Search Results (429)

Automatic milking systems (AMSs) are increasingly adopted in dairy farms, and barn design, particularly regarding cow traffic design (CowTD), plays a key role in system performance. This study evaluated the association between different CowTDs and operational and production indicators of AMS Brazilian dairy farms. The data were obtained from 149 commercial dairy farms equipped with AMS (average of 1.6 AMS per farm) encompassing approximately 14,642 lactating cows recorded between June and December 2025. Cow traffic designs were classified as free or smart-gated systems, including milk-first (MF) and feed-first (FF) configurations. Mixed models were used to evaluate the effects of regions, housing system, and CowTD on the number of lactating cows per AMS (NCowsAMS), milking frequency (MFreq), milk yield per milking (MYMilking), daily milk yield per cow (MYcow), daily milkings per AMS (MilkingsAMS), and daily milk yield per AMS (MYAMS). On average, farms milked 58 cows per AMS with a mean MFreq of 2.69 milkings/cow per day and produced 2227 kg of milk per AMS per day. Smart-gated CowTD supported a greater number of cows per AMS than free CowTD systems (FF = 57 and MF = 58 vs. Free = 53 cows/AMS). Although free CowTD increased MFreq to approximately three milkings/cow/day, this advantage did not translate into greater or equivalent MYAMS, despite MF and free CowTD exhibiting similar MYcow (37.0 and 37.2 kg/day, respectively). Even though free CowTD achieved the highest MilkingsAMS (Free = 156 vs. MF = 151 and FF = 143 milkings/day), it milked fewer cows per robot, resulting in lower MYAMS. Consequently, FF and MF systems produced 86 and 180 kg/day more MYAMS, respectively, than free CowTD. These results suggest that AMS performance is primarily driven by the NCowsAMS rather than MFreq alone. Under Brazilian commercial conditions, smart-gated CowTD systems appear to be more efficient, as evidenced by higher MYAMS, while allowing higher stocking densities, potentially without increasing labor requirements. Full article

Accurate positioning is essential for inspection robots in caged chicken houses, where long straight corridors, sparse textures, and repetitive structures challenge conventional methods. This paper proposes CVIWM (Coupled Visual-Inertial-Wheel Odometry with Markers), a tightly coupled state estimation method that fuses visual, inertial measurement unit (IMU), wheel odometry (WO), and fiducial marker observations within a factor graph optimization framework. Wheel odometry preintegration suppresses IMU horizontal drift and provides absolute scale, while sparse AprilTag markers (10 m spacing) periodically reset accumulated errors. Experiments in an 80 m corridor of a commercial caged chicken house at 0.116 m/s and 0.232 m/s showed that CVIWM achieves average positioning errors of 2.402 cm and 3.253 cm. This high precision ensured reliable image acquisition (image shift $<83$ pixels), enabling 95.7% dead hen detection and 98.9% egg detection accuracy. CVIWM offers a low-cost, easy-to-deploy, high-accuracy solution for automated poultry house inspection, supporting smart livestock farming. Full article

This study proposes and implements a hierarchical communication system for inspection robots operating in practical caged broiler houses, where confined aisles, multi-tier cages, dust, humidity, and fluctuating wireless coverage impose challenges on stable remote inspection. The system uses Jetson Orin NX as the robot-side main controller, with industrial Ethernet and RS-485 supporting onboard device access, and Robot Operating System 2 (ROS 2) used for device coordination, data processing, and task scheduling. At the robot-cloud interaction level, Message Queuing Telemetry Transport (MQTT) is used for task delivery, status feedback, alarm reporting, and environmental data upload, while a real-time preview channel and sampled key-frame transmission support video monitoring and inspection-process retention. The proposed architecture organizes the control link and data link within an end-to-end closed loop and incorporates acknowledgment, buffering, reconnection, and abnormal-state handling mechanisms to improve communication availability under weak-network field conditions. Long-term field tests in a commercial caged broiler house demonstrated that the system could maintain reliable remote command execution, continuous status feedback, stable visual data transmission, and stable environmental telemetry upload during routine inspection tasks. The results indicate that the proposed communication architecture can provide practical support for remote inspection robots in smart poultry farming scenarios. Full article

Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as a revolutionary digital near-net-shape manufacturing technology, offering innovative solutions for the design and fabrication of complex, high-performance structures and equipment. This paper reviews the recent advancements and applications of metal AM technologies in the marine sector. Firstly, the principles and characteristics of three most widely adopted metal AM processes in this field are introduced: laser powder bed fusion (L-PBF), directed energy deposition (DED), and wire arc additive manufacturing (WAAM). Subsequently, the application status of metal AM is summarized in four key marine sectors: propulsion systems, underwater vehicle housings and structures, hull structures and shipboard equipment and components, as well as marine equipment repair and emergency support. Building on this, the major challenges for metal AM applications in the marine environment are further discussed, including the fabrication of large-scale components, standardization of materials and processes, integration of smart manufacturing and digital technologies, and sustainability and circular manufacturing. Finally, future trends are projected toward higher efficiency, intelligence, and environmental sustainability. It is indicated that metal AM will fundamentally reshape the manufacturing mode of marine equipment and support its high-performance, low-cost, intelligent and rapid-response development. Full article

The urban housing sector plays a significant role in global energy consumption and carbon emissions, making the sustainable transformation of domestic buildings essential to achieving climate goals. Urban housing is also linked to the energy transition, social equity, public health, and environmental resilience. The UK’s Warm Homes Plan (WHP) is seen as a key policy initiative that aims to improve energy efficiency and living conditions, and to promote the transition to a low-carbon future. This study provides an integrated review of retrofit assessment, policy mechanisms, and socio-environmental factors in the context of urban housing decarbonization. This study adopts a structured critical review approach to analyze retrofit strategies, low-carbon heating systems, renewable energy integration, and smart control technologies. The study highlights that retrofit assessment is not limited to technical performance but also includes social acceptability, affordability, and urban infrastructure compatibility. Furthermore, case study comparisons show that decarbonization outcomes are improved when technical measures are integrated with effective governance, stakeholder engagement, and local policy support. This study presents an integrated conceptual framework that links technical retrofit measures, policy coordination, and socio-environmental indicators. The results show that isolated technical solutions are insufficient for decarbonizing urban housing. Rather, a multi-dimensional planning approach is necessary to enable a sustainable, resilient, and socially inclusive housing transition. Full article

Smart city governance increasingly relies on AI-enabled planning systems, digital twins, vulnerability scoring tools, and capital investment platforms to allocate climate-resilient housing and infrastructure investments. Yet existing smart-urbanism and adaptation frameworks do not adequately specify how such systems should encode well-being, equity, and climate uncertainty when translating urban data into ranked projects and funded portfolios. This paper develops the Caring Urban Governance Framework for AI-enabled urban prioritization through a structured scoping review and conceptual framework analysis integrating climate-risk decision-making under deep uncertainty, built-environment pathways affecting psychosocial well-being, and public-sector algorithmic accountability. The framework proposes a five-layer architecture linking urban form and infrastructure, climate exposure and environmental resources, psychosocial mediators of well-being, algorithmic design choices, and institutional governance, with explicit feedback loops. Its main outputs are an auditable decision architecture, eight mechanism-based propositions for empirical testing, an operational specification matrix for objective functions, equity constraints, robust logic, and documentation, and an analytical validation of construct clarity, coherence, literature congruence, and operationalizability. The analysis argues that aligning AI-enabled urban prioritization with SDG 11 requires treating well-being-supportive living conditions as a decision objective, constraining optimization with equity conditions, and institutionalizing auditability and contestability to reduce distributive and psychosocial harm in public investment planning. Full article

