Search Results (33)

This study presents an automated docking block placement system developed for regular and emergency repairs of large ships and naval vessels. Traditional methods involve manually arranging heavy concrete docking blocks using cranes or forklifts, which can take several days and pose significant safety risks because of the heavy materials involved. The proposed system integrates an unmanned crane with a six-degree-of-freedom (6-DOF) robotic platform and a mobile robot-based 3D precision positioning system to automate block relocation. The use of a 3D laser tracker mounted on the mobile robot is the key to the system, which, when combined with environmental sensors such as LiDAR and RTK-GPS, provides millimeter-level positional feedback. To address the lack of clear reference points in conventional docking blocks, a precisely machined aluminum target block was attached to each block. An algorithm employing Density-Based Spatial Clustering of Applications with Noise (DBSCAN), KD-Tree, and Random Sample Consensus (RANSAC) techniques was used to detect and classify the vertex of the target block from the 3D point cloud data. The experimental results demonstrated a positional measurement error within 0.5 mm at an 8 m distance. This novel system reduces the setup time, enhances worker safety, and increases the overall efficiency and capacity of dry dock maintenance operations. Full article

The growing adoption of off-site construction methods has increased the critical role of mobile cranes within the construction sector. This study develops a Construction Digital Twin (CDT) framework to optimize crane lifting positions and capacities for the installation of prefabricated bridge decks. By integrating 3D site modeling, Building Information Modeling (BIM), and crane simulations within the Unity game engine, the CDT overcomes the limitations of conventional 2D-based planning by providing a three-dimensional representation of site conditions. An exhaustive search method identifies optimal crane configurations, enhancing precision and efficiency. Simulation calibration using video analysis of real bridge deck installations aligns crane speed and cycle times with actual operations, improving reliability. Case studies demonstrate the CDT’s ability to reduce crane operation costs by 27% when employing a smaller capacity crane while maintaining operational efficiency. Additional DFA-focused simulations with varying deck dimensions revealed a potential 10% cost reduction by optimizing crane operations and deck design strategies. The CDT framework supports early-stage planning, reduces operational risks, and contributes to cost-effective and safer construction practices, offering a scalable solution adaptable to various construction scenarios. Full article

Crawler cranes are mobile lifting equipment used in the process of hoisting goods. After the initial lifting, the crane may need a secondary lift due to adjustments in the position or height of the load. Addressing the common issue of load slipping during the secondary lift caused by hydraulic motor reversal, this study proposes a control strategy applicable to crawler crane secondary lifting. Initially establishing the dynamic characteristics of the secondary lift system, incorporating a delay coefficient, and matching motor pressure build-up with memory pressure, the strategy considers a variable pump input current control to identify the relationship between motor pressure build-up and brake release. Analyzing the dynamic characteristics of secondary lifting under different conditions, this study resolves the issue of hydraulic motor reversal during the second lift caused by heavy loads. The results of this study on crawler crane secondary lifting indicate that, when using a delay coefficient of 0.70 and releasing the brake, no slip phenomenon occurred during the secondary lift process under different load conditions, categorized as 200 tons, 600 tons, and 1000 tons. This ensures the stability and transition quality of the secondary lift, providing theoretical guidance for the control of the crawler crane secondary lifting. Full article

Ensuring operational safety within high-risk environments, such as construction sites, is paramount, especially for tower crane operations where distractions can lead to severe accidents. Despite existing behavioral monitoring approaches, the task of identifying small yet hazardous objects like mobile phones and cigarettes in real time remains a significant challenge in ensuring operator compliance and site safety. Traditional object detection models often fall short in crane operator cabins due to complex lighting conditions, cluttered backgrounds, and the small physical scale of target objects. To address these challenges, we introduce YOLO-TC, a refined object detection model tailored specifically for tower crane monitoring applications. Built upon the robust YOLOv7 architecture, our model integrates a novel channel–spatial attention mechanism, ECA-CBAM, into the backbone network, enhancing feature extraction without an increase in parameter count. Additionally, we propose the HA-PANet architecture to achieve progressive feature fusion, addressing scale disparities and prioritizing small object detection while reducing noise from unrelated objects. To improve bounding box regression, the MPDIoU Loss function is employed, resulting in superior accuracy for small, critical objects in dense environments. The experimental results on both the PASCAL VOC benchmark and a custom dataset demonstrate that YOLO-TC outperforms baseline models, showcasing its robustness in identifying high-risk objects under challenging conditions. This model holds significant promise for enhancing automated safety monitoring, potentially reducing occupational hazards by providing a proactive, resilient solution for real-time risk detection in tower crane operations. Full article

