Search Results (69)

Lighting systems in sports venues have a significant impact on both the user experience and quality of events. However, owing to the large number of luminaires, high individual lamp power, and strict lighting standards, the lighting energy consumption of sports venues is high, accounting for approximately 30% of the total energy use. Therefore, introducing natural light through appropriate means during non-event periods and ensuring adequate lighting via collaborative control between natural light and artificial-lighting systems are crucial for reducing the lighting energy consumption of sports venues. Light pipe systems are a novel form of natural lighting and can effectively supplement artificial lighting. However, no clear methodology for selecting light pipes or designing light pipe systems in high spaces such as sports venues currently exists. Furthermore, developing a method for collaborative control between artificial-lighting systems and light pipe systems under various natural light conditions is an urgent issue in the optimization of the design of sports venue lighting. Therefore, we considered a conventional sports venue as a case study. By conducting HOLIGILM simulation experiments, we first investigated the factors affecting the transmission efficiency of light pipe systems and proposed optimization parameters for system design in terms of the pipe diameter, length, and configuration. Subsequently, using the Chinese Standard for Daylighting Design of Buildings (GB50033-2013) and the construction cost as optimization objectives, we optimized the pipe diameter, length, and placement of the light pipe system by applying non-dominated sorting genetic algorithm II. The simulation results showed that the optimized design of the light pipe system in the sports venue achieved a daylight factor of 1%, which met the standard requirements while reducing the construction cost by approximately 27%. Finally, to meet the indoor Class I (non-tournament) lighting standards stipulated in the Standard for Lighting Design and Test of Sports Venues (JGJ153-2016) and taking energy conservation as the optimization goal, we proposed a strategy for achieving collaborative control between the light pipe system and artificial-lighting system based on a greedy algorithm. The results indicated that under various weather conditions, the collaborative control strategy enabled the lighting of the field of play to meet Class I illuminance standards while reducing the annual lighting energy consumption by 35%. Thus, this study provides a methodological reference for optimizing the design of light pipe systems and achieving collaborative control with artificial-lighting systems in large-scale venues. Although these results were obtained based on meteorological data from Xi’an, China, the research method presented in this study can also be applied to other regions. The study provides a methodological reference for the design and optimization of light pipe systems and associated control systems to operate light pipes alongside artificial lighting systems in sports venues and other large multistory buildings. Full article

This study adopts numerical simulation methods to explore the acoustic transmission characteristics of pipe strings in the upper and lower completions of a monitoring system for test production of natural gas hydrate. A finite-element simulation model for acoustic transmission in the pipe string system is established through COMSOL. The sound pressure level attenuation and the sound pressure amplitude ratio are chosen as evaluation indexes. Parametric numerical simulations are carried out to study the effects of the number of tubing cascades and the size of connection joints in the pipe string system on the acoustic transmission characteristics of the pipe string. The Light Gradient Boosting Machine (LightGBM) algorithm is adopted to predict the acoustic transmission characteristic curves of the pipe string. Based on this prediction model, with the maximum transmission distance, maximum sound pressure amplitude ratio, and minimum transmission attenuation as objective functions, the NSGA-II (Non-dominated Sorting Genetic Algorithm-II) optimization algorithm is adopted to obtain the optimal combinations of the pipe string system structure and the transmission frequency. The findings show that within the range of 20–2000 Hz, when the acoustic wave propagates in the column system, the amplitude attenuation caused by structural damping is positively correlated with the transmission distance, and the high-frequency acoustic wave attenuates faster. When the frequency exceeds 500 Hz, the sound pressure amplitude ratio is lower than 0.4, and the attenuation is stabilized at 90% above 1500 Hz. The thickness of the joints has a weak impact on the transmission, while an increase in length raises the characteristic frequency but exacerbates sound pressure attenuation. The LightGBM algorithm has a high prediction accuracy, reaching up to 88.54% and 84.82%, respectively. The optimal parameter combinations (n, hkg, lkg, freq) optimized by NSGA-II provide an optimization scheme for the structure and frequency of acoustic transmission in down-hole pipe strings. Full article

