On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge
As reported in the recent image velocimetry literature, tracking the motion of sparse feature points floating on the river surface as done by the Optical Tracking Velocimetry (OTV) algorithm is a promising strategy to address surface flow monitoring. Moreover, the lightweight nature of OTV coupled w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/15/7027 |
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| author | Arsal-Hanif Livoroi Andrea Conti Luca Foianesi Fabio Tosi Filippo Aleotti Matteo Poggi Flavia Tauro Elena Toth Salvatore Grimaldi Stefano Mattoccia |
| author_facet | Arsal-Hanif Livoroi Andrea Conti Luca Foianesi Fabio Tosi Filippo Aleotti Matteo Poggi Flavia Tauro Elena Toth Salvatore Grimaldi Stefano Mattoccia |
| author_sort | Arsal-Hanif Livoroi |
| collection | DOAJ |
| description | As reported in the recent image velocimetry literature, tracking the motion of sparse feature points floating on the river surface as done by the Optical Tracking Velocimetry (OTV) algorithm is a promising strategy to address surface flow monitoring. Moreover, the lightweight nature of OTV coupled with computational optimizations makes it suited even for its deployment in situ to perform measurements at the edge with cheap embedded devices without the need to perform offload processing. Despite these notable achievements, the actual practical deployment of OTV in remote environments would require cheap and self-powered systems enabling continuous measurements without the need for cumbersome and expensive infrastructures rarely found in situ. Purposely, in this paper, we propose an additional simplification to the OTV algorithm to reduce even further its computational requirements, and we analyze self-powered off-the-shelf setups for in situ deployment. We assess the performance of such set-ups from different perspectives to determine the optimal solution to design a cost-effective self-powered measurement node. |
| first_indexed | 2024-03-10T09:18:46Z |
| format | Article |
| id | doaj.art-5dd54fb8019c41b8aefdb3e811744caf |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:18:46Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5dd54fb8019c41b8aefdb3e811744caf2023-11-22T05:23:19ZengMDPI AGApplied Sciences2076-34172021-07-011115702710.3390/app11157027On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the EdgeArsal-Hanif Livoroi0Andrea Conti1Luca Foianesi2Fabio Tosi3Filippo Aleotti4Matteo Poggi5Flavia Tauro6Elena Toth7Salvatore Grimaldi8Stefano Mattoccia9Department of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyDepartment for Innovation in Biological, Agro-Food and Forest Systems, University of Tuscia, 01100 Viterbo, ItalyDepartment of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, 40136 Bologna, ItalyDepartment for Innovation in Biological, Agro-Food and Forest Systems, University of Tuscia, 01100 Viterbo, ItalyDepartment of Computer Science and Engineering, University of Bologna, 40136 Bologna, ItalyAs reported in the recent image velocimetry literature, tracking the motion of sparse feature points floating on the river surface as done by the Optical Tracking Velocimetry (OTV) algorithm is a promising strategy to address surface flow monitoring. Moreover, the lightweight nature of OTV coupled with computational optimizations makes it suited even for its deployment in situ to perform measurements at the edge with cheap embedded devices without the need to perform offload processing. Despite these notable achievements, the actual practical deployment of OTV in remote environments would require cheap and self-powered systems enabling continuous measurements without the need for cumbersome and expensive infrastructures rarely found in situ. Purposely, in this paper, we propose an additional simplification to the OTV algorithm to reduce even further its computational requirements, and we analyze self-powered off-the-shelf setups for in situ deployment. We assess the performance of such set-ups from different perspectives to determine the optimal solution to design a cost-effective self-powered measurement node.https://www.mdpi.com/2076-3417/11/15/7027optical tracking velocimetryOTVsurface flow monitoringcomputer visionriver surface velocityparticle tracking |
| spellingShingle | Arsal-Hanif Livoroi Andrea Conti Luca Foianesi Fabio Tosi Filippo Aleotti Matteo Poggi Flavia Tauro Elena Toth Salvatore Grimaldi Stefano Mattoccia On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge Applied Sciences optical tracking velocimetry OTV surface flow monitoring computer vision river surface velocity particle tracking |
| title | On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge |
| title_full | On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge |
| title_fullStr | On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge |
| title_full_unstemmed | On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge |
| title_short | On the Deployment of Out-of-the-Box Embedded Devices for Self-Powered River Surface Flow Velocity Monitoring at the Edge |
| title_sort | on the deployment of out of the box embedded devices for self powered river surface flow velocity monitoring at the edge |
| topic | optical tracking velocimetry OTV surface flow monitoring computer vision river surface velocity particle tracking |
| url | https://www.mdpi.com/2076-3417/11/15/7027 |
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