migration regime, where private brokers extract substantial fees from aspiring migrants. These tensions are amplified in new growth industries—care work, manufacturing, agriculture, and construction—where labour demand intersects with gendered migration patterns and debt-financed mobility. We argue that the Vietnam–Korea migration corridor exemplifies a distinctive form of ‘brokerage capitalism’ within Asian migration governance, where state institutions and private actors co-produce regulatory spaces that simultaneously facilitate and exploit migrant workers. The article contributes to scholarship on Asian capitalism, migration brokerage, and developmental state theory by demonstrating how migration governance reflects broader patterns of variegated capitalism in East and Southeast Asia. Full article

This paper presents a decoupled Extended Reality (XR) and Digital Twin (DT) framework for robotic manipulators, leveraging mathematical, physical, and topological symmetries to achieve stable cyber–physical synchronization. Traditional robotic teleoperation architectures suffer from tight coupling between low-level control, communication, and visualization interfaces, making them vulnerable to network latency and platform dependencies. We propose an open, modular framework that structurally decouples physical and virtual counterparts. By establishing a system-theoretic formulation of Digital Twin symmetry, we represent the virtual robot as an isomorphic state-space mirror of the physical manipulator. Communication is mediated by an asynchronous, network topology using a lightweight Message Queuing Telemetry Transport (MQTT) broker, ensuring topic-based communication symmetry. This decoupled structure enables a highly flexible, many-to-many evaluation paradigm, allowing researchers to interchangeably pair a single physical robot with diverse user interfaces (UIs) or control multiple heterogeneous robots (physical and simulated) with a single virtual interface. Experimental validation on a 7-Degree-of-Freedom (7-DOF) Franka Emika Panda robot and a unified data collector confirms high-fidelity tracking, with a symmetric wired and wireless Round-Trip Times (RTT) averaging 47 ms. Finally, we discuss the challenges of transitioning this laboratory-scale architecture to high-concurrency industrial settings, addressing single-broker vulnerabilities, network jitter, and dynamic calibration drift. Full article

Cross-university scientific mobility has become an important mechanism through which universities access external knowledge, sustain inter-organizational relationships, and accumulate social capital. Existing studies have mainly examined university positions in scientific mobility networks through inflows, outflows, and general centrality, while paying less attention to brokerage roles jointly shaped by inflow sources and outflow destinations. Conceptualizing cross-university mobility as a global scientific mobility system, this study examines how universities occupy differentiated brokerage roles and how these roles are associated with research performance within different national network environments. Using ORCID researcher profile data, ROR institutional identifiers, and Web of Science publication data, we constructed a university-year panel and identified five brokerage roles, namely coordinator, gatekeeper, representative, itinerant broker, and liaison, using countries as group boundaries. We further considered the national relational environment from the dimensions of external and internal social capital, using national external centrality and domestic network density to characterize the corresponding network conditions. The results show that coordinator, gatekeeper, and representative roles are positively associated with research performance, while the liaison role is more positively associated with research performance than the itinerant broker role. As national external centrality increases, the association between itinerant brokerage and research performance becomes more positive. As domestic network density increases, the association between gatekeeper brokerage and research performance becomes more positive in the full-panel models, although the statistical evidence for this pattern is sensitive to alternative specifications and remains exploratory. This study provides a multilevel perspective for understanding university scientific mobility by examining differentiated university brokerage roles and the national network conditions in which they are embedded. Full article

Background/Objectives: Supporting families during end-of-life care in intensive care units is clinically, emotionally, and ethically demanding, and nurses’ experiences of this work in Saudi Arabian intensive care settings remain underexplored. This study explored nurses’ experiences of providing psychosocial and emotional support to families during end-of-life care, including their role in treatment-limitation and goals-of-care discussions. Methods: A qualitative descriptive study, analyzed using reflexive thematic analysis from a contextualist position, was conducted with 15 intensive care nurses across three healthcare facilities in Riyadh. Ten were Saudi nationals and five internationally recruited; eleven had Arabic as a first language. Semi-structured interviews were conducted in Arabic (n = 11) or English (n = 4) between December 2025 and February 2026 and coded in the language of collection. Results: Three themes were developed: doing relational work inside a system organized for clinical throughput; carrying what the work leaves behind; and standing between, brokering understanding for families. Nurses described having no formal decision-making authority while shaping what families understood and what the clinical team heard. Conclusions: Nurses positioned themselves as intermediaries between families and clinical teams. This relational work was shaped by staffing, formal preparation, access to palliative care, and physician recognition of the nursing role. Strengthening these organizational conditions may support more consistent family care. Full article

