Embracing the Digital Horizon

Advanced AI and Intelligent Systems for Transformative Commerce and Management

D. Arul Pon Daniel, T. Rajasanthosh Kumar, Satya Prakash Yadav

• Publisher: Bentham Science Publishers
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9798898814441
• Subtopic: Information Technology
• Index: Computer Science

Embracing the Digital Horizon is a comprehensive collection of cutting-edge research, anchored in multidisciplinary innovation, that captures the rapid evolution of artificial intelligence, intelligent systems, and advanced engineering technologies shaping modern commerce and management.

With rigorously peer-reviewed chapters, the book covers embedded hardware–software co-design, energy-efficient and sustainable architectures, intelligent sensing, real-time optimisation, advanced control systems, with additional focus on cyber-physical integration, IoT-enabled automation, machine-learning-driven decision frameworks, and robotics applications. Each contribution combines strong theoretical foundations with experimental validation, analytical modelling, comparative evaluations, and real-world case studies, effectively bridging academic research and industry practice.

With its emphasis on scalable, sustainable, and intelligent automation, the book offers valuable insights into next-generation digital ecosystems and the technologies driving transformation across engineering, commerce, and management.


Key Features:

-Multidisciplinary coverage of AI, intelligent systems, automation, and embedded technologies

-Application-driven research with real-world engineering and industrial case studies

-Comparative evaluation of modern computational, control, and optimisation methods

-Integration of AI, IoT, cyber-physical systems, and robotics for smart environments

-Focus on scalable, sustainable, and future-ready intelligent automation strategies

-Identification of emerging research challenges and future innovation pathways

Table of contents

• Welcome
• Table of Content
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• Preface
• List of Contributors
• An Experimental Framework for Optimising the AI-Driven Supply Management Solution
• AIML-Based Automated HR Management System
• Implementing a Data Mining-Based Marketing System
• Development of a Chatbot Supporting System to Support the Payment Application for Customer Support
• Implementation of Digitalized HR Process by AI and IoT
• An Efficient Intrusion Detection Model with Novel Machine Learning Stacking Ensemble Techniques
• Machine Learning (ML) is Used in the Banking Industry to make Decisions on Loan Approval
• The Impact of 3D Printing and Machine Learning in the Manufacturing Industry
• The Problems of Cashless Transactions Among the Professionals in the Kanyakumari District
• Intelligent Additive Manufacturing is Unleashing the Power of 3D Printing with Machine Learning
• AI-Based Data-Based Decision-Making System to Optimize Business Performance
• Al Effect on Employment Sustainability
• Long and Short Implications of ChatGPT and Generative AI on the Labour Market View
• IoT-Based Indoor Navigation System: Emphasizing Data-Driven Insights for Enhanced User Experience
• Integration of Generative AI and Computer Vision in the Retail Market to Reshape the Industry Dynamics
• A Novel Machine Learning-based Web Application for Disease Detection
• A Study on Analyzing the Impact of the Internet on Managing Organizations- Special Reference to the Education Sector
• A Hybrid Model for Multilevel Thresholding Segmentation for Detecting Leaf Disease in Groundnut Plants
• Transformer-based U-net Model for Segmentation of Paddy Leaf Disease
• A Study on Factors Influencing Consumer Buying Behaviour on Health Drinks with Special Reference to Palakkad District
• Machine Learning Model: Operating Machinery Status for Fault Prediction
• Development of Forecasting Models to Predict the Power Consumption of Charging Stations: IoT
• IoT-based Detection System to Support Electric Vehicle Charging Stations
• Diabetes Prediction Using Supervised and Unsupervised Machine Learning
• Evaluating Ensembles of Machine Learning Models for the Prediction of Smartphone Addiction
• Deep Learning-Based Emotion Recognition System with Depression Detection Capability
• Tackling Environment Unpredictability: A Sensor-Based Approach to Temperature and Humidity Control
• Evaluating Ensemble Machine Learning Approaches for Accurate Flight Pricing Predictions
• Facial Biometrics for Seamless Attendance Tracking in Educational Institutions