Manual assembly remains essential in modern manufacturing, yet the increasing complexity of customised production imposes significant cognitive burdens and error rates on workers. Existing Spatial Augmented Reality (SAR) systems often operate passively, lacking adaptive interaction, real-time feedback and a control system with gesture. In response, we present Gest-SAR, a SAR framework that integrates a custom MediaPipe-based gesture classification model to deliver adaptive light-guided pick-to-place assembly instructions and real-time error feedback within a closed-loop interaction instance. In a within-subject study, ten participants completed standardised Duplo-based assembly tasks using Gest-SAR, paper-based manuals, and tablet-based instructions; performance was evaluated via assembly cycle time, selection and placement error rates, cognitive workload assessed by NASA-TLX, and usability test by post-experimental questionnaires. Quantitative results demonstrate that Gest-SAR significantly reduces cycle times with an average of 3.95 min compared to Paper (Mean = 7.89 min, p < 0.01) and Tablet (Mean = 6.99 min, p < 0.01). It also achieved 7 times less average error rates while lowering perceived cognitive workload (p < 0.05 for mental demand) compared to conventional modalities. In total, 90% of the users agreed to prefer SAR over paper and tablet modalities. These outcomes indicate that natural hand-gesture interaction coupled with real-time visual feedback enhances both the efficiency and accuracy of manual assembly. By embedding AI-driven gesture recognition and AR projection into a human-centric assistance system, Gest-SAR advances the collaborative interplay between humans and machines, aligning with Industry 5.0 objectives of resilient, sustainable, and intelligent manufacturing. Full article

As a special component, inner-wall-shaped parts with a narrow aperture and large cavity play an important role in the field of industrial manufacturing. It is of great significance to accurately measure the full profile of the inner surface of such parts. Line-structured light scanning is a widely used method for inner wall 3D measurement, which is usually applied to linear scanning measurements of the inner wall of pipe-shaped parts. In view of the structural characteristics of narrow-aperture and large-cavity parts, this article establishes a multi-sensor scanning measurement system based on the principle of line-structured light, which adopts rotary scanning instead of the traditional linear scanning measurement method in the system. Additionally, a calibration method is introduced to resolve the challenges associated with the calibration of rotation axis parameters. Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. In order to minimize the size of the sensor, the adjacent sub-sensors in the system are arranged in the form of low overlapping fields of view (FOV). To solve the problem of multi-sensor registration under low overlapping FOV, a calibration method based on the structural characteristics of the measurement system itself is proposed, which realizes low-cost and high-precision calibration of the multi-sensor system. Through the repeatability measurement experiment of the spherical cavity parts, the average measurement deviation of the spherical cavity radius was measured to be 6 μm, and the standard deviation was 11.4 μm, which verified the feasibility of the measurement system proposed in this article. By comparing the system calibration method proposed in this article with existing methods, the measurement accuracy of the system is improved by approximately 80%, demonstrating the effectiveness of the proposed method. Full article

Hybrid photovoltaic (PV) and thermoelectric generator (TEG) systems combine heat and light energy harvesting in a single module by utilizing the entire solar spectrum. This work analyzed the feasibility and performance of a hybrid photovoltaic–thermoelectric generator system with efficient thermal management by integrating heat pipe (HP), radiative cooling (RC), and heat sink (HS) systems. The proposed system effectively reduces the PV operation temperature by evacuating the residual heat used in the TEG system to generate an additional amount of electricity. The remaining heat is evacuated from the TEG’s cold side to the atmosphere using RC and HS systems. This study also analyzed the inclusion of two TEG arrays on both sides of the HP condenser section. This numerical analysis was performed using COMSOL Multiphysics 5.5 software and was validated by previous analysis. The performance was evaluated through an energy and exergy analysis of the TEG and PV systems. Enhancing the thermal management of the hybrid PV-TEG system can increase energy production by 2.4% compared to a PV system operating under the same ambient and solar radiation conditions. Furthermore, if the proposed system includes a second array of TEG modules, the energy production increases by 5.8% compared to the PV system. The exergy analysis shows that the enhancement in the thermal management of the PV operating temperature decreases the thermal exergy efficiency of the proposed system but increases the electricity exergy efficiency. Including TEG modules on both sides of the condenser section of the HP shows the system’s best thermal and electrical performance. These results may be helpful for the optimal design of realistic solar-driven hybrid systems for globally deserted locations. Full article

Gesture recognition technology has emerged as a transformative solution for natural and intuitive human–computer interaction (HCI), offering touch-free operation across diverse fields such as healthcare, gaming, and smart home systems. In mobile contexts, where hygiene, convenience, and the ability to operate under resource constraints are critical, hand gesture recognition provides a compelling alternative to traditional touch-based interfaces. However, implementing effective gesture recognition in real-world mobile settings involves challenges such as limited computational power, varying environmental conditions, and the requirement for robust offline–online data management. In this study, we introduce ThumbsUp, which is a gesture-driven system, and employ a partially systematic literature review approach (inspired by core PRISMA guidelines) to identify the key research gaps in mobile gesture recognition. By incorporating insights from deep learning–based methods (e.g., CNNs and Transformers) while focusing on low resource consumption, we leverage Google’s MediaPipe in our framework for real-time detection of 21 hand landmarks and adaptive lighting pre-processing, enabling accurate recognition of a “thumbs-up” gesture. The system features a secure queue-based offline–cloud synchronization model, which ensures that the captured images and metadata (encrypted with AES-GCM) remain consistent and accessible even with intermittent connectivity. Experimental results under dynamic lighting, distance variations, and partially cluttered environments confirm the system’s superior low-light performance and decreased resource consumption compared to baseline camera applications. Additionally, we highlight the feasibility of extending ThumbsUp to incorporate AI-driven enhancements for abrupt lighting changes and, in the future, electromyographic (EMG) signals for users with motor impairments. Our comprehensive evaluation demonstrates that ThumbsUp maintains robust performance on typical mobile hardware, showing resilience to unstable network conditions and minimal reliance on high-end GPUs. These findings offer new perspectives for deploying gesture-based interfaces in the broader IoT ecosystem, thus paving the way toward secure, efficient, and inclusive mobile HCI solutions. Full article

