Artificial Intelligence and Knowledge Processing: Methods and Applications Hemachandran K.

Format:

Book

Author/Creator:

K., Hemachandran, Author.

Contributor:

K., Hemachandran, editor.

Language:

English

Subjects (All):

Artificial intelligence--Data processing.

Artificial intelligence.

Decision making--Data processing.

Decision making.

Physical Description:

1 online resource (241 pages)

Edition:

First edition.

Place of Publication:

Singapore : Bentham Science Publishers Pte. Ltd., [2023]

Summary:

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.".

Contents:

Cover

Title

Copyright

End User License Agreement

Contents

Foreword

Preface

List of Contributors

Artificial General Intelligence

Pragmatism or an Antithesis?

K. Ravi Kumar Reddy1,*, K. Kailash2 and Y. Vani3

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

NOTES

CONSENT FOR PUBLICATON

REFERENCES

Applications of Artificial Intelligence in Robotics

Pingili Sravya1,*, Hemachandran K.2 and Ezendu Ariwa3

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 &amp

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

ACKNOWLEDGEMENTS

Smart Regime with IoT application using AI

Sri Rama Sai Pavan Kumar1,*, Guda Vineeth Reddy1, Sailaja Maggidi1 and Rajesh Kumar K. V.1

LAYERS OF IOT

PRIMARILY WE ARE USING THESE TECHNOLOGIES IN: WEARABLES

SMART HOMES AND BUILDINGS

Self-Driving Vehicles

Security Devices

Traffic Control

Face, Age &amp

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

Artificial Intelligence in Marketing and Operations

Gaddam Venkat Shobika1,*, Sourav Chakraborty1, Varadharaja Krishna1, Dibya Nandan Mishra1 and Pranay Kumar2

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

Data Insights by Using Data Visualization and Exploration

Choppala Swathi Priya1,*, Sai Santosh Potnuru1, Ishank Jha1, Hemachandran K.2 and Chinna Swamy Dudekula3

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

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

Data Visualization's Future

REFERENCES.

Application of Computer Vision to Laboratory Experiments

P.K. Thiruvikraman1,*, Devendra Dheeraj Gupta Sanagapalli1 and Simran Sahni1

INTRODUCTION: BACKGROUND

THE COUPLED PENDULUM EXPERIMENT

THE FLYWHEEL EXPERIMENT

REFERENCES:

Violence Detection for Smart Cities using Computer Vision

Jyoti Madake1,*, Shripad Bhatlawande1, Abhishek Rajput1, Aditya Rasal1, Sambodhi Umare1, Varun Shelke1 and Swati Shilaskar1

LITERATURE SURVEY

METHODOLOGY

Feature Extraction

Transfer Learning

Binary Classification using LSTM

MODEL TRAINING AND OPTIMIZATION

RESULTS AND DISCUSSION

A Big Data Analytics Architecture Framework for Oilseeds and Textile Industry Production and International Trade for Sub-Saharan Africa (SSA)

Gabriel Kabanda1,*

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

A Design of Lighting and Cooling System for Museum and Heritage Sites

Amrapali Nimsarkar1, Piyush Kokate2,*, Mamta Tembhare3 and Harikumar Naidu1

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

Predict Network Intruder Using Machine Learning Model and Classification

Chithik Raja1,*, Hemachandran K.2, V. Devarajan1 and K. Jarina Begum3

RELEVANT RESEARCH

Dataset Specification

Experimentalism

Information-Gain

Tools Used for Analysis

EXPERIMENTALISM

Data Preparation Process

Feature Selection Based On IG

Experimental Result

Experimental Analysis

Machine Learning Based Crop Recommendation System

Keerti Adapa1 and Sudheer Hanumanthakari1,*

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

Applying Machine Learning Algorithms

Application

CONCLUSION.

REFERENCES

Artificial Neural Networks based Distributed Approach for Heart Disease Prediction

Thakur Santosh1,*, Hemachandran K.4, Sandip K. Chourasiya3, Prathyusha Pujari2, K. Vishal2 and B. R. S. S. Sowjanya2

RELATED WORK

OVERVIEW OF THE MODEL

EXPERIMENTAL SETUP

RESULTS

Reinforcement Learning Based Automated Path Planning in Garden Environment using Depth - RAPiG-D

S. Sathiya Murthi1,*, Pranav Balakrishnan1, C. Roshan Abraham1 and V. Sathiesh Kumar1

RELATED WORKS

Software Implementation

Hardware Implementation

FUTURE WORKS

Analysis of Human Gait by Selecting Anthropometric Data Based on Machine Learning Regression Approach

Nitesh Singh Malan1,* and Mukul Kumar Gupta1,*

METHODS AND MATERIALS

MULTI LINK SEGMENT MODEL

SIMULATION OF HUMAN GAIT

REGRESSION FOR ANTHROPOMETRIC MEASUREMENTS

Subject Index

Back Cover.

Notes:

Includes bibliographical references.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9789815165739

9815165739

OCLC:

1491307617