Constructing age-friendly residential environments is essential for supporting aging in place among the growing population of urban empty-nest older adults in China. Grounded in person–environment fit theory, this study developed and validated a multidimensional Aging-Suitability Index (ASI) to examine how residential environmental factors shape housing suitability and perceived independence. In this study, “aging suitability” refers to the degree of fit between residential environments and older adults’ needs for safety, functionality, accessibility, social support, and technological support, with the central aim of enabling aging in place and independent living. Questionnaire data were collected from 753 urban empty-nest older adults across 19 provinces in China and analyzed using partial least squares structural equation modeling (PLS-SEM). The structural model showed strong explanatory power (R² = 0.754). The results revealed a clear hierarchy of environmental influences. Safety facilities and physical design were the strongest direct predictors of residential aging suitability, indicating that risk reduction and ergonomically appropriate spatial design constitute the foundation of age-friendly housing. Although accessibility showed a smaller direct effect, it exerted a significant indirect effect through perceived independence, with 67.35% of its total effect mediated through this pathway, highlighting the importance of barrier-free design in maintaining autonomy. Social support and smart technology also contributed positively as complementary resources that strengthened person–environment fit. These findings suggest that age-friendly housing interventions should move beyond fragmented modifications toward integrated residential renewal strategies that prioritize safety and physical design, improve accessibility to support independent living, and combine community support with age-friendly technologies. This study provides empirical evidence to inform built-environment decision-making in the design and renewal of housing for older adults in rapidly aging urban contexts. Full article

The transition toward sustainable facility management requires cleaning systems that reduce environmental burdens while maintaining high hygienic standards. This study presents a comparative evaluation of a green cleaning protocol (EVA SmartClean), compliant with the Italian Minimum Environmental Criteria (CAM; D.M. 29 January 2021), compared with a conventional cleaning system implemented in a civil facility (Adriatico Guest House, Trieste, Italy; 8260 m²). The assessment integrates a cradle-to-grave Life Cycle Assessment (LCA), conducted in accordance with ISO 14040, ISO 14044, ISO 14067 and PCR 2011:03 for professional cleaning services, with an extensive microbiological surface monitoring campaign performed using RODAC plates and swab sampling. The functional unit was defined as 1 m² of representative surface maintained clean for one year. The green protocol achieved a 47.7% reduction in Global Warming Potential (GWP100 based on IPCC AR6 characterization factors), corresponding to −110 g CO₂e/m²·year and −908 kg CO₂e/year for the entire facility. Major reductions in climate impact were associated with chemical consumption (−82.6%), energy use (−49.5%), and textile waste generation (−92.4%). Microbiological analyses demonstrated that both protocols complied with reference hygiene thresholds, while the green system achieved reductions in total mesophilic counts that were comparable or superior across representative surfaces. The results confirm that environmental optimization in cleaning services can be achieved without compromising microbiological safety, supporting public procurement policies aligned with CAM requirements and Sustainable Development Goals (SDGs 12 and 13). Full article

Population aging intensifies the need for built environments that support healthy and independent living while reducing preventable risks. This integrative review examines how architectural design, safety measures, and corporate security can function as an integrated, layered system for creating age-friendly environments across public spaces, housing, and intergenerational community settings. Drawing on a systematic search of literature published between 2010 and 2026 across databases including Scopus, Web of Science, Google Scholar, and PubMed, supplemented by international standards and policy documents, the review analyses how universal design principles, injury prevention strategies, and governance routines intersect to sustain mobility, reduce harms, and protect data, devices, and operational continuity. The findings indicate that gaps in any layer, such as inaccessible layouts, poorly maintained safety systems, or weak cybersecurity, can undermine overall effectiveness, compromise trust, and affect older adults’ autonomy. The COVID-19 pandemic further exposed these interdependencies, accelerating smart technology adoption while exacerbating digital inequality and social isolation, particularly in rural settings. This review concludes that age-friendly environments require not only barrier-free architecture and proportionate safety measures, but also robust governance structures that ensure accountability, lifecycle maintenance, and responsible data practices. Integrating these three domains provides a foundation for resilient, trustworthy, and health-promoting environments that enable older adults to remain active, socially connected, and secure. Full article

