dc.contributor.author | Maru, Vatsal K. | |
dc.contributor.author | Nannapaneni, Saideep | |
dc.contributor.author | Krishnan, Krishna K. | |
dc.date.accessioned | 2020-08-03T19:18:17Z | |
dc.date.available | 2020-08-03T19:18:17Z | |
dc.date.issued | 2020-06-10 | |
dc.identifier.citation | V. Maru, S. Nannapaneni and K. Krishnan, "Internet of Things based Cyber-Physical System framework for Real-Time Operations," 2020 IEEE 23rd International Symposium on Real-Time Distributed Computing (ISORC), Nashville, TN, USA, 2020, pp. 146-147 | en_US |
dc.identifier.isbn | 978-172816958-3 | |
dc.identifier.uri | https://doi.org/10.1109/ISORC49007.2020.00031 | |
dc.identifier.uri | https://soar.wichita.edu/handle/10057/18873 | |
dc.description | Click on the DOI link to access the article (may not be free). | en_US |
dc.description.abstract | The paper presents an intelligent cyber-physical system (CPS) framework using object detection for real-Time operations in an Internet-of-Things (IoT) connected physical environment. To facilitate real-Time object detection, we used a variant of Convolutional Neural Network (CNN) known as Faster R-CNN (R stands for the region proposals). The control action related to the detected object is exchanged with the actuation system using Real-Time Data Exchange (RTDE) protocol. We demonstrate the proposed framework to perform pick-And-place operations as it is a widely performed operation on a production floor using a Universal Robot (UR5) as an actuation system. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartofseries | 23rd International Symposium on Real-Time Distributed Computing;2020 IEEE | |
dc.subject | Convolutional neural network | en_US |
dc.subject | Cyber-physical | en_US |
dc.subject | Object detection | en_US |
dc.subject | Real-time control | en_US |
dc.subject | Universal robot | en_US |
dc.subject | Ur5 | en_US |
dc.title | Internet of things based cyber-physical system framework for real-time operations | en_US |
dc.type | Conference paper | en_US |
dc.rights.holder | © 2020 IEEE | en_US |