This work presents an imaging testing system (software and hardware) that can generate repeatable images through a stabilized port in the soil for processes known to change with time. The system includes (i) a stabilized port in the ground made of standard PVC pipe, with sections lined with a borosilicate glass tube, and (ii) a digital imaging instrument to survey the optically transparent portion of the stabilized port. The instrument uses a probe containing a digital camera and two light sources, one using white lights and one using ultraviolet (UV) lights (365 nm). The main instrument controls the probe using a cable within the stabilized port to take overlapping pictures of the soil under the different light sources. Two examples are provided, one to document the distribution of soil and groundwater contaminants known as non-aqueous phase liquids (NAPL, which include petroleum) at variable water saturation levels and a second one to monitor the growth of a plant over a 2-week interval. In both examples, the system successfully identified critical changes in soil processes and showed a resolution of approximately 15 µm (in the order of the thickness of a human hair), demonstrating the potential for repeated imaging of soil processes known to experience temporal changes. Both examples are illustrative, as additional applications might be possible. The novelty of this system lies in its ability to generate repeated measurements at larger depths than the current shallow systems installed by hand. Full article

The aim of this research is to investigate the performance of indoor amorphous photovoltaic systems with PVC water cooling and compare them with those using heatsink cooling. The amorphous approach used in this study involves water flowing through a PVC pipe and a heatsink cooler. The circular heatsink that was used has fins all around it. The water flow through the pipe is pumped from the reservoir to the PVC pipe. The study found that a PVC water flow-based active cooling system is the most effective at preserving thermal stability and improving the performance of amorphous PV modules under high light intensity circumstances, providing insights for future advancements. Full article

In this study, the challenge of teleoperating robots in harsh environments such as underwater or in tunnels is addressed. In these environments, wireless communication networks are prone to congestion, leading to potential mission failures. Our approach integrates a Human–Robot Interface (HRI) with a network congestion control algorithm at the application level for conservative transmission of images using the Robot Operating System (ROS) framework. The system was designed to avoid network congestion by adjusting the image compression parameters and the transmission rate depending on the real-time network conditions. To evaluate its performance, the algorithm was tested in two wireless underwater use cases: pipe inspection and an intervention task. An Autonomous Underwater Vehicle for Intervention (I-AUV) equipped with a Visual Light Communication (VLC) modem was used. Characterization of the VLC network was performed while the robot performed trajectories in the tank. The results demonstrate that our approach allows an operator to perform wireless missions where teleoperation requires images and the network conditions are variable. This solution provides a robust framework for image transmission and network control in the application layer, which allows for integration with any ROS-based system. Full article

Detecting faulty pipelines in water management systems is crucial for ensuring a reliable supply of clean water. Traditional inspection methods are often time-consuming, costly, and prone to errors. This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. The YOLOv8 model is employed for object detection due to its exceptional performance in detecting objects, segmentation, pose estimation, tracking, and classification. By training on a large dataset of labeled images, the model effectively learns to identify visual patterns associated with pipeline faults. Experiments conducted on a real-world dataset demonstrate that the AI-based model significantly outperforms traditional methods in detection accuracy. The model also exhibits robustness to various environmental conditions such as lighting changes, camera angles, and occlusions, ensuring reliable performance in diverse scenarios. The efficient processing time of the model enables real-time fault detection in large-scale water distribution networks implementing this AI-based model offers numerous advantages for water management systems. It reduces dependence on manual inspections, thereby saving costs and enhancing operational efficiency. Additionally, the model facilitates proactive maintenance through the early detection of faults, preventing water loss, contamination, and infrastructure damage. The results from the three conducted experiments indicate that the model from Experiment 1 achieves a commendable mAP50 of 90% in detecting faulty pipes, with an overall mAP50 of 74.7%. In contrast, the model from Experiment 3 exhibits superior overall performance, achieving a mAP50 of 76.1%. This research presents a promising approach to improving the reliability and sustainability of water management systems through AI-based fault detection using image analysis. Full article

Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a state-of-the-art pose estimation model. A dataset was collected from 49 participants (35 males, 14 females) performing seven distinct exercises, with twelve anatomical landmarks then extracted using the Google MediaPipe library. Each landmark was represented by four features, which were used for classification. The core challenge addressed in this research involves ensuring accurate and real-time exercise classification across diverse body morphologies and exercise types. Several tree-based classifiers, including Random Forest, Extra Tree Classifier, XGBoost, LightGBM, and Hist Gradient Boosting, were employed. Furthermore, two novel ensemble models called RandomLightHist Fusion and StackedXLightRF are proposed to enhance classification accuracy. The RandomLightHist Fusion model achieved superior accuracy of 99.6%, demonstrating the system’s robustness and effectiveness. This innovation offers a practical solution for providing real-time feedback in telephysiotherapy, with potential to improve patient outcomes through accurate monitoring and assessment of exercise performance. Full article

This paper introduces an autonomous robot designed for in-pipe structural health monitoring of oil/gas pipelines. This system employs a 3D Optical Laser Scanning Technical Vision System (TVS) to continuously scan the internal surface of the pipeline. This paper elaborates on the mathematical methodology of 3D laser surface scanning based on dynamic triangulation. This paper presents the mathematical framework governing the combined kinematics of the Mobile Robot (MR) and TVS. It discusses the custom design of the MR, adjusting it to use of robustized mathematics, and incorporating a laser scanner produced using a 3D printer. Both experimental and theoretical approaches are utilized to illustrate the formation of point clouds during surface scanning. This paper details the application of the simple and robust mathematical algorithm RANSAC for the preliminary processing of the measured point clouds. Furthermore, it contributes two distinct and simplified criteria for detecting defects in pipelines, specifically tailored for computer processing. In conclusion, this paper assesses the effectiveness of the proposed mathematical and physical method through experimental tests conducted under varying light conditions. Full article

The term “viscoelastic pipe” refers to high polymer pipes that exhibit both elastic and viscoelastic properties. Owing to their widespread use in water transport systems, it is important to understand the transient flow characteristics of these materials for pipeline safety. Despite extensive research, these characteristics have not been sufficiently explored. This study evaluates the impact of friction models on the transient flow of viscoelastic pipes across various Reynolds numbers by employing an energy analysis approach. Given the complexity and computational demands of two-dimensional models, this paper compares the accuracy of one-dimensional and quasi-two-dimensional models. Notably, the superiority of the quasi-two-dimensional model in simulating viscoelastic pipelines is demonstrated. Owing to the interaction between pressure waves and fluid within viscoelastic pipes, fluid–structure coupling significantly attenuates pressure waves during transmission. These findings shed light on the constitutive properties of viscoelastic pipes and the influence of pipe wall friction models on transient hydraulic characteristics, building upon prior studies focused on elastic pipes. Nevertheless, numerous factors affecting transient flow in viscoelastic pipes remain unexplored. This paper suggests further analysis of strain effects, starting with temperature and pipe dynamics, to enhance the understanding of the coupling laws and flow mechanisms in viscoelastic pipelines. Full article

Stones are one of the primary objects that impede the normal activity of underground pipelines. As human intervention is difficult inside a narrow underground pipe, a robot with a machine vision system is required. In order to remove the stones during regular robotic inspections, precise stone detection, segmentation, and measurement of their distance from the robot are needed. We applied Mask R-CNN to perform an instant segmentation of stones. The distance between the robot and the segmented stones was calculated using spatial information obtained from a lidar camera. Artificial light was used for both image acquisition and testing, as natural light is not available inside the underground pipe. ResNet101 was chosen as the foundation of the Mask R-CNN, and transfer learning was utilized to shorten the training time. The experimental results of our model showed that the average detection precision rate reached 92.0; the recall rate was 90.0%; and the F1 score rate reached 91.0%. The distance values were calculated efficiently with an error margin of 11.36 mm. Moreover, the Mask R-CNN-based stone detection model can detect asymmetrically shaped stones in complex background and lighting conditions. Full article

The global scientific community is intensively promoting energy-plus buildings. Following the leading world trends, this paper presents a new energy-plus building concept—elevational earth-sheltered buildings with three different types of horizontal overhang photovoltaic-integrated panels: wooden support columns covered with clay tiles, steel pipes as support columns covered with sheet steel, and concrete support columns with concrete coverage. In this instance, the specific multi-numerical case study building model for the city of Kragujevac (located in central Serbia with favorable climatic conditions) was performed over 7 months (from 1 October to 30 April), taking into account the soil temperature, the effects of solar shading, the performance of the heating system—a ground source heat pump—and the characteristics of the artificial and automatic lighting control system. The simulation results show that the optimal depth of a horizontal overhang (energy-plus status) depends on the occupant’s habits, in addition to meteorological conditions. The presented methodology can be used for any other location, both in Europe and the world. Full article