A digital twin system for centrifugal pump fault diagnosis driven by transfer learning based on graph convolutional neural networks

Computers in Industry, Год журнала: 2024, Номер 163, С. 104155 - 104155

Опубликована: Авг. 30, 2024

Язык: Английский

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Advanced Energy Performance Modelling: Case Study of an Engineering and Technology Precinct

Buildings, Год журнала: 2024, Номер 14(6), С. 1774 - 1774

Опубликована: Июнь 12, 2024

The global demand for energy is significantly impacted by the consumption patterns within building sector. As such, importance of simulation and prediction growing exponentially. This research leverages Building Information Modelling (BIM) methodologies, creating a synergy between traditional software methods algorithm-driven approaches comprehensive analysis. study also proposes method monitoring select management factors, step that could potentially pave way integration digital twins in systems. grounded case newly constructed educational New South Wales, Australia. physical model was created using Autodesk Revit, conventional BIM methodology. EnergyPlus, facilitated OpenStudio, employed software-based analysis output then used to develop preliminary algorithm models regression strategies Python. In this analysis, temperature relative humidity each unit were as independent variables, with their being dependent variable. sigmoid model, known its accuracy interpretability, advanced simulation. combined sensor data real-time prediction. A basic twin (DT) example simulate dynamic control air conditioning lighting, showcasing adaptability effectiveness system. explores potential machine learning, specifically reinforcement optimizing response environmental changes usage conditions. Despite current limitations, identifies future directions. These include enhancing developing complex algorithms boost efficiency reduce costs.

Язык: Английский

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Data Enabling Technology in Digital Twin and its Frameworks in Different Industrial Applications

Journal of Industrial Information Integration, Год журнала: 2025, Номер unknown, С. 100793 - 100793

Опубликована: Фев. 1, 2025

Язык: Английский

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Digital twin enhanced with Machine Learning Algorithms for Irrigation Management Using Sensor Data

Procedia Computer Science, Год журнала: 2025, Номер 253, С. 2419 - 2427

Опубликована: Янв. 1, 2025

Язык: Английский

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Energy Saving Management in Russian Agriculture Using Digital Technologies

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 337 - 348

Опубликована: Янв. 1, 2025

Язык: Английский

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Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review

Applied Sciences, Год журнала: 2025, Номер 15(8), С. 4228 - 4228

Опубликована: Апрель 11, 2025

This systematic review explores the use of digital twins (DT) for sustainable agricultural water management. DTs simulate real-time environments, enabling precise resource allocation, predictive maintenance, and scenario planning. AI enhances DT performance through machine learning (ML) data-driven insights, optimizing usage. In this study, from an initial pool 48 papers retrieved well-known databases such as Scopus Web Science, etc., a rigorous eligibility criterion was applied, narrowing focus to 11 pertinent studies. highlights major disciplines where technology is being applied: hydroponics, aquaponics, vertical farming, irrigation. Additionally, literature identifies two key sub-applications within these disciplines: simulation prediction quality soil water. also types maturity levels concepts applications. Based on their current implementation, in agriculture can be categorized into functional types: monitoring DTs, which emphasize response environmental control, enable proactive irrigation management forecasting. techniques used framework were identified based These findings underscore transformative role that play enhancing efficiency sustainability Despite technological advancements, challenges remain, including data integration, scalability, cost barriers. Further studies should conducted explore issues practical farming environments.

Язык: Английский

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Cloud computing and digital twin-based healthcare monitoring frameworks for next generation

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 193 - 212

Опубликована: Янв. 1, 2025

Язык: Английский

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Exploring the Comprehensive Integration of Artificial Intelligence in Optimizing HVAC System Operations: A Review and Future Outlook

Results in Engineering, Год журнала: 2024, Номер unknown, С. 103765 - 103765

Опубликована: Дек. 1, 2024

Язык: Английский

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Rethinking and redesigning storage, packaging and distribution practices for food supply chain

British Food Journal, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 10, 2024

Purpose The study aims to add the existing literature on food supply chains by specifically taking into redesigning of alignment storage, packaging and distribution practices in modern complex chain. redesign chain’s is a transformative endeavor ultimately aimed at enhancing efficiency, sustainability reliability. Design/methodology/approach In order identify, classify prioritize main challenges, this conducted an extensive analysis experts’ opinions areas academia, information technology chain (FSC) using combined compromise solution method (CoCoSo) proportional assessment (COPRAS). Findings top three classes key indicators revealed are dynamic route optimization on-demand delivery pods (RD4), implementation active with nanotechnology (RP3) collaborative last-mile (RD2). findings reveal that (RD4) (RD2) maintaining balance between networks through which very discussable theme recent literature. Originality/value research provides fresh insights how perishable shelf life parameters use within short can be taken consideration when system for chains.

Язык: Английский

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Special Issue on Digital Twin for Future Networks and Emerging IoT Applications (DT4IoT)

Future Generation Computer Systems, Год журнала: 2024, Номер 161, С. 81 - 84

Опубликована: Июнь 28, 2024

Язык: Английский

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