Deep learning for internet of things infrastructure:
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging...
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press, Taylor & Francis Group
2022
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| Ausgabe: | First edition |
| Zusammenfassung: | This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users.FEATURESPromotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructuresAddresses emerging trends and issues on IoT systems and services across various application domainsInvestigates the challenges posed by the implementation of deep learning on IoT networking models and servicesProvides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoTExplores new functions and technologies to provide adaptive services and intelligent applications for different end usersUttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia.Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom.Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh |
| Beschreibung: | 1. Data Caching at Fog Nodes under IoT Networks: Review of Machine Learning Approaches; Riya, Nitin Gupta, and Qin Xin; 2. ECC-Based Privacy-Preserving Mechanisms Using Deep Learning for Industrial IoT: A State-of-the-Art Approaches; R. Sivaranjani, P. Muralidhara Rao, and P. Saraswathi; 3. Contemporary Developments and Technologies in Deep Learning–Based IoT; Prishita Ray, Rajesh Kaluri, Thippa Reddy G., Praveen Kumar Reddy M., and Kuruva Lakshmanna; 4. Deep Learning–Assisted Vehicle Counting for Intersection and Traffic Management in Smart Cities; Guy M. Lingani, Danda B. Rawat, and Moses Garuba; 5. Toward Rapid Development and Deployment of Machine Learning Pipelines across Cloud-Edge; Anirban Bhattacharjee, Yogesh Barve, Shweta Khare, Shunxing Bao, Zhuangwei Kang, Aniruddha Gokhale, and Thomas Damiano; 6. Category Identification Technique by a Semantic Feature Generation Algorithm; Somenath Chakraborty; 7. Role of Deep Learning Algorithms in Securing Internet of Things Applications; Rajakumar Arul, Shakila Basheer, Asad Abbas, and Ali Kashif Bashir; 8. Deep Learning and IoT in Ophthalmology; Md Enamul Haque and Suzann Pershing; 9. Deep Learning in IoT-Based Healthcare Applications; S.M. Zobaed, Mehedi Hassan, Muhammad Usama Islam, and Md Enamul Haque; 10. Authentication and Access Control for IoT Devices and Its Applications; Ananda Kumar S., Arthi B., Aruna M., Aaisha Makkar, and Uttam Ghosh; 11. Deep Neural Network–Based Security Model for IoT Device Network; Dukka Karun Kumar Reddy, Janmenjoy Nayak, Bighnaraj Naik, and G. M. Sai Pratyusha |
| Beschreibung: | xvii, 248 Seiten Illustrationen, Diagramme 649 grams |
| ISBN: | 9780367457334 9781032064703 |
Internformat
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| 500 | |a 1. Data Caching at Fog Nodes under IoT Networks: Review of Machine Learning Approaches; Riya, Nitin Gupta, and Qin Xin; 2. ECC-Based Privacy-Preserving Mechanisms Using Deep Learning for Industrial IoT: A State-of-the-Art Approaches; R. Sivaranjani, P. Muralidhara Rao, and P. Saraswathi; 3. Contemporary Developments and Technologies in Deep Learning–Based IoT; Prishita Ray, Rajesh Kaluri, Thippa Reddy G., Praveen Kumar Reddy M., and Kuruva Lakshmanna; 4. Deep Learning–Assisted Vehicle Counting for Intersection and Traffic Management in Smart Cities; Guy M. Lingani, Danda B. Rawat, and Moses Garuba; 5. Toward Rapid Development and Deployment of Machine Learning Pipelines across Cloud-Edge; Anirban Bhattacharjee, Yogesh Barve, Shweta Khare, Shunxing Bao, Zhuangwei Kang, Aniruddha Gokhale, and Thomas Damiano; 6. Category Identification Technique by a Semantic Feature Generation Algorithm; Somenath Chakraborty; 7. Role of Deep Learning Algorithms in Securing Internet of Things Applications; Rajakumar Arul, Shakila Basheer, Asad Abbas, and Ali Kashif Bashir; 8. Deep Learning and IoT in Ophthalmology; Md Enamul Haque and Suzann Pershing; 9. Deep Learning in IoT-Based Healthcare Applications; S.M. Zobaed, Mehedi Hassan, Muhammad Usama Islam, and Md Enamul Haque; 10. Authentication and Access Control for IoT Devices and Its Applications; Ananda Kumar S., Arthi B., Aruna M., Aaisha Makkar, and Uttam Ghosh; 11. Deep Neural Network–Based Security Model for IoT Device Network; Dukka Karun Kumar Reddy, Janmenjoy Nayak, Bighnaraj Naik, and G. M. Sai Pratyusha | ||
| 520 | |a This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. | ||
| 520 | |a The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users.FEATURESPromotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructuresAddresses emerging trends and issues on IoT systems and services across various application domainsInvestigates the challenges posed by the implementation of deep learning on IoT networking models and servicesProvides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoTExplores new functions and technologies to provide adaptive services and intelligent applications for different end usersUttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, | ||
