dc.contributor.author |
Skosana, Vusi J
|
|
dc.contributor.author |
Abu-Mahfouz, Adnan MI
|
|
dc.date.accessioned |
2022-05-09T08:31:45Z |
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dc.date.available |
2022-05-09T08:31:45Z |
|
dc.date.issued |
2021-12 |
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dc.identifier.citation |
Skosana, V. & Abu-Mahfouz, A.M. 2021. Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review. http://hdl.handle.net/10204/12408 . |
en_ZA |
dc.identifier.isbn |
978-1-6654-1091-5 |
|
dc.identifier.isbn |
978-1-6654-1092-2 |
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dc.identifier.uri |
DOI: 10.1109/FoNeS-AIoT54873.2021.00021
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|
dc.identifier.uri |
http://hdl.handle.net/10204/12408
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|
dc.description.abstract |
Wireless Multimedia Sensor Networks (WMSN) hold the key to unlocking the next generation of video surveillance applications. They operate under energy-constrained environments but Compressive Sensing (CS) is a tool that can help overcome these challenges. Sensing matrices are critical in delivering the promise of CS, there are different types and each has its benefits and costs. In this paper, these sensing matrices are compared and the strengths and weaknesses were highlighted. It was found that deterministic sensing matrices held the most promise as they gave better recovery accuracy than dense random matrices while being more efficient but, work still needs to be done to evaluate the energy cost of their implementation. |
en_US |
dc.format |
Abstract |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.uri |
https://ieeexplore.ieee.org/document/9759936 |
en_US |
dc.source |
2021 International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT), Nicosia, Turkey, 27-28 December 2021 |
en_US |
dc.subject |
Compressive sensing |
en_US |
dc.subject |
Image compression |
en_US |
dc.subject |
Matrix |
en_US |
dc.subject |
Sensing |
en_US |
dc.subject |
Wireless Multimedia Sensor Networks |
en_US |
dc.title |
Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.description.pages |
6pp |
en_US |
dc.description.note |
©2021 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9759936 |
en_US |
dc.description.cluster |
Next Generation Enterprises & Institutions |
en_US |
dc.description.impactarea |
EDT4IR Management |
en_US |
dc.identifier.apacitation |
Skosana, V., & Abu-Mahfouz, A. M. (2021). Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review. http://hdl.handle.net/10204/12408 |
en_ZA |
dc.identifier.chicagocitation |
Skosana, V, and Adnan MI Abu-Mahfouz. "Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review." <i>2021 International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT), Nicosia, Turkey, 27-28 December 2021</i> (2021): http://hdl.handle.net/10204/12408 |
en_ZA |
dc.identifier.vancouvercitation |
Skosana V, Abu-Mahfouz AM, Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review; 2021. http://hdl.handle.net/10204/12408 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Skosana, V
AU - Abu-Mahfouz, Adnan MI
AB - Wireless Multimedia Sensor Networks (WMSN) hold the key to unlocking the next generation of video surveillance applications. They operate under energy-constrained environments but Compressive Sensing (CS) is a tool that can help overcome these challenges. Sensing matrices are critical in delivering the promise of CS, there are different types and each has its benefits and costs. In this paper, these sensing matrices are compared and the strengths and weaknesses were highlighted. It was found that deterministic sensing matrices held the most promise as they gave better recovery accuracy than dense random matrices while being more efficient but, work still needs to be done to evaluate the energy cost of their implementation.
DA - 2021-12
DB - ResearchSpace
DP - CSIR
J1 - 2021 International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT), Nicosia, Turkey, 27-28 December 2021
KW - Compressive sensing
KW - Image compression
KW - Matrix
KW - Sensing
KW - Wireless Multimedia Sensor Networks
LK - https://researchspace.csir.co.za
PY - 2021
SM - 978-1-6654-1091-5
SM - 978-1-6654-1092-2
T1 - Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review
TI - Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review
UR - http://hdl.handle.net/10204/12408
ER - |
en_ZA |
dc.identifier.worklist |
25609 |
en_US |