Amid accelerating globalization and resource scarcity, rapid urbanization and population mobility have made sustainable development a critical issue for cities. Frequent relocations pose furniture disposal challenges for many young migrants, with high transportation costs and furniture wear increasing their economic burden and resource waste. Origami design effectively addresses these needs with its portability, easy storage, simplified manufacturing, and reduced failure rates. However, most furniture designers lack origami expertise, limiting their ability to leverage these benefits. This study integrates the existing literature and presents a sustainable furniture design method combining Rhinoceros 3D, Grasshopper, and Crane, enabling designers to incorporate origami principles with limited prior knowledge. The results show that this method not only enhances the economic feasibility of furniture but also balances user needs, commercial interests, and environmental sustainability, offering new insights for urban sustainable development. Full article

Mobile cranes are essential for transporting heavy materials at construction sites, but their operation carries significant safety risks, particularly due to the potential for overturning accidents. These accidents can be classified into two main categories: mechanical accidents, which are caused by factors such as outrigger failure, excessive load weight, and operator skill, and environmental accidents, which arise from ground subsidence due to groundwater and sinkholes. While numerous studies have addressed the causes and prevention of mechanical accidents, there has been a lack of research focusing on the prevention of environmental accidents. This study presents the development of an Electrical Resistivity Measurement System (ERMS) designed to prevent overturning accidents caused by ground subsidence at mobile crane work sites. The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. Unlike typical buried electrode methods, the proposed system features a foldable electrode mechanism and a water supply device, thereby making installation and removal more efficient. Furthermore, it uses a ground stability determination algorithm that qualitatively assesses soft ground conditions, which are the primary cause of ground subsidence. The performance of the ERMS was validated through comparisons with commercial equipment, and its applicability was further confirmed through field tests conducted at mobile crane installations. The ERMS is expected to significantly reduce the risk of accidents caused by ground subsidence during mobile crane operations and to contribute to enhancing overall safety in construction environments. Full article

Reducing the construction time for large logistics buildings can result in reduced construction management costs and economic gains from early operation. A large logistics building with a heavy load and long spans was constructed as a precast concrete (PC) structure, which required the use of a sizable crane to lift heavy PC members. A basic analytical approach was employed to resolve potential errors in the planning of PC member erection and to build a systematic erection plan. Calculation techniques for the trajectory distance that use the crane location were applied to select an erection plan that minimizes crane work. A crane trajectory distance calculation algorithm for sustainable PC member erection in large logistics buildings with heavy loads and long spans has been developed. The developed model aids in creating simulation and optimization models to ensure the minimal usage of cranes in the future and in determining the cost, construction time, CO₂ emissions, and energy use for each erection plan. Full article

Mobile cranes represent conventional construction machinery that is indispensable for the erection of most prefabricated buildings, especially those containing heavy components. However, it is also common knowledge that the engagement of these machines has a significant influence on the environment, various social aspects of the construction process, and its economic benefits. Optimal positioning of the mobile crane on the construction site, primarily driven by the contractor’s interest to perform assembly operations with expensive machinery as effectively as possible, considerably reduces not only the costs of engaging such a machine but indirectly also its negative impacts on construction sustainability. This paper discusses an exact nonlinear model for the optimization task. The optimization model consists of a cost objective function that is subject to various duration and positioning constraints for the mobile crane, including bounds on its degrees of freedom of movement and stop positions. Because the model formulation includes discontinuous and non-smooth expressions, nonlinear programming with discontinuous derivatives (DNLP) was employed to ensure the optimal solution was reached. The model provides the mobile crane operator with exact key information that enables the complete and optimal assembly of the building structure under consideration. Additionally, the information gained on the optimal distribution of the mobile crane rental period to assembly operations allows for a detailed duration analysis of the entire process of building structure erection, which can be used for its further improvement. An application example is given in this study to demonstrate the advantages of the proposed approach. Full article