Automated surface defect detection in hot-rolled steel is a prerequisite for real-time quality control, yet most deployed inspection systems operate in isolation from Industrial Internet of Things (IIoT) infrastructure. This paper reports a laboratory-scale proof of concept with two contributions. The first is a segmentation study on the Severstal dataset using a leakage-free, defect-stratified split of 1886 test images. Because a trivial all-background predictor already attains 96.66% pixel accuracy, performance is reported through Dice, IoU, precision, recall, and F1 with 95% confidence intervals. A compact from-scratch U-Net (0.49 M parameters) reaches a Dice of 0.416 at 38.6 ms per image, an ImageNet-pretrained DeepLabV3+ model reaches 0.677 at 46.3 ms and 37 times the parameters, and a classical Otsu baseline reaches 0.060, bracketing an explicit accuracy-versus-footprint design space rather than a single recommended model. The second contribution is architectural: a three-layer IIoT architecture whose messaging layer is empirically characterized on a Raspberry Pi broker over 158,500 messages. A factorial experiment isolates the transport configuration of the broker, rather than that of the publisher, as the determinant of end-to-end latency, yielding a seventeen-fold reduction. The layer sustains 1920 messages per second without loss, and a deliberate broker outage shows that MQTT delivery guarantees are semantic rather than temporal, motivating an application-level message-expiry policy. Embedded inference deployment is identified as the primary next step. Full article

Background: Smallholder farmers are at the forefront of climate change, necessitating dynamic, continuous adaptation strategies to safeguard their livelihoods and food systems. Although climate-smart technologies and indigenous knowledge are available, traditional top-down agricultural extension models often fall short in promoting inclusive, community-driven ownership, which is vital for long-term resilience. Objective: This paper investigates how effective knowledge brokering can augment the agricultural extension system—facilitating connections among researchers, extension agents, and smallholder farmers—to maintain climate resilience and foster inclusive, locally led adaptation (LLA). Methods: Drawing on the IDRC–Step Change SCALE project, implemented between August 2025 and May 2026, this study assesses the effect of targeted capacity-building interventions within the extension system. By employing active knowledge-brokering mechanisms such as safe-spaced KIIs, FGDs, co-creation workshops, and capacity-building workshops, the project enabled ongoing, bidirectional learning. This strategy ensured that scientific innovations were adapted into context-specific practices, while indigenous knowledge and local priorities directly influenced ongoing agricultural research. Pre- and post-intervention assessment scores were compared using paired-samples t-tests with exact Wilcoxon signed-rank confirmation, taking the knowledge area as the unit of analysis; differences between training rounds were tested by randomized complete block ANOVA with orthogonal country, phase, and country-by-phase contrasts; and qualitative data from KIIs and FGDs were analyzed thematically. Results: The findings indicate that knowledge brokering transforms the extension system into a responsive foundation for agricultural resilience. Key outcomes include a mean knowledge gain of 53.8 percentage points across the four capacity-strengthening rounds, from 26.5% pre-training to 80.3% post-training (95% CI 51.4 to 56.3; paired t(27) = 44.78, p < 0.001), with improvement recorded in all seven knowledge areas in all four rounds; sustained adoption of climate-adaptive technologies across 1042 participant attendances in Nigeria and Senegal; enhanced participation of marginalized groups, with women accounting for 568 attendances (54.5%) overall, though ranging from 38.9% to 60.2% between rounds; and a clear transition toward self-sustaining, locally led adaptation practices. Conclusions: To effectively confront climate uncertainty, agricultural extension must evolve from a mere information dissemination system into an interactive, knowledge-brokering network. Strengthening this system is a vital, scalable pathway to maintaining inclusive resilience in smallholder agriculture. Full article

