Search Results (1,065)

Infrared imaging technology demonstrates significant advantages in aviation safety monitoring due to its exceptional all-weather operational capability and anti-interference characteristics, particularly in scenarios requiring real-time detection of aerial objects such as airport airspace management. However, traditional infrared target detection algorithms face critical challenges in complex sky backgrounds, including low signal-to-noise ratio (SNR), small target dimensions, and strong background clutter, leading to insufficient detection accuracy and reliability. To address these issues, this paper proposes the AFK-YOLO model based on the YOLO11 framework: it integrates an ADown downsampling module, which utilizes a dual-branch strategy combining average pooling and max pooling to effectively minimize feature information loss during spatial resolution reduction; introduces the KernelWarehouse dynamic convolution approach, which adopts kernel partitioning and a contrastive attention-based cross-layer shared kernel repository to address the challenge of linear parameter growth in conventional dynamic convolution methods; and establishes a feature decoupling pyramid network (FDPN) that replaces static feature pyramids with a dynamic multi-scale fusion architecture, utilizing parallel multi-granularity convolutions and an EMA attention mechanism to achieve adaptive feature enhancement. Experiments demonstrate that the AFK-YOLO model achieves 78.6% mAP on a self-constructed aerial infrared dataset—a 2.4 percentage point improvement over the baseline YOLO11—while meeting real-time requirements for aviation safety monitoring (416.7 FPS), reducing parameters by 6.9%, and compressing weight size by 21.8%. The results demonstrate the effectiveness of dynamic optimization methods in improving the accuracy and robustness of infrared target detection under complex aerial environments, thereby providing reliable technical support for the prevention of mid-air collisions. Full article

This study tries to make some improvements in the order picking operations by offering a novel mathematical model and efficient solution algorithm. Accordingly, the order picking policies are examined to allow for picking more orders by reducing the collection time/distance of order pickers. Batching orders for the pick are included in the order picking process as it could enable the order picker to collect more orders. Since the most labor-intensive movement in the order picking function in a high-level shelf layout is the retrieval of products from upper shelves and placing them onto the collection vehicle in the picker-to-part system, the use of drones is preferred to eliminate this costly movement. Drones assist humans in the order picking process by retrieving products from upper levels, thus reducing the order picking time. Here, a Vehicle Routing Problem (VRP) is formulated to deal with drone routing which is then solved based on the Order Picking Problem (OPP) framework. Consequently, an integrated OPP involving both order pickers and drones is addressed and formulated using a Mixed-Integer Linear Programming (MILP) model. To cope with the complexity of the problem, an Adaptive Genetic Algorithm (AGA) is designed which is able to yield superior results compared to the classical Genetic Algorithm (GA). Finally, a sensitivity analysis is performed to assess the behavior of the model against real-world fluctuations. The main reason for this research is to speed up the order picking process in warehouses by taking advantage of the tools brought by the technology age. According to the research results, when the results of the drone-assisted order picking process are compared to the order picking process without drone support, an improvement of 29.68% is observed. The theoretical contribution of this work is that it initially mathematically defines the drone-aided OPP in the literature and proposes a solution with the help of the AGA. As a practical contribution, it provides a solution with the capacity to reduce operational costs by accelerating the order picking operation in warehouses and a practical optimization framework for logistics managers. In addition, warehouse managers, senior company managers, and researchers working on order picking processes can benefit from this study. Full article

