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Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario = = Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario =/
其他題名:	Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.
其他題名:	Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.
作者:	Atalik, Ahmet Arda.
面頁冊數:	1 online resource (57 pages)
附註:	Source: Masters Abstracts International, Volume: 84-05.
Contained By:	Masters Abstracts International84-05.
標題:	Innovations. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30158199click for full text (PQDT)
ISBN:	9798352990049

Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario = = Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.
Atalik, Ahmet Arda.

Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario =Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim. - 1 online resource (57 pages)

Source: Masters Abstracts International, Volume: 84-05.

Thesis (M.Sc.)--Bilkent Universitesi (Turkey), 2022.

Includes bibliographical references

Goal-oriented signal processing and communications are assured to play a key role in developing the next generation of sensor devices and networks, e.g., 6G IoT networks. A critical task of semantic signal processing is the detection of innovation and transmission scheduling based on the innovation in AI-enabled sensor networks and IoT for 6G. This thesis proposes efficient and optimal sampling and transmission strategies for goal-oriented sensor networks for various data models, investigates their performances both analytically and numerically; and introduces the use of dimensionality reduction algorithms in semantic signal processing and highlights its effectiveness in real life case studies. That is, the proposed methods are explained rigorously and demonstrated through simulations and case studies based on real-world computer vision examples with recorded video signals. Numerical results indicate that the next generation sensor devices and networks can benefit significantly from the proposed methods in terms of energy efficiency and semantic innovation detection performances.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352990049Subjects--Topical Terms:

754112
Innovations.
Index Terms--Genre/Form:

542853
Electronic books.

Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario = = Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.
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245 1 0 $a Innovation Based Transmission in Ai-Enabled Sensor Networks for 6G Iot Scenario = $b Yapay Zeka Etkinlenmis Sensor Aglarinda 6G Nesnelerin Interneti Senaryolari Icin Inovasyon Bazli Iletim.
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500 $a Source: Masters Abstracts International, Volume: 84-05.
500 $a Advisor: Arikan, Orhan.
502 $a Thesis (M.Sc.)--Bilkent Universitesi (Turkey), 2022.
504 $a Includes bibliographical references
520 $a Goal-oriented signal processing and communications are assured to play a key role in developing the next generation of sensor devices and networks, e.g., 6G IoT networks. A critical task of semantic signal processing is the detection of innovation and transmission scheduling based on the innovation in AI-enabled sensor networks and IoT for 6G. This thesis proposes efficient and optimal sampling and transmission strategies for goal-oriented sensor networks for various data models, investigates their performances both analytically and numerically; and introduces the use of dimensionality reduction algorithms in semantic signal processing and highlights its effectiveness in real life case studies. That is, the proposed methods are explained rigorously and demonstrated through simulations and case studies based on real-world computer vision examples with recorded video signals. Numerical results indicate that the next generation sensor devices and networks can benefit significantly from the proposed methods in terms of energy efficiency and semantic innovation detection performances.
520 $a Hedefe yonelik sinyal isleme ve iletisim gelecek nesil (6G) sensor ag ve aygitlarinin gelistirilmesinde anahtar bir rol oynayacaktir. Hedefe yonelik sinyal islemede kri- tik bir is paketi ise inovasyon kestirimi ve inovasyon bazli iletim yontemlerinin akilli sensor ve nesnelerin interneti aglarinda 6G senaryolari icin kullanimidir. Bu tez hedefe yonelik sensor aglari icin verimli ve eniyi ornekleme ve iletim stratejileri ileri surup bunlarin performanslarini analitik ve numerik olarak in- celer ve anlamsal sinyal islemede boyut indirgeme algoritmalarinin kullanimini one surerek gercek hayat uygulamalarinda bu metotlarin etkinligini vurgular. Onerilen metotlar dikkatli bir bicimde aciklandiktan sonra gercek hayat bilgisa- yar gorusu ornekleri ve vaka analizleriyle desteklenir. Yapilan numerik calismalar gelecek nesil sensor ag ve aygitlarini ileri surulen metotlardan enerji verimi ve anlamsal inovasyon kestirimi bakimindan belirgin bicimde yararlanabilecegini or- taya koymaktadir.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Innovations. $3 754112
650 4 $a Communication. $3 524709
650 4 $a Sensors. $3 3549539
650 4 $a Signal processing. $3 533904
650 4 $a Radio frequency identification. $3 3686382
650 4 $a Energy efficiency. $3 3555643
650 4 $a Probability. $3 518898
650 4 $a Algorithms. $3 536374
650 4 $a Semantics. $3 520060
650 4 $a Computer science. $3 523869
650 4 $a Electrical engineering. $3 649834
650 4 $a Energy. $3 876794
650 4 $a Information technology. $3 532993
650 4 $a Logic. $3 529544
650 4 $a Mathematics. $3 515831
650 4 $a Web studies. $3 2122754
655 7 $a Electronic books. $2 lcsh $3 542853
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690 $a 0984
690 $a 0544
690 $a 0791
690 $a 0489
690 $a 0395
690 $a 0405
690 $a 0646
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Bilkent Universitesi (Turkey). $3 1919057
773 0 $t Masters Abstracts International $g 84-05.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30158199 $z click for full text (PQDT)