Artificial Intelligence and Knowledge Processing: Methods and Applications

✍ Scribed by Hemachandran K., Raul V. Rodriguez, Umashankar Subramaniam, Valentina Emilia Balas

• Publisher: Bentham Science Publishers
• Year: 2023
• Tongue: English
• Leaves: 241
• Category: Library

✦ Synopsis

Artificial Intelligence and Knowledge Processing: Methods and Applications demonstrates the transformative power of Artificial Intelligence (AI) in our lives. The book is a collection of 14 edited reviews that cover a wide range of topics showcasing the application of AI and machine learning to create knowledge, and facilitate different processes.
The book starts by illuminating how AI is employed in robotics, IoT, marketing, and operations. It showcases how AI extracts insights from big data, optimizes museum management, and empowers automated garden path planning using reinforcement learning. The book also explores how AI can be used to predict heart disease using artificial neural networks. Furthermore, the book underscores how AI predicts crop suitability, manages crop systems, and can even help to detect violence in using computer vision. Chapters highlight specific techniques or systems such as recommendation systems and reinforcement learning where appropriate.
Key Features
· Showcases a wide range of AI applications
· Bridges theory and practice with real-word insights
· Uses accessible language to explain complex AI concepts
· Includes references for advanced readers
This book is intended as a guide for a broad range of readers who want to learn about AI applications and the profound influence it has on our lives.
Readership
General readers, students, researchers and entrepreneurs interested in AI use-cases and applications."