Criminal ecosystems are durable social systems in which differentiated criminal functions become recurrently interdependent across organizations, networks, illicit markets, institutional actors, financial facilitators, territorial brokers, and social environments. The concept applies when coercion, illicit accumulation, political protection, territorial regulation, and other specialized capacities depend on one another over time and become structurally coupled with institutional, sociocultural, spatial, or technological conditions. A criminal ecosystem is therefore not defined by the presence of a particular organization, market, or territory, nor by resilience itself. It is identified by functional differentiation, recurrent interdependence, structural coupling, and temporal reproduction. Complex adaptive systems theory explains how decentralized interactions can generate adaptation, substitution, and emergent order, while autopoietic social systems theory explains how recurring communications stabilize expectations and reproduce boundaries. Digital infrastructure can mediate financial and transnational functions without constituting a separate operational dimension in the present framework. This distinction allows resilience, reconfiguration, displacement, and decline to be examined as empirical outcomes rather than assumed properties of the ecosystem. Full article

Smart-city services increasingly rely on Internet of Things (IoT) deployments using lightweight Message Queuing Telemetry Transport (MQTT), yet weakly protected systems remain exposed to spoofing, unauthorized state changes, and limited accountability. This work evaluates blockchain and smart contracts as a complementary trust layer for MQTT-based smart-city IoT rather than as a replacement for transport-layer security. The proposed architecture provides owner-controlled device registration, per-sensor nonce management, replay-resistant Elliptic Curve Digital Signature Algorithm (ECDSA) authentication, authorization of state-changing operations, and tamper-evident event logging. MQTT confidentiality remains dependent on Transport Layer Security (TLS) or payload encryption. A prototype was implemented using ESP32 microcontrollers, a Raspberry Pi MQTT broker, Node-RED supervision, MongoDB storage, and Ethereum smart contracts deployed on Sepolia. The evaluation combines practical attack scenarios (unauthorized sensor modification, identity spoofing, and data manipulation) with measurements of blockchain latency, throughput, and gas consumption. Results show auditable nonce-bound signed updates, with mean transaction latency close to 12 s. Because the contract updates one sensor per transaction, costs are interpreted per confirmed write operation and scenario size. The findings position blockchain as an audit and policy-enforcement component for MQTT-based IoT. Full article

This article presents an experimental evaluation of the data-transmission performance of an IoT device communicating with an MQTT broker over a local IEEE 802.11n Wi-Fi network in the 2.4 GHz band, coexisting with modern Wi-Fi networks based on the IEEE 802.11ax (Wi-Fi 6) and IEEE 802.11be (Wi-Fi 7) standards. The effect of sharing the radio medium on the communication quality parameters of the IoT device, such as end-to-end delay, jitter, the packet delivery ratio (PDR), and application throughput (goodput), was assessed. Unlike previous work, which focuses primarily on PHY/MAC metrics or on simulation-based analysis, this study targets the application layer (MQTT) from the perspective of a legacy IoT end-device. The results presented and discussed herein show that the presence of 802.11ax and 802.11be networks in the 2.4 GHz band can significantly degrade the temporal parameters of MQTT transmissions performed by IoT devices operating in the older 802.11n standard. The greatest impact is observed in jitter and in the extreme delay values (for instance, in the worst-case coexistence scenario—with simultaneous Wi-Fi 6 and Wi-Fi 7 interference, the P95 delay increased from 38 to 869 ms), whereas the PDR remains relatively high because retransmissions compensate for packet losses at the expense of delay. Full article