Motivation: Life Cycle Assessment (LCA) is a valuable tool for quantifying environmental impacts in construction. However, inconsistencies between software outputs may compromise effective decision-making. Knowledge Gap: In New Zealand’s construction sector, practitioners have limited guidance in selecting suitable LCA tools due to gaps in software scope, data transparency, and the quality of result interpretation. Aim and Objectives: This study investigates inconsistencies in results produced by eight widely used LCA software tools and identifies the key factors contributing to these variations. Research Method: This study uses a comparative analysis with data from a timber-framed warehouse project in Auckland, New Zealand. Eight software tools (SimaPro V9.0, openLCA V2.0, LCAQuick V3.5, Building Carbon Calculator V1.0, CCaLC2 V3.1, eTool V5.0, One Click LCA, and Athena Impact Estimator for Buildings V5.4) were evaluated across 14 environmental impact categories using standardised inputs. Preliminary Findings: Substantial inconsistencies were observed even with standardised inputs, although SimaPro V9.0 and openLCA V2.0 provided the most consistent results. These findings highlight the importance of software selection for reliable environmental assessments. Research Significance: This study aids industry practitioners in selecting effective LCA tools for sustainable construction practices. Full article

Efficient navigation of Automated Guided Vehicles (AGVs) in dynamic warehouse environments requires real-time and accurate path segmentation algorithms. However, traditional semantic segmentation models suffer from excessive parameters and high computational costs, limiting their deployment on resource-constrained embedded platforms. A lightweight image segmentation algorithm is proposed, built on an improved ESPNet-C architecture, combining Spatial Group-wise Enhance (SGE) and Efficient Channel Attention (ECA) with a dual-branch upsampling decoder. On our custom warehouse dataset, the model attains 90.5% Miou with 0.425 M parameters and runs at ~160 FPS, reducing parameters by ×116–×136 and computational costs by 70–92% in comparison with DeepLabV3+. The proposed model improves boundary coherence by 22% under uneven lighting and achieves 90.2% Miou on the public BDD100K benchmark, demonstrating strong generalization beyond warehouse data. These results highlight its suitability as a real-time visual perception module for AGV navigation in resource-constrained environments and offer practical guidance for designing lightweight semantic segmentation models for embedded applications. Full article

Millet (Pennisetum glaucum (L.) R. Br.) is the most widely consumed cereal in Niger. Although its production lasts six months, consumption is year-round, requiring effective and safe storage solutions. Post-harvest losses of millet can reach up to 17% after several months of storage. Chemical pesticides are commonly used in large warehouses, but concerns over misuse and health risks have driven interest in safer alternatives. This study assessed the effectiveness of traditional and improved storage methods in controlling Trogoderma granarium Everts, an emerging pest of millet in large warehouse facilities. Three storage methods were tested: (i) a hermetic Purdue Improved Crop Storage (PICS) bag; (ii) chemical pesticide Phostoxin; and (iii) an untreated ordinary polypropylene bag as a control. Naturally infested millet obtained from a large warehouse was assessed for each treatment at the start and end of a six-month storage period. Two insect pests were identified, T. granarium and Tribolium sp. Initial infestation levels were 60 larvae and 0.47 adults per 500 g. After six months, the control showed a 1.7-fold increase in T. granarium larvae, a 2.96-fold increase in its adults, and a 3.19-fold increase in Tribolium sp. adults, resulting in 19.15% weight loss. In contrast, PICS and Phostoxin treatments maintained initial pest levels with no weight loss. These results suggest that hermetic storage is a safe, effective, and chemical-free alternative for preserving millet in large warehouses. Full article

Background: Industry 4.0 (I4.0) has gained significant attention in recent years, with the term Logistics 4.0 (L4.0) emerging in the logistics industry. However, L4.0 remains vague and lacks a unified definition or classification of related technologies. Existing studies defining L4.0 are mainly conceptual and speculative, rather than grounded in empirical research. To address this gap, this study contributes to defining L4.0 through the sub-area of Warehouse 4.0 (W4.0), focusing on the challenges of adopting I4.0 technologies in warehouses. Methods: Through the I4.0 and L4.0 literature, an initial classification of W4.0 technologies in third-party logistics (3PL) was developed. This was refined using a case study of a global logistics service provider (LSP) in the 3PL industry, through semi-structured interviews with stakeholders. Results: The empirical findings identify new application areas for I4.0 technology in 3PL warehouses, including horizontal and vertical system integration, big data, and cybersecurity, technologies that can enhance 3PL competitiveness. Conclusions: This study offers a structured classification of W4.0 technologies and insights into the application areas of W4.0 in 3PLs. It contributes practical insights into which I4.0 technologies are relevant for the 3PL warehouse industry and their potential application areas. Full article