IoT-based smart greenhouse sensing, real-time signal conditioning and abnormality detection are still predominantly executed at gateway or cloud levels, limiting responsiveness and increasing vulnerability to noise-induced false alarms. This study proposes and experimentally validates a mobile-edge signal processing and abnormality detection framework executed entirely within an Android-based smartphone application, eliminating dependence on continuous cloud-side analytics. Environmental data from 27 wireless sensor nodes measuring temperature, relative humidity, CO₂ concentration, and light intensity were processed in real time using a sliding-window moving-average filter (N = 6) implemented with O(1) computational complexity. Abnormal conditions were determined via thresholding combined with temporal majority voting validation to suppress transient violations. Performance was also evaluated with direct threshold-based detection on raw signals to assess the effect of mobile-side filtering and temporal majority validation on abnormal sample counts, event fragmentation, and detection consistency. Mobile application side signal conditioning reduced short-term variance by 35–55% while maintaining an effective delay below two sampling intervals. Event-level analysis demonstrated substantial consolidation of noise-induced detections, reducing abnormal event frequency by up to 69% and increasing median event duration from 5 to 38 min for temperature, with negligible detection bias (±1.1%). End-to-end processing latency remained bounded under sustained multi-node streaming, with median delays of 1.0–1.6 s and 95th-percentile delays below 4.0 s. These results demonstrate that lightweight mobile-edge signal conditioning can significantly enhance detection robust-ness, reduce false alarms, and achieve low-latency environmental monitoring in green-houses. The proposed framework provides scalable and computationally efficient architecture for real-time abnormality detection in precision agriculture systems. Full article

Global poultry production continues to expand rapidly to meet the growing demand for affordable and high-quality animal protein. However, this growth raises pressing concerns about environmental sustainability, natural resource use, and public health. Although current initiatives, such as improved housing systems, optimized feeding practices, and partial soybean meal substitution, have helped mitigate some impacts, comprehensive integrated solutions remain underexplored. This review synthesizes emerging nutritional and management innovations that enhance the sustainability of poultry production while maintaining profitability. It addresses three central research questions: (1) Which alternative feed ingredients most effectively preserve animal performance while minimizing environmental burdens? (2) How can environmental management practices enhance resource efficiency and waste valorization? (3) What roles do life cycle assessment methodologies and policy frameworks play in advancing sustainable poultry systems? Evidence from 100 peer-reviewed studies, industrial data, and field analyses reveals that incorporating insect meals, algae, and agro-industrial by-products can reduce dependence on soybean meal by 20–40% and improve feed efficiency by 5–12% across various poultry production systems. Furthermore, integrating environmental management strategies, such as manure valorization, efficient water and energy use, and the adoption of renewable energy, substantially reduces greenhouse gas emissions and promotes circular economic principles. Life cycle assessment studies confirm that combined dietary and management interventions yield greater reductions in carbon footprint than isolated measures. Future research should focus on optimizing interactions among feed strategies, environmental management, and policy frameworks through digital technologies, nanomaterial-based feed additives, and region-specific sustainability plans to accelerate the transition toward resilient, climate-smart poultry production systems. Full article

Using transaction cost economics (TCE) and agency theory, this paper examines how blockchain, smart contracts, and decentralized autonomous organizations (DAOs) reconfigure financial services across payments, wealth management, real estate, and corporate governance. Three research questions are addressed: (1) What are the quantifiable efficiency gains from blockchain-based real-time settlement compared with legacy systems? (2) How do blockchain technologies reduce intermediation and agency costs in wealth management and real estate? (3) Finally, to what extent do DAOs resolve or transform traditional corporate governance problems? By combining a present-value model calibrated to U.S. Automated Clearing House (ACH) data ($86.2 trillion in annual volume), comparative institutional analysis, and synthesis of empirical evidence from pilot implementations and on-chain governance metrics, this paper makes three principal contributions. First, real-time settlement yields approximately $12 billion in annual opportunity cost savings at the baseline 7.5% discount rate, with sensitivity analysis producing a range of $8–15 billion. The majority of gains accrue from moving to same-day or within-hour settlement. Second, tokenization and smart contract escrow substantially reduce real estate intermediation costs, blockchain-based digital identity streamlines wealth management onboarding, and a stablecoin taxonomy classifies fiat-collateralized, crypto-collateralized, and algorithmic designs by risk profile. Third, on-chain data reveal persistent governance token concentration (Gini > 0.98) and low voter participation (typically below 10%), exposing a gap between DAO theory and practice. Blockchain-specific risks are mapped to National Institute of Standards and Technology (NIST) Cybersecurity Framework 2.0, and mechanism design solutions, such as quadratic voting and AI-assisted proposal evaluation, are proposed to address whale dominance. Effective adoption requires hybrid architecture combining on-chain automation with off-chain structures for accountability and regulatory compliance. Full article

