Real-time 3D data acquisition for augmented-reality man and machine interfacing

2003 ◽  
Author(s):  
Chun Guan ◽  
Laurence G. Hassebrook ◽  
Daniel L. Lau
2016 ◽  
Author(s):  
Laura Haraké ◽  
Hendrik Schilling ◽  
Christian Blohm ◽  
Markus Hillemann ◽  
Andreas Lenz ◽  
...  
Keyword(s):  

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Rujianto Eko Saputro ◽  
Dhanar Intan Surya Saputra
Keyword(s):  

Media pembelajaran ternyata selalu mengikuti perkembangan teknologi yangada, mulai dari teknologi cetak, audio visual, komputer sampai teknologi gabunganantara teknologi cetak dengan komputer. Saat ini media pembelajaran hasil gabunganteknologi cetak dan komputer dapat diwujudkan dengan media teknologi AugmentedReality (AR). Augmented Reality (AR) adalah teknologi yang digunakan untukmerealisasikan dunia virtual ke dalam dunia nyata secara real-time. Organ pencernaanmanusia terdiri atas Mulut, Kerongkongan atau esofagus, Lambung, Usus halus, danUsus besar. Media pembelajaran mengenal organ pencernaan manusia pada saat inisangat monoton, yaitu melalui gambar, buku atau bahkan alat proyeksi lainnya.Menggunakan Augmented Reality yang mampu merealisasikan dunia virtual ke dunianyata, dapat mengubah objek-objek tersebut menjadi objek 3D, sehingga metodepembelajaran tidaklah monoton dan anak-anak jadi terpacu untuk mengetahuinya lebihlanjut, seperti mengetahui nama organ dan keterangan dari masing-masing organtersebut.


2018 ◽  
Author(s):  
Kyle Plunkett

This manuscript provides two demonstrations of how Augmented Reality (AR), which is the projection of virtual information onto a real-world object, can be applied in the classroom and in the laboratory. Using only a smart phone and the free HP Reveal app, content rich AR notecards were prepared. The physical notecards are based on Organic Chemistry I reactions and show only a reagent and substrate. Upon interacting with the HP Reveal app, an AR video projection shows the product of the reaction as well as a real-time, hand-drawn curved-arrow mechanism of how the product is formed. Thirty AR notecards based on common Organic Chemistry I reactions and mechanisms are provided in the Supporting Information and are available for widespread use. In addition, the HP Reveal app was used to create AR video projections onto laboratory instrumentation so that a virtual expert can guide the user during the equipment setup and operation.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.


2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.


J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.


Author(s):  
Cheyma BARKA ◽  
Hanen MESSAOUDI-ABID ◽  
Houda BEN ATTIA SETTHOM ◽  
Afef BENNANI-BEN ABDELGHANI ◽  
Ilhem SLAMA-BELKHODJA ◽  
...  

2021 ◽  
Vol 1768 (1) ◽  
pp. 012017
Author(s):  
K Burhanudin ◽  
M H Jusoh ◽  
Z I Abdul Latiff ◽  
M S Suaimi ◽  
Z Ibrahim ◽  
...  

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