Chazence is a subsidiary of Zence Object Technology Company in the Greater Bay Area of China. It is a sustainable enterprise that combines tea industry consumables (tea residue) with fiber composite technology to replace traditional materials and conduct product practices. Their core philosophy aligns with the United Nations’ Sustainable Development Goals (SDGs), particularly Goals 9 and 12, emphasizing industrial innovation, the sustainable management of natural resources, and the promotion of sustainable consumption and production patterns. However, the current system of tea recycling is extensive and requires precise data management and back-end human resource allocation to ensure efficient collaboration between professionals and grassroots staff. Currently, the system does not have a user-friendly interface for human resource allocation, data management, resource management, and visual information. Therefore, we optimized the interface and functional design of the warehouse system to improve the efficiency of resource management of Chazence by understanding its approach to tea recycling. Through surveys and interviews, employee needs and user experiences were analyzed, and the results guide the design of a sustainable enterprise management system from a user experience (UX) perspective. Full article

Background: This paper provides the first national analysis of antimicrobial use (AMU) of oral and parenteral dosages in Bangladesh, as well as biannual trends for the years from 2019 to 2023. It also analyzes the effect of the COVID-19 pandemic on AMU. Methods: AMU was analyzed in accordance with the WHO Anatomical Therapeutic Chemical classification and defined daily doses per 1000 inhabitants per day methodology. Data on antimicrobial medicine dispatched from manufacturers’ central warehouse was collected and categorized based on the WHO’s Access, Watch, and Reserve (AWaRe) classification. Findings: This AMU surveillance demonstrates an increase in the use of antimicrobial medicines from 2021 to 2022, and in 2023, it decreased, with our national AMU surveillance data indicating that cefixime and azithromycin were the most consumed antibiotics during this period. Most antibiotics used in Bangladesh are broad-spectrum ‘Watch’-category antibiotics. Among oral antibiotics, 50 to 67% are from the ‘Watch’-category. When considering only parenteral antibiotics, 70 to 91 % fall under the ‘Watch’-category. Third-generation cephalosporin consumption has been found to be higher than second- and first-generation cephalosporins. The oral antimicrobials are more commonly used than parenteral ones. AMU notably increased during the COVID-19 pandemic, especially in the case of systemic antibacterial use. Conclusions: To achieve the global target of 70% use of Access category antibiotics by 2030, the use of Watch-group antibiotics, like cefixime, azithromycin, ciprofloxacin, levofloxacin, and ceftibuten, needs to be reduced through investing in and strengthening stewardship programs and eliminating self-medication in Bangladesh. The findings of this study provide useful information to policymakers to tackle AMR in Bangladesh. Full article

With the upgrading of consumption driving the transformation of the home furnishing industry towards personalized customization, panel furniture enterprises are confronted with a core contradiction between large-scale production and individualized demands: The traditional production management model is unable to cope with the chaos in production scheduling, resource waste, and low collaborative efficiency caused by small-batch and multi-variety orders. This paper proposes an intelligent production scheduling system that integrates Enterprise Resource Planning (ERP), Manufacturing Execution System (MES), Advanced Planning and Scheduling (APS), and Warehouse Management System (WMS), and elaborates on its data processing methods and specific application processes in each production stage. Compared with the traditional model, it effectively overcomes limitations such as coarse-grained planning, delayed execution, and information islands in middle-level systems, achieving deep collaboration between planning, workshop execution, and warehouse logistics. Empirical studies show that this system not only can effectively reduce the production costs of customized panel furniture manufacturers, enhance their market competitiveness, but also provides a digital transformation framework for the entire customized panel furniture manufacturing industry, with significant theoretical and practical value. Full article

