ADVANCEMENT OF DATA PROCESSING METHODS FOR ARTIFICIAL AND COMPUTING INTELLIGENCE

Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proved. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling for better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behavior from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.

This book aims to emphasis the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to Data Science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, Engineering, and Data Science, this cutting-edge technology is ready to support us.

Chapters relevant to the topic are invited, including but not limited to following:

Section 1: Trends in Data Processing & Analytics

Chapter 1: Data analysis and interpretation

Chapter 2: Big data analytics in cloud

Chapter 3: AIDA- Artificial intelligence for data analytics

Chapter 4: In-memory and predictive analytics

Section 2: Advance implementation of Artificial Intelligence & Data Analytics

Chapter 5: Artificial Intelligence and Data Science in various domains

Chapter 6: Enterprise AI- Data analytics, data science and ML

Chapter 7: Real-time implementation of AI in automation

Chapter 8: Algorithms for Self-configuration and self-optimization

Section 3: Data Science Applications

Chapter 9: Complex Data Science Applications in Analytics Engineering.

Chapter 10: Data Processing applications in Small Business Enterprises (SMEs)

Chapter 11: Data Analytics in Central and State Governments, Public Sector and Society in General

Chapter 12: Real-life Case Studies of Value Creation through Big Data Processing

Abstract Submission : 20th July 2022

Abstract Acceptance : 30th July 2022

Full Chapter Submission : 30th August 2022

First Decision/Corrections : 15th Sept. 2022

Final Chapter Due : 10th Oct. 2022

Submission Process

All the contributors are invited to submit their proposal in file specifying:

1. Proposed/Tentative Title of the Chapter

2. List of contributing co-authors (Specify affiliation for each coauthor)

3. Abstract- 300 words

4. 6 Keywords

5. Table of Contents/Tentative Structure of the Chapter.

The Submission for the Proposal is welcome till 20th July 2022 via following EasyChair link.

https://easychair.org/conferences/?conf=dataandai2022

Inquires can be forwarded to:

Dr. Seema Rawat | Email: srawat1@amity.edu; Mobile: +91-9958975227

Dr V. Ajantha Devi | Email: ap3solutionsresearch@gmail.com ; Mobile: +91-9444284265

Dr. Praveen Kumar | Email: Pkumar3@amity.edu ; Mobile: +91-9911181619