The study addresses the design and development of a unified corporate information system for multimodal transport and logistics companies engaged in maritime and railway transportation. Analysis of the existing literature revealed the absence of a coherent methodological framework for the design of corporate information systems tailored to the specific operational characteristics of multimodal transport and logistics enterprises. To bridge this gap, a design methodology for corporate information system databases is proposed, intended for subsequent deployment in companies operating multimodal supply chains. The development of the unified corporate information system was guided by the principle of “total costs,” which requires that the decision-maker—when selecting transport modes, methods of transportation, carriers, routing, and auxiliary intermediaries (insurer, stevedore, bank, and customs broker)—address the problem as an integrated whole rather than optimizing individual components in isolation. The study encompasses information modeling of the business processes of multimodal transport and logistics companies, construction of an optimal model of the transport process for maritime and railway transportation using integrated computer automated manufacturing definition (IDEF) and structured analysis and design technique (SADT) modeling, and the design of a multilevel unified database structure for the coordination of different transport modes. A decision-making and support system has been developed for managing the operational activities of a multimodal transport and logistics company engaged in maritime and railway transportation. The proposed unified corporate information system enables the replacement of task resolution by local optimization criteria applied separately to each transport mode—such as freight cost and delivery time—with a single global optimization criterion for the multimodal supply chain. Full article

Smart-building systems need reliable sensing, long-term storage, and remote control, but many studies mix up fast network response with slow physical changes in the building. We report measurements from an openHAB deployment at University Lab 1 and University Lab 2 in Greece over 19 months (April 2024–October 2025), with Z-Wave and ZigBee devices and Parquet exports for offline analysis. We treat sensing availability, Message Queuing Telemetry Transport (MQTT) command latency, and heating, ventilation, and air conditioning (HVAC) behavior as separate questions. In March–June 2024, raw record-level temperature field availability was 79.7% and 74.2% at University Lab 1 and University Lab 2, respectively, increasing to 99.7% and 98.5% after the <30 min linear field interpolation used in golden-dataset construction; assessable device-month cadence-normalized reading-count ratios were far lower (7.9% temperature and 13.0% humidity under the 300 s assumption at University Lab 1; humidity 7.8–26.0% across 180–600 s), reflecting heterogeneous archival participation rather than a fully populated expected-cadence denominator over the full archive span. In May–June 2024, 1247 MQTT commands yielded 1246 successful correlated responses; the archived application log contained no repeated correlation identifiers or duplicate response records (broker DUP flags are not archived); median, p90, and p99 latencies were 287 ms, 487 ms, and 1.66 s. These times describe the MQTT–edge-agent–openHAB path only, not physical device action. HVAC figures are illustrative; we do not infer settling times. The results show why availability metrics, archive denominators, and response-time boundaries must be defined separately in smart-building evaluations. Full article

Objective: To synthesise contemporary Australian evidence on how local governments act to support healthier, sustainable and equitable food environments, and to examine the governance arrangements, policy and planning levers, monitoring practices, and implementation conditions shaping local action. Methods: A rapid review of peer-reviewed and grey literature published between January 2015 and February 2026 was performed. Searches were conducted in Medline Complete, CINAHL Complete, Health Policy Reference Centre and Scopus, alongside structured grey literature searches. Included documents addressed Australian LG food environment roles, policies, planning, governance, or monitoring. Findings were narratively synthesised and mapped to national research priorities. Results: Thirty-eight documents were included (23 peer-reviewed studies and 15 grey literature reports). Evidence clustered most strongly around food systems and food security, governance and multisectoral partnerships, and food environment monitoring, particularly food access profiling, affordability monitoring and mapping activities. In contrast, the extent of coverage on statutory planning mechanisms, formal regulatory powers, and consumer behaviour outcomes was limited. Reports of evaluated interventions were concentrated in bounded organisational settings where councils held clearer jurisdiction, such as sport and recreation facilities. Across contexts, LGs were commonly positioned as convenors, brokers and enablers operating within constrained mandates and fragmented multi-level governance settings. Reported enablers included leadership, dedicated resourcing, partnerships and access to local data; common barriers included limited statutory authority, short-term funding and weak vertical policy integration. Conclusions: Australian local governments are active food system actors, but stronger statutory integration, clearer decision pathways, and more consistent monitoring and evaluation are needed to translate local activity into sustained improvements in healthy, sustainable and equitable food environments. Full article