Опубликована: Май 2, 2024
Язык: Английский
Sensors, Год журнала: 2025, Номер 25(3), С. 765 - 765
Опубликована: Янв. 27, 2025
This article focuses on the integration of Internet Things (IoT) and Robotic Things, representing a dynamic research area with significant potential for industrial applications. The (IoRT) integrates IoT technologies into robotic systems, enhancing their efficiency autonomy. provides an overview used in IoRT, including hardware components, communication technologies, cloud services. It also explores IoRT applications industries such as healthcare, agriculture, more. discusses challenges future directions, data security, energy efficiency, ethical issues. goal is to raise awareness importance demonstrate how this technology can bring benefits across various sectors.
Язык: Английский
Процитировано
2
Sensors, Год журнала: 2024, Номер 24(4), С. 1099 - 1099
Опубликована: Фев. 8, 2024
(1) Background: A current trend observed in the logistics sector is use of Industry 4.0 tools to improve and enhance efficiency cargo handling processes. One popular solutions an augmented reality system that supports operators everyday tasks. The article aims present design assumptions for implementing support air at warehouse. (2) Methods: Research was carried out based on a five-stage analytical procedure, aiming analyze state identify potential AR system. following methods were used collect data: co-participant observations, process analysis, direct interviews, analysis internal documentation, applicable legal regulations. (3) Results: conducted research allowed identifying information flows accompanying developing project automate selected flows. obtained results made it possible operations which system’s implementation will increase their effectiveness efficiency. (4) Conclusions: identified need develop hybrid algorithm arranging warehouse build supporting self-verification markings cargo.
Язык: Английский
Процитировано
6
Опубликована: Авг. 5, 2024
There is a growing need to implement modern technologies, such as digital twinning, improve the efficiency of transport fleet maintenance processes and maintain company's operational capacity at required level. Therefore, paper reviews existing literature present an up-to-date content-relevant analysis in this field. The proposed methodology systematic review using Primo multi-search tool following Preferred Reporting Items for Systematic Reviews Meta-Analyzes (PRISMA) guidelines. main inclusion criteria included publication dates (studies published from 2012–2024) studies English. This resulted selection 201 most relevant papers area investigation. Finally, selected articles were categorized into seven groups: a) air transportation, b) railway c) land transportation (road), d) in-house logistics, e) water intermodal f) supply chain operation, g) other applications. One advantages study that results are obtained different scientific sources/databases thanks tool. Moreover, bibliometric was performed. have led authors specify research problems trends related analyzed identify gaps future investigation academic engineering perspectives. In addition, based on results, framework DT system developed. ends with conclusions directions.
Язык: Английский
Процитировано
6
International Journal on Interactive Design and Manufacturing (IJIDeM), Год журнала: 2023, Номер 18(8), С. 6069 - 6091
Опубликована: Окт. 7, 2023
Язык: Английский
Процитировано
14
Applied Sciences, Год журнала: 2023, Номер 13(17), С. 9895 - 9895
Опубликована: Сен. 1, 2023
The future development of Industry 4.0 places paramount importance on human-centered/-centric factors in the production, design, and management logistic systems, which has led to emergence 5.0. However, effectively integrating logistics scenarios become a challenge. A pivotal technological solution for dealing with such challenge is distinguish track moving objects as humans goods. Therefore, an algorithm model combining YOLOv5 DeepSORT warehouse object tracking designed, where selected object-detection distinguishes from goods environments. evaluation metrics MOT Challenge affirm algorithm’s robustness efficacy. Through rigorous experimental tests, combined demonstrates rapid convergence (within 30 ms), holds promising potential applications real-world warehouses.
Язык: Английский
Процитировано
13
Applied Sciences, Год журнала: 2025, Номер 15(2), С. 589 - 589
Опубликована: Янв. 9, 2025
Background: The paper aims at answering cognitive questions which let one draw conclusions on AR usability in terms of supporting the dangerous goods acceptance (DGA) process before air transportation, including (1) operations DGA airports reveal highest potential being supported by solutions? (2) Which parameters can be improved use (3) What benefits and drawbacks solutions derived from technology have been noticed practical experiments? Research method: study has conducted analysing while considering support technology, development applications for goggles a mobile phone, their testing. Results: There model developed as well decision algorithms, helping operators controlling DGs flight, identified. Following these foundations, design functions DG indicated expected influence results evaluated. Conclusions: very positively assessed experts; however, there also observed differences between that indicate most promising less aspects. Operators especially appreciate when goal is to show virtual picture data related law regulations regarding controlled DGs, interactions with are positively. prove that, present stage development, tools assist an operator neither carried out automatically.
Язык: Английский
Процитировано
0
Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Март 1, 2025
With the rapid growth of e-commerce and ongoing innovations in logistics industry, intelligent unmanned warehousing systems have emerged to significantly enhance operational efficiency reduce costs. In these systems, two critical stages order assignment path planning are interconnected through racks picking process. However, prior research has largely overlooked their joint optimization. this paper, we investigate real time task problem (RTTP) warehousing, where dynamically assigned orders arriving time, robots responsible for delivering workstations according planned paths, with goal jointly minimizing total processing travel To solve RTTP, first design a optimization evaluation indicator propose (JOTP) algorithm. Furthermore, innovatively introduce reinforcement learning-based approach (JOTP-RL) by modeling selection as partially observable Markov decision process (POMDP), employing Q-Mix algorithm it. efficiency, optimize improved THA $$^*$$ eliminating redundant calculations accounting congestion times. Finally, extensive experiments conducted on datasets demonstrate that our proposed algorithms outperform baseline state-of-the-art methods, achieving superior effectiveness both execution
Язык: Английский
Процитировано
0
Journal of Organizational and End User Computing, Год журнала: 2025, Номер 37(1), С. 1 - 26
Опубликована: Март 5, 2025
Estimated Time of Arrival (ETA) is a crucial task in the logistics and transportation industry, aiding businesses individuals optimizing time management improving operational efficiency. This study proposes novel Graph Recurrent Neural Network (GRNN) model that integrates external factor data. The first employs Multilayer Perceptron (MLP)-based data embedding layer to categorize combine influencing factors into vector representation. A Network, combining Long Short-Term Memory (LSTM) GNN models, then used predict ETA based on historical undergoes both offline online evaluation experiments. Specifically, experiments demonstrate 5.3% reduction RMSE BikeNYC dataset 6.1% DidiShenzhen dataset, compared baseline models. Online using Baidu Maps further validates model's effectiveness real-time scenarios. These results underscore potential predictions for urban traffic systems.
Язык: Английский
Процитировано
0
The European Physical Journal Special Topics, Год журнала: 2025, Номер unknown
Опубликована: Янв. 7, 2025
Язык: Английский
Процитировано
0
Procedia Computer Science, Год журнала: 2025, Номер 253, С. 2951 - 2960
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0