| 520 | |a USA.Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia.Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom.Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh | ||
| 700 | 1 | |a Ghosh, Uttam |4 edt | |
| 700 | 1 | |a Alazab, Mamoun |4 edt | |
| 700 | 1 | |a Bashir, Ali Kashif |4 edt | |
| 700 | 1 | |a Pathan, Al-Sakib Khan |0 (DE-588)1122046650 |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-003-03217-5 |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032968470 | ||
Datensatz im Suchindex
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| building | Verbundindex |
| bvnumber | BV047583123 |
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| edition | First edition |
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| id | DE-604.BV047583123 |
| illustrated | Illustrated |
| index_date | 2024-07-03T18:33:47Z |
| indexdate | 2024-07-10T09:15:29Z |
| institution | BVB |
| isbn | 9780367457334 9781032064703 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032968470 |
| oclc_num | 1286857359 |
| open_access_boolean | |
| owner | DE-29T |
| owner_facet | DE-29T |
| physical | xvii, 248 Seiten Illustrationen, Diagramme 649 grams |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | CRC Press, Taylor & Francis Group |
| record_format | marc |
| spelling | Deep learning for internet of things infrastructure edited by Uttam Ghosh, Mamoun Alazab, Ali Kashif Bashir, and Al-Sakib Khan Pathan First edition Boca Raton ; London ; New York CRC Press, Taylor & Francis Group 2022 xvii, 248 Seiten Illustrationen, Diagramme 649 grams txt rdacontent n rdamedia nc rdacarrier 1. Data Caching at Fog Nodes under IoT Networks: Review of Machine Learning Approaches; Riya, Nitin Gupta, and Qin Xin; 2. ECC-Based Privacy-Preserving Mechanisms Using Deep Learning for Industrial IoT: A State-of-the-Art Approaches; R. Sivaranjani, P. Muralidhara Rao, and P. Saraswathi; 3. Contemporary Developments and Technologies in Deep Learning–Based IoT; Prishita Ray, Rajesh Kaluri, Thippa Reddy G., Praveen Kumar Reddy M., and Kuruva Lakshmanna; 4. Deep Learning–Assisted Vehicle Counting for Intersection and Traffic Management in Smart Cities; Guy M. Lingani, Danda B. Rawat, and Moses Garuba; 5. Toward Rapid Development and Deployment of Machine Learning Pipelines across Cloud-Edge; Anirban Bhattacharjee, Yogesh Barve, Shweta Khare, Shunxing Bao, Zhuangwei Kang, Aniruddha Gokhale, and Thomas Damiano; 6. Category Identification Technique by a Semantic Feature Generation Algorithm; Somenath Chakraborty; 7. Role of Deep Learning Algorithms in Securing Internet of Things Applications; Rajakumar Arul, Shakila Basheer, Asad Abbas, and Ali Kashif Bashir; 8. Deep Learning and IoT in Ophthalmology; Md Enamul Haque and Suzann Pershing; 9. Deep Learning in IoT-Based Healthcare Applications; S.M. Zobaed, Mehedi Hassan, Muhammad Usama Islam, and Md Enamul Haque; 10. Authentication and Access Control for IoT Devices and Its Applications; Ananda Kumar S., Arthi B., Aruna M., Aaisha Makkar, and Uttam Ghosh; 11. Deep Neural Network–Based Security Model for IoT Device Network; Dukka Karun Kumar Reddy, Janmenjoy Nayak, Bighnaraj Naik, and G. M. Sai Pratyusha This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users.FEATURESPromotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructuresAddresses emerging trends and issues on IoT systems and services across various application domainsInvestigates the challenges posed by the implementation of deep learning on IoT networking models and servicesProvides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoTExplores new functions and technologies to provide adaptive services and intelligent applications for different end usersUttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia.Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom.Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh Ghosh, Uttam edt Alazab, Mamoun edt Bashir, Ali Kashif edt Pathan, Al-Sakib Khan (DE-588)1122046650 edt Erscheint auch als Online-Ausgabe 978-1-003-03217-5 |
| spellingShingle | Deep learning for internet of things infrastructure |
| title | Deep learning for internet of things infrastructure |
| title_auth | Deep learning for internet of things infrastructure |
| title_exact_search | Deep learning for internet of things infrastructure |
| title_exact_search_txtP | Deep learning for internet of things infrastructure |
| title_full | Deep learning for internet of things infrastructure edited by Uttam Ghosh, Mamoun Alazab, Ali Kashif Bashir, and Al-Sakib Khan Pathan |
| title_fullStr | Deep learning for internet of things infrastructure edited by Uttam Ghosh, Mamoun Alazab, Ali Kashif Bashir, and Al-Sakib Khan Pathan |
| title_full_unstemmed | Deep learning for internet of things infrastructure edited by Uttam Ghosh, Mamoun Alazab, Ali Kashif Bashir, and Al-Sakib Khan Pathan |
| title_short | Deep learning for internet of things infrastructure |
| title_sort | deep learning for internet of things infrastructure |
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