Building information modeling and complementary technologies in heritage buildings: A bibliometric analysis

Results in Engineering, Год журнала: 2024, Номер 22, С. 102192 - 102192

Опубликована: Апрель 29, 2024

Язык: Английский

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Time-Series Image-Based Automated Monitoring Framework for Visible Facilities: Focusing on Installation and Retention Period

Sensors, Год журнала: 2025, Номер 25(2), С. 574 - 574

Опубликована: Янв. 20, 2025

In the construction industry, ensuring proper installation, retention, and dismantling of temporary structures, such as jack supports, is critical to maintaining safety project timelines. However, inconsistencies between on-site data documentation remain a significant challenge. To address this, this study proposes an integrated monitoring framework that combines computer vision-based object detection document recognition techniques. The system utilizes YOLOv5 for detecting supports in both drawings images captured through wearable cameras, while optical character (OCR) natural language processing (NLP) extract installation timelines from work orders. proposed enables continuous ensures compliance with retention periods by aligning documented requirements. analysis includes 23 monitored daily over 28 days under varying environmental conditions, including lighting changes structural configurations. results demonstrate achieves average accuracy 94.1%, effectively identifying discrepancies reducing misclassifications caused similarities variations. further enhance reliability, methods color differentiation, plan overlays, vertical segmentation were implemented, significantly improving performance. This validates effectiveness integrating visual textual sources dynamic environments. development automated systems measures manual intervention, offering practical insights future site management.

Язык: Английский

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BIM Integration with XAI Using LIME and MOO for Automated Green Building Energy Performance Analysis

Energies, Год журнала: 2024, Номер 17(13), С. 3295 - 3295

Опубликована: Июль 4, 2024

Achieving sustainable green building design is essential to reducing our environmental impact and enhancing energy efficiency. Traditional methods often depend heavily on expert knowledge subjective decisions, posing significant challenges. This research addresses these issues by introducing an innovative framework that integrates information modeling (BIM), explainable artificial intelligence (AI), multi-objective optimization. The includes three main components: data generation through DesignBuilder simulation, a BO-LGBM (Bayesian optimization–LightGBM) predictive model with LIME (Local Interpretable Model-agnostic Explanations) for prediction interpretation, the optimization technique AGE-MOEA address uncertainties. A case study demonstrates framework’s effectiveness, achieving high accuracy (R-squared > 93.4%, MAPE < 2.13%) identifying HVAC system features. resulted in 13.43% improvement consumption, CO2 emissions, thermal comfort, additional 4.0% gain when incorporating enhances transparency of machine learning predictions efficiently identifies optimal passive active solutions, contributing significantly construction practices. Future should focus validating its real-world applicability, assessing generalizability across various types, integrating generative capabilities automated

Язык: Английский

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Priority-based scheduling in residential energy management systems integrated with renewable sources using adaptive Salp swarm algorithm

Results in Engineering, Год журнала: 2024, Номер 23, С. 102643 - 102643

Опубликована: Июль 31, 2024

With the remarkable growth and implementation of communication technology, sensors, measurement equipment in Smart Grid (SG) environment, demand side management (DSM) response (DRs) can be easily implementable residential energy systems integrated with renewable sources (RES). Looking at this perspective, paper suggests an intelligent dynamic load-priority-based scheduling optimal smart system (REMS). The objectives to achieve through priority-based case a are multi-focussed terms peak load reduction, consumer choice consumption according priority basis, cost-effectiveness towards electricity price savings. issues related uncertainties RES due environmental dependency must incorporated into DSM. A single objective discrete formulation based on Adaptive Salp Swarm Algorithm (ASSA) has been done modelling optimizing crucial parameters for scheduling, ideally operation appliances, along prioritized-based loads available. System constraints, priorities, source availability, uncertainties, considered justify approach that is feasible real-time conditions. To enhance search capabilities SSA, control vary optimally both exploration exploitation stages searching. Comparative results genetic algorithms (GA), particle swarm optimization (PSO), conventional SSA presented different cases, such as (1) traditional homes without REMS, (ii) REMS (iii) using RES.

Язык: Английский

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MSVMD-Informer: A Multi-Variate Multi-Scale Method to Wind Power Prediction

Energies, Год журнала: 2025, Номер 18(7), С. 1571 - 1571

Опубликована: Март 21, 2025

Wind power prediction plays a crucial role in enhancing grid stability and wind energy utilization efficiency. Existing methods demonstrate insufficient integration of multi-variate features, such as speed, temperature, humidity, along with inadequate extraction correlations between variables. This paper proposes novel multi-scale method named variational mode decomposition informer (MSVMD-Informer). First, modal module is designed to decompose univariate time-series features into multiple scales. Adaptive graph convolution applied extract scales, while self-attention mechanisms are utilized capture temporal dependencies within the same scale. Subsequently, feature fusion proposed better account for inter-variable correlations. Finally, reconstructed by integrating aforementioned modules, enabling forecasting. The was evaluated through comparative experiments ablation studies against seven baselines using public dataset two private datasets. Experimental results that our achieves optimal metric performance, its lowest MAPE scores being 1.325%, 1.500% 1.450%, respectively.

Язык: Английский

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Optimizing sustainable alternatives in value engineering Decision-Making through BIM-Integrated plugin automation for buildings

Ain Shams Engineering Journal, Год журнала: 2025, Номер 16(6), С. 103373 - 103373

Опубликована: Апрель 1, 2025

Язык: Английский

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Key factors shaping post-disaster building damage assessment: insights from the Gaza Strip as a conflict zone

Journal of Asian Architecture and Building Engineering, Год журнала: 2025, Номер unknown, С. 1 - 21

Опубликована: Апрель 1, 2025

Язык: Английский

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Sustainability in construction economics as a barrier to cloud computing adoption in small-scale Building projects

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 2, 2025

Язык: Английский

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Optimizing Energy Efficiency Through Building Orientation and Building Information Modelling (BIM) in Diverse Terrains: A Case Study in Pakistan

Energy, Год журнала: 2024, Номер unknown, С. 133307 - 133307

Опубликована: Окт. 1, 2024

Язык: Английский

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A Comprehensive Review of UAV-UGV Collaboration: Advancements and Challenges

Journal of Sensor and Actuator Networks, Год журнала: 2024, Номер 13(6), С. 81 - 81

Опубликована: Ноя. 28, 2024

Unmanned aerial vehicles (UAVs) and unmanned ground (UGVs) have rapidly evolved, becoming integral to various applications such as environmental monitoring, disaster response, precision agriculture. This paper provides a comprehensive review of the advancements challenges in UAV-UGV collaboration its potential applications. These systems offer enhanced situational awareness operational efficiency, enabling complex tasks that are beyond capabilities individual by leveraging complementary strengths UAVs UGVs. Key areas explored this include multi-UAV multi-UGV systems, collaborative operations, communication coordination mechanisms support these efforts. Furthermore, discusses limitations, future research directions, considers issues computational constraints, network instability, adaptability. The also detailed analysis how impact effectiveness collaboration.

Язык: Английский

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