Artificial Intelligence, Machine Learning and IoT for Smart Business Management

1. Auflage 2025
ISBN: 978-1-032-91200-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 250 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Artificial Intelligence, Machine Learning, Data Analytics and Automation for Business Management

This book investigates the transformative impact of AI, ML, data analytics, and IoT on modern business, emphasizing their roles in strategic growth, operational efficiency, and data-driven decision-making. Through real-world case studies, strategic frameworks, and ethical considerations, it offers actionable insights for integrating these technologies. Covering emerging trends and responsible adoption, this book is an essential resource for professionals navigating digital transformation and achieving sustainable success.

- Explore the application of AI, ML, data analytics, and IoT within business contexts, emphasizing their roles in strategic growth, operational efficiency, and decision-making.

- Provides methodologies for maximizing ROI, mitigating risks, and fostering innovation.

- Explores predictive modeling, market segmentation, and business intelligence for competitive advantage.

- Examines cutting-edge automation technologies that optimize processes and enhance workforce efficiency.

- Investigates neuro-fuzzy systems in financial forecasting to improve predictive accuracy and decision-making.

This book serves as a practical guide for professionals and as a reference for scholars, researchers, and students of computer science and business management.

Zielgruppe

Academic

Autoren/Hrsg.

Jain, Ankush

Jain, Garima

Balusamy, Balamurugan

Grover, Veena

Tomar, Praveen

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Webprogrammierung
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik

Inhaltsverzeichnis

- Evolution of AI, ML, and IoT in Business Management
Poornima Tyagi, Shiv Narain Gupta, Divya Sahu, Mohd Firoz Waris, and Parvendra Kumar

- Strategic Implementation of AI for Business Advancement
Priti Rai and Palanivel Rathinasabapathi Velmurugan

- ML Techniques for Business Intelligence and Decision-Making
Vijay Anand Rajasekaran, Magesh Gopu, Madala Guru Brahmam, and Veena Grover

- Operational Excellence through AI, ML, and IoT
A. Anitha, K. Anitha, Kashish Bhasin, Aditya Singh, and Balakrishnan Kamaraj

- Technical Analysis for Traders: Stock Price Prediction
Purnima Pal, Harshit Thakur, Meghali Das, Nisha, and Manju Nandal

- Future Trends and Ethical Considerations in AI, ML, and IoT
Sarabjeet Kaur, Swarnima, Purnima Pal, and Nidhi Sharma

- Voice Assisted Chat Bots in Enhancing CRM in Modern Marketing for Small Businesses
Aditi Srivastava, Ajay Singh, and Brij Mohan Singh

- IoT Applications in Business Operations
Taher Alkhalaf, Omar Durrah, and Monir Alkhalaf

- Robotic Process Automation: Streamlining Business Processes for Operational Excellence
Magesh Sankar, Vijayalakshmi Sivaramakrishnan, Palamadai Subramanian Rajakumar, S. Geetha, and R. Manikandan

- Intelligent Forecasting Models Based on Neural Systems for Smart Business Management
Hina Riaz and Mohan Prasad Sharma

- Customer Churn Prediction Using Machine Learning
Meghali Das, Purnima Pal, and Garima Srivastava

- Intelligent Techniques: Fuzzy Logic and Computational Techniques
Swarnima and Bhawna Khullar

Über Autor(innen)

Garima Jain is an Assistant Professor and Deputy Head in the Department of Computer Science and Buisness System at Noida Institute of Engineering and Technology, Greater Noida, India. She completed her M.Tech. from Galgotias University, Greater Noida, in 2017. She is pursuing her Ph.D. from Dayalbagh University on Resource Provisioning in Cloud and Edge Computing environment.

Ankush Jain is an Assistant Professor in Department of Computer Science and Engineering, Netaji Subhas University of Technology (Formerly known as NSIT), Main Campus, Dwarka, New Delhi. He completed his Ph.D. and M.Tech. from ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior. He received his B. Tech. degree in Computer Science and Engineering from Rajasthan Technical University, Kota.

Veena Grover is currently working as Professor in Department of Management at Noida Institute of Engineering & Technology, Greater Noida, UP, India. Prior to this, she has been working as Professor in School of Business, Galgotias University, she has more than 21 years of teaching experience in educational institutions of repute like Lingaya’s University, New Delhi Institute of Management, University of Delhi, DAV Institute of Management etc.

Balamurugan Balusamy is presently working as an Associate Dean (Student engagement), Shiv Nadar University. Delhi-National Capital Region (NCR) He has also served up to the position of Associate Professor in his stint of 14 years of experience with VIT University, Vellore. His research focuses on Blockchain and IoT.

Praveen Tomar is a passionate civil servant, researcher and technology enthusiast. He has over 23 years of experience in IT transformation, Data, AI and automation, with a Six Sigma Black Belt certification and multiple publications on low-code digital automation. As the Head of Process Digitisation (Data and AI) at Ofgem, he leads a team of talented professionals who are passionate about enhancing public service delivery and outcomes by harnessing the power of data and automation, while respecting human dignity and values.