Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems
Herausgeber: Singla, Anshu; Hsiung, Pao-Ann; Tanwar, Sarvesh
Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems
Herausgeber: Singla, Anshu; Hsiung, Pao-Ann; Tanwar, Sarvesh
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This book comprehensively discusses the role of cloud computing in artificial intelligence-based data-driven systems, and hybrid cloud computing for large data-driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data.
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This book comprehensively discusses the role of cloud computing in artificial intelligence-based data-driven systems, and hybrid cloud computing for large data-driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 284
- Erscheinungstermin: 31. Juli 2024
- Englisch
- Abmessung: 234mm x 156mm x 18mm
- Gewicht: 590g
- ISBN-13: 9781032548173
- ISBN-10: 1032548177
- Artikelnr.: 70148732
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 284
- Erscheinungstermin: 31. Juli 2024
- Englisch
- Abmessung: 234mm x 156mm x 18mm
- Gewicht: 590g
- ISBN-13: 9781032548173
- ISBN-10: 1032548177
- Artikelnr.: 70148732
Dr. Anshu Singla has a PhD in Computer Science and Engineering with 17 years of experience in research, training, and academics. Currently, she is a Professor with Chitkara University, Punjab, India. Her areas of expertise are Machine Learning, Soft Computing, Pattern Recognition, Image Processing, and Artificial Intelligence. She has 45 publications, including 13 SCI publications. She has been granted six patents and filed eight patents in the relevant field. She has guided four ME research scholars and five PhD scholars. Currently, she is supervising three PhD scholars in the areas of Emotion recognition, Color blindness, Object detection, Crop yield prediction, and Satellite imaging. Dr. Sarvesh Tanwar is an Associate Professor at the Amity Institute of Information Technology (AIIT), Amity University, Noida. She is the head of AUN Blockchain & Data Security Research Lab. She completed her MTech (CSE) degree from MMU, Mullana and PhD (CSE) from Mody University, Laxmangarh, Rajasthan. She has more than 15 years of teaching and research experience. Her areas of research include Public Key Infrastructure (PKI), Cryptography, Blockchain, and Cyber Security. She has published more than 100 research papers in International Journals and Conferences. She is currently guiding six PhD scholars and has guided five MTech research scholars. She has filed 19 patents and two copyrights in the relevant field. She is a Senior Member of IEEE, Life Member of the Cryptology Research Society of India (CRSI), Indian Institute of Statistics, Kolkata, India, and member of the International Association of Computer Science and Information Technology (IACSIT), Singapore. She is a reviewer of the Journal of Cases on Information Technology (JCIT), IEEE Access, MDPI, Asian Research Journal of Mathematics, and Inderscience. She is a member of the editorial reviewer board of IJISP, IGI Global, USA. She is a member of the Editorial Board in the International Journal of Research in Science and Technology (IJRSTO), Ghaziabad, UP, Advances in Science, Technology and Engineering Systems Journal (ASTES), USA, and IAENG. She received the Teacher's Excellence Award for being the most committed, emerging leader, and collaborative in April 2019 (Chitkara University, Punjab). PaöAnn Hsiung earned a BS degree in Mathematics and a PhD degree in Electrical Engineering from the National Taiwan University, Taipei, Taiwan, ROC, in 1991 and 1996, respectively. From 1993 to 1996, he was a teaching assistant and system administrator in the Department of Mathematics, National Taiwan University. From 1996 to 2000, he was a postdoctoral researcher at the Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC. From February 2001 to July 2002, he was an assistant professor, and from August 2002 to July 2007, he was an associate professor in the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, ROC. Since August 2007, he has been a full professor. He was the division chief of Information Management at the Computer Center from May 2008 to July 2011. He was the department chair from August 2011 to January 2016. Then, he held the post of the Dean of International Affairs starting from February 2016 until now. Dr. Hsiung has published more than 260 papers in top international journals and conferences. He was the recipient of the 2001 ACM Taipei Chapter KuöTing Li Young Researcher for his significant contributions to design automation of electronic systems. This award is given annually to only one person under the age of 36 who is conducting research in Taiwan. Dr. Hsiung was also a recipient of the 2004 Young Scholar Research Award given by National Chung Cheng University, which is given to five young faculty members per year. He was awarded the 2010 Outstanding Research Award by National Chung Cheng University (only three faculty members were awarded in 2010). He has been included in several professional listings such as Marquis' Who's Who in the World (starting from the 17th Millennium Edition, 2000), Marquis' Who's Who in Asia (starting from the 1st edition, 2007), Outstanding People of the 20th Century (2nd edition, 2000), 2000 Outstanding People of the 21st Century (1st edition, 2008), by International Biographical Centre, Cambridge, England, Rifacimento International's Admirable Asian Achievers (2006), Afro/ Asian Who's Who, Vol. I (2007), and Asia/Pacific Who's Who, Vol. VII, (2007), Who's Who in Formal Methods, ACM SIGDA's design automation professionals.