Tornadoes pose growing threats to both communities and the built environment, yet few studies have quantified how spatial characteristics of the built environment interact with social and economic factors while influencing tornado impacts. This paper introduces an integrated metric that combines tornado risk and exposure to evaluate localized disaster impact. Focusing on Florida’s Panhandle, we examine how housing density and affordability, network connectivity, and urban form efficiency, together with demographic and socioeconomic attributes, shape tornado impacts at the U.S. census block group (CBG) level. To address spatial autocorrelation and non-stationarity, five statistical models were compared, including both global and local spatial regressions. The findings indicate that multiscale geographically weighted regression (MGWR) most effectively captures the spatial heterogeneity of tornado impacts. Built-environment and affordability factors show clear spatial heterogeneity— smart location indexand housing cost burden (h_ami) are positively associated with tornado impact in CBGs near Tallahassee and parts of Pensacola—suggesting amplified impacts in location-efficient urban areas where exposure is concentrated and affordability stress may limit preparedness and recovery. In contrast, network density is negatively associated with the impact of key clusters, consistent with the idea that denser, more redundant road networks can reduce canopy-weighted disruption by providing alternative routes for emergency access and restoration. Overall, these findings can inform our understanding of how the built environment influences tornado exposure, offering critical insights for planners and policymakers seeking to strengthen communities against tornadoes. Full article

Smart home technologies are increasingly integrated into residential environments jointly inhabited by older adults and young children. However, existing research remains largely ageing-centered and insufficiently addresses the governance challenges arising from generational asymmetries in vulnerability, spatial agency, and authority within shared domestic space. Rather than merely complicating design, these asymmetries fundamentally reshape how safety, autonomy, access, and surveillance are structured in everyday residential practice. This study reconceptualizes senior–child intergenerational co-living as a governance-oriented socio-technical system in which generational asymmetry functions as a structuring principle of design prioritization. An expert-based decision framework integrating interdisciplinary focus groups and the Analytic Hierarchy Process was developed to evaluate five design dimensions and thirty indicators. The findings reveal a differentiated priority structure in which intelligent safety, accessibility, and risk governance together with spatial integration and technological accessibility constitute the foundational architecture of inclusive intergenerational housing, while interaction-oriented functions receive comparatively lower weights. By embedding generational asymmetry within a formal hierarchical evaluation model, this study extends smart housing scholarship beyond ageing-centered optimization and provides a structured decision-support logic for inclusive multi-generational residential design aligned with the objectives of the United Nations Sustainable Development Goals (SDGs), particularly those promoting inclusive communities and health equity. Full article

Timely and accurate detection of sow oestrus is crucial for enhancing reproductive efficiency and reducing non-productive days (NPDs) in large-scale pig farms. However, traditional manual observation is labour-intensive and subjective, while cloud-based deep learning solutions face challenges such as high latency and privacy risks when applied in intensive housing environments. This study developed an edge-intelligent monitoring system that integrates deep temporal modelling with sound source localisation technology. A three-stage hierarchical screening strategy was utilised to select and deploy a lightweight Stacked-LSTM model on the resource-constrained ESP32-S3 hardware platform. This model was trained and calibrated using a high-quality acoustic dataset validated against serum reproductive hormones, specifically follicle-stimulating hormone (FSH), luteinising hormone (LH), and progesterone ($P_4$). Experimental results demonstrate that the optimised model achieved a classification accuracy of 96.17%, with an inference latency of only 41 ms, thereby fully satisfying the stringent real-time monitoring requirements while maintaining a minimal memory footprint. Furthermore, the system integrates a localisation algorithm based on Generalised Cross-Correlation with Phase Transform (GCC-PHAT). Through spatial geometric modelling, the system successfully implements the functional mapping of vocalisation events to individual gestation stalls (Stall IDs). Laboratory pressure tests validated the robustness and low-cost deployment advantages of the “edge recognition–cloud synchronization” architecture, providing a reliable technical framework for the precision management of smart livestock farming. Full article