![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Advances in Computers, Volume 117
Volume 117, 2020
- Pethuru Raj, Jenn-Wei Lin:
Chapter One - Stepping into the digitally instrumented and interconnected era. 1-34 - Preetha Evangeline
, P. Anandhakumar:
Chapter Two - Digital twin technology for "smart manufacturing". 35-49 - J. Pushpa, S. A. Kalyani:
Chapter Three - The fog computing/edge computing to leverage Digital Twin. 51-77 - Peter Augustine
:
Chapter Four - The industry use cases for the Digital Twin idea. 79-105 - Vidya Hungud, Senthil Kumar Arunachalam:
Chapter Five - Digital twin: Empowering edge devices to be intelligent. 107-127 - Sathyan Munirathinam:
Chapter Six - Industry 4.0: Industrial Internet of Things (IIOT). 129-164 - Ranganathan Indrakumari, Thangamuthu Poongodi, Palanimuthu Suresh, Balamurugan Balusamy
:
Chapter Seven - The growing role of integrated and insightful big and real-time data analytics platforms. 165-186 - Chetan Shetty, B. J. Sowmya, S. Seema, K. G. Srinivasa
:
Chapter Eight - Air pollution control model using machine learning and IoT techniques. 187-218 - Janet Barnabas
, Pethuru Raj:
Chapter Nine - The human body: A digital twin of the cyber physical systems. 219-246 - Nagarajan Susila, Anand Sruthi, Sakthivel Usha:
Chapter Ten - Impact of cloud security in digital twin. 247-263 - D. Sudaroli Vijayakumar
:
Chapter Eleven - Digital twin in consumer choice modeling. 265-284 - Pethuru Raj, Chellammal Surianarayanan
:
Chapter Twelve - Digital twin: The industry use cases. 285-320 - Ambika Paranthaman
:
Chapter Thirteen - Machine learning and deep learning algorithms on the Industrial Internet of Things (IIoT). 321-338 - S. Abirami, P. Chitra:
Chapter Fourteen - Energy-efficient edge based real-time healthcare support system. 339-368
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.