1. Artificial Intelligence & IoT: Challenges and Future Directions for Data
Driven System. 2. Cloud Computing in AI-based Data-Driven Systems:
Opportunities and Challenges. 3. Study on Detection of Potato Diseases
using Deep Learning Network and Image Segmentation. 4. Leveraging Cloud
Computing for Efficient AI-Based Data-Driven Systems. 5. Analyzing and
contrasting the outcomes of performance-based plagiarism detection methods.
6. Machine Learning Algorithms for Data Driven Systems in IoT. 7. Improving
Classification Accuracy of Diabetes Mellitus Prediction using Ensemble
Techniques. 8. Machine learning Models for IoT Botnet attack Detection. 9.
Blockchain-based identity authentication for Internet of Things systems: A
comprehensive survey. 10. Connected Healthcare: The Impact of Internet of
Things on Medical Services: Merits, Limitations, Future Insights, Case
Studies, and Open Research Questions. 11. IoT-Enabled Smart Farming Systems
using Data Analytics and Machine Learning: An empirical study of livestock
monitoring. 12. Exploring the Performance Improvement and Skill Set
Transformations in Sheet Metal Operations through Digital Technology. 13.
Crowd-Sourced Based Emergency Response on the Internet of Vehicles (IOV):
Harnessing Strengths and Limitations.
Driven System. 2. Cloud Computing in AI-based Data-Driven Systems:
Opportunities and Challenges. 3. Study on Detection of Potato Diseases
using Deep Learning Network and Image Segmentation. 4. Leveraging Cloud
Computing for Efficient AI-Based Data-Driven Systems. 5. Analyzing and
contrasting the outcomes of performance-based plagiarism detection methods.
6. Machine Learning Algorithms for Data Driven Systems in IoT. 7. Improving
Classification Accuracy of Diabetes Mellitus Prediction using Ensemble
Techniques. 8. Machine learning Models for IoT Botnet attack Detection. 9.
Blockchain-based identity authentication for Internet of Things systems: A
comprehensive survey. 10. Connected Healthcare: The Impact of Internet of
Things on Medical Services: Merits, Limitations, Future Insights, Case
Studies, and Open Research Questions. 11. IoT-Enabled Smart Farming Systems
using Data Analytics and Machine Learning: An empirical study of livestock
monitoring. 12. Exploring the Performance Improvement and Skill Set
Transformations in Sheet Metal Operations through Digital Technology. 13.
Crowd-Sourced Based Emergency Response on the Internet of Vehicles (IOV):
Harnessing Strengths and Limitations.
1. Artificial Intelligence & IoT: Challenges and Future Directions for Data
Driven System. 2. Cloud Computing in AI-based Data-Driven Systems:
Opportunities and Challenges. 3. Study on Detection of Potato Diseases
using Deep Learning Network and Image Segmentation. 4. Leveraging Cloud
Computing for Efficient AI-Based Data-Driven Systems. 5. Analyzing and
contrasting the outcomes of performance-based plagiarism detection methods.
6. Machine Learning Algorithms for Data Driven Systems in IoT. 7. Improving
Classification Accuracy of Diabetes Mellitus Prediction using Ensemble
Techniques. 8. Machine learning Models for IoT Botnet attack Detection. 9.
Blockchain-based identity authentication for Internet of Things systems: A
comprehensive survey. 10. Connected Healthcare: The Impact of Internet of
Things on Medical Services: Merits, Limitations, Future Insights, Case
Studies, and Open Research Questions. 11. IoT-Enabled Smart Farming Systems
using Data Analytics and Machine Learning: An empirical study of livestock
monitoring. 12. Exploring the Performance Improvement and Skill Set
Transformations in Sheet Metal Operations through Digital Technology. 13.
Crowd-Sourced Based Emergency Response on the Internet of Vehicles (IOV):
Harnessing Strengths and Limitations.
Driven System. 2. Cloud Computing in AI-based Data-Driven Systems:
Opportunities and Challenges. 3. Study on Detection of Potato Diseases
using Deep Learning Network and Image Segmentation. 4. Leveraging Cloud
Computing for Efficient AI-Based Data-Driven Systems. 5. Analyzing and
contrasting the outcomes of performance-based plagiarism detection methods.
6. Machine Learning Algorithms for Data Driven Systems in IoT. 7. Improving
Classification Accuracy of Diabetes Mellitus Prediction using Ensemble
Techniques. 8. Machine learning Models for IoT Botnet attack Detection. 9.
Blockchain-based identity authentication for Internet of Things systems: A
comprehensive survey. 10. Connected Healthcare: The Impact of Internet of
Things on Medical Services: Merits, Limitations, Future Insights, Case
Studies, and Open Research Questions. 11. IoT-Enabled Smart Farming Systems
using Data Analytics and Machine Learning: An empirical study of livestock
monitoring. 12. Exploring the Performance Improvement and Skill Set
Transformations in Sheet Metal Operations through Digital Technology. 13.
Crowd-Sourced Based Emergency Response on the Internet of Vehicles (IOV):
Harnessing Strengths and Limitations.