✦ Table of Contents

Welcome
Table of Content
Title
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
List of Contributors
Artificial General Intelligence; Pragmatism or an Antithesis?
Abstract
INTRODUCTION
Elucidation of Echelons, the Hierarchy
Ancient Mythological Milieu
Perplexity of Technophobia26
Incredulous of Celluloid Apocryphal
Chaotic Proclamations of Digital Prowess
Gregarious and Pervasive Transgenic Consciousness
Apperceptive Terrestrial Systematization
Conclusion
Candid Exhortation
CONSENT FOR PUBLICATON
References
Applications of Artificial Intelligence in Robotics
Abstract
INTRODUCTION
DIFFERENCE BETWEEN AI AND ROBOTICS
PERCEPTION AND INTELLIGENT ROBOTS
AI AND ADVANCED ROBOTICS TECHNIQUES
Will Robots Replace the Human Workforce?
Robots And Our Developing Environment
AI, Robots Vs Humans
ROBOTICS & AI FUTURE OF HUMANITY?
A. Robots in School
B. Robots in Health Care
C. Robots to Analyze Emotions
D. Robots in Industries
E. Robots in the Aviation Industry
F. Robotics in Defense Sectors
G. Robots in the Mining Industry
LIMITATIONS OF AI
CONCLUSION
CONSENT FOR PUBLICATON
ACKNOWLEDGEMENTS
REFERENCES
Smart Regime with IoT application using AI
Abstract
INTRODUCTION
LAYERS OF IoT
PRIMARILY WE ARE USING THESE TECHNOLOGIES IN: WEARABLES
SMART HOMES AND BUILDINGS
Self-Driving Vehicles
Security Devices
Traffic Control
Face, Age & Height Detection System
IoT in the Healthcare Industry
IoT in the Agriculture Sector
Smart City
IoT Combination of Data Science and AI
The Data Mining Process in IoT
AI Libraries and Their Role in IoT Applications
Keras
TensorFlow
NumPy
MATPLOTLIB
INNOVATIVE MILESTONES CAN BE ACHIEVED IN IOT USING AI
CONCLUSION
CONSENT FOR PUBLICATON
ACKNOWLEDGEMENTS
REFERENCES
Artificial Intelligence in Marketing and Operations
Abstract
INTRODUCTION
Application of Artificial Intelligence in Marketing
Impact of Artificial Intelligence on Customers
Impact of Artificial Intelligence on Marketing
Application of Artificial Intelligence in Operations
Application Of Market Basket Analysis
Architecture
BASICS OF MARKET BASKET ANALYSIS
Support
Confidence
Market Basket Analysis Applications
Benefits Of Market Basket Analysis
CONCLUSION
CONSENT FOR PUBLICATON
ACKNOWLEDGEMENTS
REFERENCES
Data Insights by Using Data Visualization and Exploration
Abstract
INTRODUCTION
Visualization as a Tool for Insight Discovery
How to Visualize Data?
Transform the Data
Tools
Why a Tool Like Data Visualization is so Effective?
Data Visualization and Big Data
Characteristics of the Big Data
Architecture
The following workloads are among those that big data solutions frequently include
Big Data Architectures Should be taken into Consideration
Main Advantages and Disadvantages of Big Data
Advantages of Big Data
Disadvantages of Big Data
Big Data and Data Visualization Relationship
While big data visualization has its benefits, there are also some serious disadvantages for enterprises. The following are their names
Data Exploration
CONCLUSION
Data Visualization's Future
CONSENT FOR PUBLICATON
ACKNOWLEDGEMENTS
REFERENCES
Application of Computer Vision to Laboratory Experiments
Abstract
Introduction: Background
The Coupled Pendulum Experiment
The Flywheel Experiment
CONCLUSION
References:
Violence Detection for Smart Cities using Computer Vision
Abstract
INTRODUCTION
LITERATURE SURVEY
METHODOLOGY
Feature Extraction
Transfer Learning
Binary Classification using LSTM
MODEL TRAINING AND OPTIMIZATION
RESULTS AND DISCUSSION
CONCLUSION
REFERENCES
A Big Data Analytics Architecture Framework for Oilseeds and Textile Industry Production and International Trade for Sub-Saharan Africa (SSA)
Abstract
INTRODUCTION
Background
STATEMENT OF THE PROBLEM
Research Aim
Research Objectives
Research Questions
Literature Survey
OILSEEDS AND TEXTILE PRODUCTION COMPETITIVE CHALLENGES IN SSA
• A Lack of Demand from the Apparel Industry
• Lack of Understanding of Local and Global Market Opportunities
• Insufficient Availability of Dependable Electricity at Affordable Prices
• A Lack of Infrastructure for the Treatment of Waste Water and Clean Water
• A Lack of Competitive Access to Capital
• Lack of Professional or Trained Labor
CONCEPTUAL FRAMEWORK FOR ADOPTION OF BIG DATA ANALYTICS
Methodology
Results and Discussion
Critical Challenges around the Applications of Big Data Analytics in the Oilseeds and Textile Industries
IMPLEMENTATION OF AN AI CHATBOT AND E-COMMERCE
DATA ANALYSIS OF OILSEEDS PRODUCTION IN SSA
Soybean
Groundnuts
Cowpea
Shea Butter
Limited Availability of Better Seeds
A Lack of Agriculture Equipment
Poor Soil Fertility
Input Market Restrictions
Market Restrictions
Low Acceptance Rates for New Technologies
TEXTILE PRODUCTION CAPACITY AND COMPETITIVE FACTORS
Conclusion and Recommendations on the Cotton and Textile Industry in SSA
Big Data Analytics Framework Model for Oilseeds and Textile Production in SSA
The Big Data Framework's Structure
CONCLUSION
REFERENCES
A Design of Lighting and Cooling System for Museum and Heritage Sites
Abstract
INTRODUCTION
Methodology
Pre-Scanning of LMS
Results and Discussion: Lighting Module Design
Cooling Effect Study by Temperature Monitoring Vs Time and Distance
Proposed Cooling Effect Enhancement System Design
CONCLUDING REMARKS
REFERENCES
Predict Network Intruder Using Machine Learning Model and Classification
Abstract
INTRODUCTION
RELEVANT RESEARCH
METHODOLOGY
Dataset Specification
Experimentalism
Information-Gain
Tools Used for Analysis
EXPERIMENTALISM
Data Preparation Process
Feature Selection Based On IG
Experimental Result
Experimental Analysis
CONCLUSION
REFERENCES
Machine Learning Based Crop Recommendation System
Abstract
INTRODUCTION
Effect of Soil Types on Crop Production
Effect of Rainfall on Crop Production
Role of Temperature in Crop Production
Crop Recommendation System
THEORETICAL BACKGROUND
Overview of Machine Learning
SciKit-learn
Dataset
Data Pre-processing
Streamlit
MACHINE LEARNING ALGORITHMS
Logistic Regression
Decision Tree
k-nearest Neighbours (KNN) Algorithm
Naive Bayes Algorithm
IMPLEMENTATION
Data Pre-processing
Applying Machine Learning Algorithms
Application
RESULTS AND DISCUSSION
CONCLUSION
REFERENCES
Artificial Neural Networks based Distributed Approach for Heart Disease Prediction
Abstract
INTRODUCTION
RELATED WORK
OVERVIEW OF THE MODEL
EXPERIMENTAL SETUP
RESULTS
CONCLUSION
REFERENCES
Reinforcement Learning Based Automated Path Planning in Garden Environment using Depth - RAPiG-D
Abstract
INTRODUCTION
RELATED WORKS
METHODOLOGY
RESULTS AND DISCUSSION
Software Implementation
Hardware Implementation
CONCLUSION
FUTURE WORKS
REFERENCES
Analysis of Human Gait by Selecting Anthropometric Data Based on Machine Learning Regression Approach
Abstract
INTRODUCTION
METHODS AND MATERIALS
MULTI LINK SEGMENT MODEL
SIMULATION OF HUMAN GAIT
REGRESSION FOR ANTHROPOMETRIC MEASUREMENTS
RESULTS AND DISCUSSION
CONCLUSION
ACKNOWLEDGEMENTS
REFERENCES