The emerging advances in deep learning and computer vision have enabled traditional cloud-based decision-making through edge computing with artificial intelligent internet of things (AIoT) image sensors (AIoT-IS). As a result, the timeliness and security of image recognition can be obtained. This study aims to develop an AIoT-IS-based smart safety control device for construction sites (“SmartCon” hereafter) for the operations of mobile cranes. The research is carried out to include the definition of hazardous control areas and the identification of unsafe scenarios for crane operations, the development of an intelligent prototype system for the safety control of lifting operations, system application demonstrations, and the evaluation of effectiveness. It is intended to assist labor inspection agencies and industry practitioners with a tool for monitoring lifting operations. The results of two empirical field tests show that the proposed SmartCon improves the safety monitoring of the operation of the machine through the real-time response to the identified potential risks on construction sites. Full article

The rapid urbanization phenomenon has introduced multifaceted challenges across various domains, including housing, transportation, education, health, and the economy. This necessitates a significant transformation of seaport operations in order to optimize smart mobility and facilitate the evolution of intelligent cities. This conceptual paper presents a novel mathematical framework rooted in deep learning techniques. Our innovative model accurately identifies parking spaces and lanes in seaport environments based on crane positions, utilizing live Closed-Circuit Television (CCTV) camera data for real-time monitoring and efficient parking space allocation. Through a comprehensive literature review, we explore the advantages of merging artificial intelligence (AI) and computer vision (CV) technologies in parking facility management. Our framework focuses on enhancing container drayage efficiency within seaports, emphasizing improved traffic management, optimizing parking space allocation, and streamlining container movement. The insights from our study provide a foundation that could have potential implications for real-world applications. By integrating cutting-edge technologies, our proposed framework not only enhances the efficiency of seaport operations, but also lays the foundation for sustainable and intelligent seaport systems. It signifies a significant leap toward the realization of intelligent seaport operations, contributing profoundly to the advancement of urban logistics and transportation networks. Future research endeavors will concentrate on the practical implementation and validation of this pioneering mathematical framework in real-world seaport environments. Additionally, our work emphasizes the crucial need to explore further applications of AI and CV technologies in seaport logistics, adapting the framework to address the evolving urbanization and transportation challenges. These efforts will foster continuous advancements in the field, shaping the future of intelligent seaport operations. Full article

A sustainable future is required for precast concrete structures, and the reuse of concrete elements will be an essential part of the solution. Design for disassembly is currently conducted with costly and time-consuming mechanical joints. Now, mortar joints with much weaker mortar types are proposed for new buildings, enabling easier disassembly by new methods: removal by direct pulling and removal by use of a system of flat jacks. Different weak mortar types were tested in the lab to achieve the properties required to check the transfer of wind loads and the level of resistance to separation during disassembly. Using a modelled case study building, the results showed that weak lime cement-based mortars had the required properties to substitute regular cement-based mortar in joints between slabs and a stabilising wall during a critical wind load. Regarding disassembly, pulling concrete slabs out with a mobile crane would be possible if hydro demolition systems could be implemented to remove parts of the mortar joint beforehand. Using a system of flat jacks to push the slab apart showed that the method’s weakness was the punching failure of the thin wall to the hollow cores. Solutions were proposed to overcome the challenge. Full article

Laser scanning has revolutionized the ability to quantify single-tree morphologies and stand structural variables. In this study, we address the issue of occlusion when scanning a spruce (Picea abies (L.) H.Karst.) and beech (Fagus sylvatica L.) forest with a mobile laser scanner by making use of a unique study site setup. We scanned forest stands (1) from the ground only and (2) from the ground and from above by using a crane. We also examined the occlusion effect by scanning in the summer (leaf-on) and in the winter (leaf-off). Especially at the canopy level of the forest stands, occlusion was very pronounced, and we were able to quantify its impact in more detail. Occlusion was not as noticeable as expected for crown-related variables but, on average, resulted in smaller values for tree height in particular. Between the species, the total tree height underestimation for spruce was more pronounced than that for beech. At the stand level, significant information was lost in the canopy area when scanning from the ground alone. This information shortage is reflected in the relative point counts, the Clark–Evans index and the box dimension. Increasing the voxel size can compensate for this loss of information but comes with the trade-off of losing details in the point clouds. From our analysis, we conclude that the voxelization of point clouds prior to the extraction of stand or tree measurements with a voxel size of at least 20 cm is appropriate to reduce occlusion effects while still providing a high level of detail. Full article

