ResearchSpace

Energy-efficient sensing matrices for Wireless Multimedia Sensor Networks: A Review

Show simple item record

dc.contributor.author Skosana, V
dc.contributor.author Abu-Mahfouz, Adnan MI
dc.date.accessioned 2022-05-09T08:31:45Z
dc.date.available 2022-05-09T08:31:45Z
dc.date.issued 2021-12
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
dc.identifier.uri DOI: 10.1109/FoNeS-AIoT54873.2021.00021
dc.identifier.uri http://hdl.handle.net/10204/12408
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


Files in this item

This item appears in the following Collection(s)

Show simple item record