Robotic hands require reliable and precise sensing systems to achieve accurate object recognition and manipulation, particularly in environments where vision- or capacitive-based approaches face limitations such as poor lighting, dust, reflective surfaces, or non-metallic materials. This paper presents a novel radiofrequency (RF) pre-touch sensing system that enables robust localization and orientation estimation of objects prior to grasping. The system integrates a compact coplanar waveguide (CPW) probe with fully passive chipless RF resonator tags fabricated using a patented flexible and stretchable conductive ink through additive manufacturing. This approach provides a low-cost, durable, and highly adaptable solution that operates effectively across diverse object geometries and environmental conditions. The experimental results demonstrate that the proposed RF sensor maintains stable performance under varying distances, orientations, and inter-tag spacings, showing robustness where traditional methods may fail. By combining compact design, cost-effectiveness, and reliable near-field sensing independent of an object or lighting, this work establishes RF sensing as a practical and scalable alternative to optical and capacitive systems. The proposed method advances robotic perception by offering enhanced precision, resilience, and integration potential for industrial automation, warehouse handling, and collaborative robotics. Full article

Physical conditions in grain storage environments influence trophic interactions between predators and their prey and can affect the effectiveness of biocontrol agents. The study aimed to assess the potential of Xylocoris flavipes (Reuter) (Hemiptera: Anthocoridae), to manage Liposcelis decolor (Pearman) (Psocodea: Liposcelididae). Liposcelis decolor population suppression and X. flavipes progeny production were assessed at five predator–prey (P-P) ratios (0:240, 1:240, 2:240, 3:240, and 5:240), four temperatures (20, 24, 28, and 32 °C), and three relative humidities (RH) (63, 75, and 85%) over 40 days at 0:24 (L:D) photoperiod in the laboratory. Compared with the Control P-P ratio of 0:240 (no predators), prey suppression >97% was achieved across all predator release ratios. At 32 °C and 75% RH, which are the optimal conditions for L. decolor, 3985.13 ± 255.45 prey survived in the Control P-P ratio compared with 19.85 ± 2.47–115.73 ± 8.99 found for the four P-P ratios with the predator, representing prey reduction of 97.10–99.50%. Temperature influenced X. flavipes progeny production, which was greatest at 28 °C and a P-P ratio of 1:240. Suppression caused by X. flavipes demonstrates its potential as a biological control agent to manage psocid infestations in stored commodities. Full article

In the context of the rapid development of e-commerce, the selection of optimal land plots for the construction of warehouse complexes that meet environmental, technical, and political requirements has become increasingly relevant. This task requires a comprehensive approach that accounts for a wide range of factors, including transportation accessibility, environmental conditions, geographic features, legal constraints, and more. Such an approach enhances the efficiency and sustainability of decision-making processes. This article presents a solution to the aforementioned problem that employs the use of land suitability maps generated by aggregating multiple evaluation criteria. These criteria represent the degree to which each land plot satisfies the requirements of various stakeholders and are expressed as suitability functions based on attribute values. Attributes describe different characteristics of the land plots and are represented as layers on a digital terrain map. The criteria and their corresponding attributes are classified as either quantitative or binary. Binary criteria are aggregated using the minimum operator, which filters out plots that violate any constraints by assigning them a suitability score of zero. Quantitative criteria are aggregated using the second-order Choquet integral, a method that accounts for interdependencies among criteria while maintaining computational simplicity. The criteria were developed based on statistical and environmental data obtained from an analysis of the Samara region in Russia. The resulting suitability maps are visualized as gradient maps, where land plots are categorized according to their degree of suitability—from completely unsuitable to highly suitable. This visual representation facilitates intuitive interpretation and comparison of different location options. These maps serve as an effective tool for planners and stakeholders, providing comprehensive and objective insights into the potential of land plots while incorporating all relevant factors. The proposed approach supports spatial analysis and land use planning by integrating mathematical modeling with modern information technologies to address pressing challenges in sustainable development. Full article