Heavy mobile machinery cabs and their equipment are still not well adjusted to operators, so it is not surprising that we are still witnessing huge consequences of accidents at sites where they operate. The checklist with 39 questions, based on the previous research, is formed, and its’ measurement structure has been tested on the sample of 102 transport, construction, and mining machines, including cranes, excavators, bucket wheel excavators, bulldozers, loaders, graders, backhoe loaders, trenchers, dump trucks, and scrapers by correlation analysis, Cronbach’s alpha, Spearman-Brown and Kendall’s W coefficient, exploratory factor analysis, and confirmatory factor analysis. The results validate the measurement structure of a checklist with only 17 items and five constructs. The results show that special attention should be put to the design of armrests and working conditions/exhaust gases, which are negatively correlated to cab interior space and task visibility. All other correlations between seat characteristics, the characteristics of armrests, whole-body vibration influences, reaching commands, the characteristics of cab interior space and environments, and interpersonal relationships are positive, which means that improvements to one area lead to improvements in another. Accordingly, the proposed model should be used for the fast, efficient, and cost-effective evaluation of ergonomics risks and as a guideline for further cab design improvements. Full article

In this work, the authors analyse the influence of the order and range of sequential movements of a crane’s working members on the accuracy of the final cargo positioning. The analysis was conducted on the basis of a specially developed method in which the authors proposed the introduction of a geometrical indicator of positioning the load in the intermediate positions (after completing each movement sequence) and in the target position, depending on the adopted control strategy and the accuracy of kinematic input of the working mechanisms (powered mechanisms). A mathematical model was presented to enable the accuracy of unidirectional positioning of the crane’s working members when conducting sequential movements controlled through the rotation of the crane column, inner and outer boom, and retractable stages of the six-section telescopic boom. Sample results of the numerical simulations showing the influence of the assumed kinematic inputs of the crane members on the accuracy of unidirectional angular and linear positioning and, consequently, on the accuracy of the final positioning of the transported cargo, were presented. Moreover, an indicator of the cargo positioning accuracy dependent on the location of an operator or a video camera and the trajectory of the cargo was developed, allowing the formulation of application conclusions. Full article

Drones, as mobile media of the present day, increase the operational and narrative capabilities of television and accelerate the logistics of shooting. Unmanned aerial vehicles with a camera properly steered by a pilot are able, to some extent, to replace a jimmy jib/crane and a dolly; basic technical devices, used in the studios, enabling the creation of narrative systems of pictures in film and television. Television is more and more often using drone footage to report events, broadcast live, as well as create coverage and television documentaries. In many productions, the pilot of the drone simultaneously acts as the drone camera operator, which can improve the effectiveness of shooting, but also carries some risks related to flight safety. The article describes and presents in the form of processed footage the real conditional ties of a Visual Line of Sight (VLOS) flight faced by pilots filming with a drone. VLOS is a type of air operation, which requires maintaining eye contact with the drone. In many countries, a drone visibility flight is legally sanctioned as VLOS Operation. An experiment was conducted to investigate the interactions between a human and a machine in airspace steered using a controller with a touchscreen. The drone pilot was considered an integral part of the drone’s flight system control Experimental data was collected with the use of a mobile eye-tracker, video cameras, surveys, and pilot declarations. During the experiment, eight television drone pilot operators recaptured a model shot under the regime of VLOS flight at low altitudes. They all show that both advanced and beginner pilots did not look at the UAV for over half the time of shot execution. The experiment allowed establishing two coefficients related to the effectiveness of a VLOS flight aiming at filming from the drone. The results point to clear differences in screen perception styles used by drone television pilots. The coefficients were described in the form of mathematical formulas and their limit values were determined. The research also determines the limits of pilots’ perception, within which they can film with a drone. The outcomes may help to optimize the process of aerial filming with the use of a drone, carried out for television, film, and other media, as well as in a simulation of such a flight for research and training. From the perspective of media science and social communication, the presented study included a technological component that can be accessed through information science, using statistical models and variable distributions. Media scholars can study the impact of the media without having to look into the metaphorical black box. Computer science opens up this possibility. Full article