Urban logistics face complexity due to traffic congestion, fleet heterogeneity, warehouse constraints, and driver workload balancing, especially in the Heterogeneous Multi-Trip Vehicle Routing Problem with Time Windows and Time-Varying Networks (HMTVRPTW-TVN). We develop a mixed-integer linear programming (MILP) model with dual-peak time discretization and exact linearization for heterogeneous fleet coordination. Given the NP-hard nature, we propose a Hyper-Heuristic based on Cumulative Reward Q-Learning (HHCRQL), integrating reinforcement learning with heuristic operators in a Markov Decision Process (MDP). The algorithm dynamically selects operators using a four-dimensional state space and a cumulative reward function combining timestep and fitness. Experiments show that, for small instances, HHCRQL achieves solutions within 3% of Gurobi’s optimum when customer nodes exceed 15, outperforming Large Neighborhood Search (LNS) and LNS with Simulated Annealing (LNSSA) with stable, shorter runtime. For large-scale instances, HHCRQL reduces gaps by up to 9.17% versus Iterated Local Search (ILS), 6.74% versus LNS, and 5.95% versus LNSSA, while maintaining relatively stable runtime. Real-world validation using Shanghai logistics data reduces waiting times by 35.36% and total transportation times by 24.68%, confirming HHCRQL’s effectiveness, robustness, and scalability. Full article

In the age of labor shortage, increasing the throughput of warehouses is a good issue. In the recent two decades, automatic warehouses designed to reduce human labor have therefore become a very hot research topic. Tricycle forklifts being able to carry heavy goods can play important roles in automatic warehouses. Meanwhile, Robot Operating System (ROS) is a very famous and popular platform for developing the software of robotics. Its powerful communication function makes lots of warehouse information exchange easy. Therefore, ROS installed as the communication backbone of warehouse is very popular. However, the software modules of ROS do not offer tricycle forklifts. Therefore, in this research, the model of a tricycle forklift developed for ROS systems in warehouse applications is constructed. In spite of the developed model, the existing software modules must be modified for compatible connection such that the tricycle forklift can be navigated and controlled by constructed ROS. For the function of Simultaneous Localization And Mapping (SLAM) and the control of self-guided navigation, the constructed system is verified by Gazebo simulation. In addition, the experiments of a real tricycle forklift to demonstrate the developed ROS for enough accuracy of warehouse application are also included. Full article

The storage conditions of multi-floor grain warehouses change frequently during grain circulation. This paper investigates the effects of various storage conditions on the seismic performance of multi-floor grain warehouses. The numerical results indicate that the higher the storage material distribution position, the greater the damping ratio of the structural model and the more obvious the contribution of storage material movement to the damping of the structure. The intensity of earthquake action and the spatial height of the floor where the storage material is located are negatively correlated with the acceleration response of the structure. Under full-silo conditions, when the peak ground acceleration (PGA) is 0.4 g, the acceleration amplification factor at the top of the structure is 69.7% of the corresponding parameter at 0.1 g. The discontinuity in the storage space of the structure results in a torsional effect on the structure. When PGA = 0.22 g, the peak inter-story displacement angle of the first floor differs by nearly 1.7 times under different operating conditions, and the peak inter-story displacement angle of the second floor during an earthquake with PGA = 0.40 g differs by about 1.5 times under different operating conditions. The lateral pressure of the silo wall at different burial depths under earthquake action shows a highly nonlinear distribution trend, and the overpressure coefficient at the same burial depth of the warehouse wall is proportional to the PGA of the earthquake action. During 0.1 g, 0.22 g, and 0.40 g earthquakes, the maximum overpressure coefficients at the bottom of the warehouse wall on different floors are 1.13, 1.21, and 1.66, respectively. Full article