Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 A Sensor-Based Automated Irrigation System for Indian Agricultural Fields -- 1.1 Introduction -- 1.2 Literary Survey -- 1.3 Proposed System -- 1.3.1 System Architecture -- 1.3.2 Flow of Automated Irrigation -- 1.3.3 Interfacing Sensors -- 1.3.4 Physical Characteristics Determination Using Image Processing -- 1.3.4.1 Fractal Dimension Estimation -- 1.3.4.2 Box-Counting Method -- 1.3.4.3 Physical Parameters -- 1.4 Performance Studies -- 1.4.1 Experimental Environment -- 1.4.2 Accessing Shared Variables from NI Data Dashboard -- 1.4.2.1 Scenario 1 -- 1.4.2.2 Scenario 2 -- 1.4.2.3 Scenario 3 -- 1.4.2.4 Scenario 4 -- 1.5 Image Processing to Determine Physical Characteristics -- 1.6 Conclusion and Future Enhancements -- 1.6.1 Conclusion -- 1.6.2 Future Scope -- References -- Chapter 2 An Enhanced Integrated Image Mining Approach to Address Macro Nutritional Deficiency Problems Limiting Maize Yield -- 2.1 Introduction -- 2.2 Related Work -- 2.3 Motivation -- 2.4 Framework of Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield -- 2.5 Algorithm -- Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield -- 2.6 Conclusion -- References -- Chapter 3 Collaborative Filtering Skyline (CFS) for Enhanced Recommender Systems -- 3.1 Introduction and Objective -- 3.1.1 Objective -- 3.2 Motivation -- 3.3 Literature Survey -- 3.4 System Analysis and Existing Systems -- 3.4.1 Drawbacks -- 3.5 Proposed System -- 3.5.1 Feasibility Study -- 3.5.2 Economic Feasibility -- 3.5.3 Operational Feasibility -- 3.5.4 Technical Feasibility -- 3.5.5 Problem Definition and Project Overview -- 3.5.6 Overview of the Project -- 3.5.7 Exact Skyline Computation.

3.5.8 Approximate Skyline Computation -- 3.5.9 Module Description -- 3.5.9.1 Modules -- 3.5.10 Data Flow Diagram -- 3.5.10.1 External Entity (Source/Sink) -- 3.5.10.2 Process -- 3.5.10.3 Data Flow -- 3.5.10.4 Data Store -- 3.5.11 Rules Used For Constructing a DFD -- 3.5.12 Basic DFD Notation -- 3.5.13 Profiles -- 3.5.14 Uploaded My Videos -- 3.5.15 Rating My Videos -- 3.6 System Implementation -- 3.6.1 Implementation Procedures -- 3.6.1.1 User Training -- 3.6.1.2 User Manual -- 3.6.1.3 System Maintenance -- 3.6.1.4 Corrective Maintenance -- 3.6.1.5 Adaptive Maintenance -- 3.6.1.6 Perceptive Maintenance -- 3.6.1.7 Preventive Maintenance -- 3.7 Conclusion and Future Enhancements -- 3.7.1 Conclusion -- 3.7.2 Enhancements -- References -- Chapter 4 Automatic Retinopathic Diabetic Detection: Data Analyses, Approaches and Assessment Measures Using Deep Learning -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Initial Steps and Experimental Environment -- 4.3.1 Analyzing the Principle Components -- 4.3.2 Firefly Algorithm -- 4.4 Experimental Environment -- 4.5 Data and Knowledge Sources -- 4.6 Data Preparation -- 4.7 CNN's Integrated Design -- 4.8 Preparing Retinal Image Data -- 4.9 Performance Evaluation -- 4.10 Metrics -- 4.11 Investigation of Tests -- 4.12 Discussion -- 4.13 Results and Discussion -- 4.14 Conclusions -- References -- Chapter 5 Design and Implementation of Smart Parking Management System Based on License Plate Detection -- 5.1 Introduction -- 5.2 Literature Survey -- 5.2.1 Cloud-Based Smart-Parking System Based on Internet-of-Things/Technologies -- 5.2.2 A Cloud-Based Intelligent Car Parking System -- 5.2.3 Research and Implement of the Intelligent Parking Reservation Management System Based on ZigBee Technology -- 5.2.4 Zigbee and GSM-Based Secure Vehicle Parking Management and Reservation System.

5.2.5 Car Park Management with Networked Wireless Sensors and Active RFID -- 5.2.6 Automated Parking System with Bluetooth Access -- 5.2.7 Smart Parking: A Secure and Intelligent Parking System -- 5.3 Proposed System -- 5.3.1 Methodology -- 5.3.2 Vehicle Number Plate Recognition Technique -- 5.4 High Level Design of Proposed System -- 5.4.1 Data Flow Diagram -- 5.4.2 UML Diagrams -- 5.5 Project Requirement Specification -- 5.5.1 Software Requirements -- 5.5.2 Hardware Requirements -- 5.6 Algorithms -- 5.7 Proposed System Results -- 5.8 Conclusion -- References -- Chapter 6 A Novel Algorithm for Stationary Analysis of the Characteristics of the Queue-Dependent Random Probability for Co-Processor-Shared Memory Using Computational Sciences -- 6.1 Introduction -- Processor-Shared Service Queue with Independent Service Rate Using Probability Queuing Theory -- 6.2 The Applications of Queuing Models in Processor-Shared Memory -- 6.3 The Basic Structure of Queuing Models -- 6.4 Characteristics of Queuing System -- 6.5 The Arrival Pattern of Customers -- 6.6 The Service Pattern of Servers Queue Discipline, System Capacity, and the Number of Servers -- 6.7 Kendall's Notation -- 6.8 The Formation of Retrial Queues as a Solution -- 6.9 The Stationary Analysis of the Characteristics of the M/M/2 Queue with Constant Repeated Attempts -- 6.10 Computation of the Steady-State Probabilities -- 6.11 Application of Retrial Queues -- 6.12 Conclusion -- References -- Chapter 7 Smart e-Learning System with IoT-Enabled for Personalized Assessment -- 7.1 Introduction -- 7.2 Literature Study -- 7.3 Architecture Model -- 7.4 Assessment Technique: CBR Algorithm -- 7.5 Implementation Modules: Project Outcome -- 7.5.1 Creating a Web Application -- 7.5.2 Integrating Raspberry Pi and Scribble Pad -- 7.5.3 Deploying Web App over Internet/FTP Server.

7.5.4 Assessment Technique -- Online Exam -- 7.6 Conclusion -- References -- Chapter 8 Implementation of File Sharing System Using Li-Fi Based on Internet of Things (IoT) -- 8.1 Introduction -- 8.1.1 Motivation -- 8.1.2 Problem Statement -- 8.1.3 Background -- 8.2 Existing System/Related Work -- 8.2.1 SHARE It -- 8.2.2 Super Beam -- 8.2.3 Xender -- 8.3 Literature Survey -- 8.4 Proposed System -- 8.4.1 Input Data -- 8.4.2 Conversion to Binary Encoded Information -- 8.4.3 Led Driver -- 8.4.4 Photo Diode Receiver -- 8.5 Workflow -- 8.6 Proposed Solution -- 8.6.1 Hardware Setup -- 8.6.2 Transistor-Transistor Logic Serial Communication -- 8.6.3 Arduino Uno -- 8.7 Software Implementation -- 8.7.1 Video Transmission -- 8.7.2 Text/Text File Transmission -- 8.7.3 Audio Transmission -- 8.7.4 Image Transmission -- 8.8 Block Diagram -- Indoor Navigation System Using Li-Fi -- 8.9 Implementation -- 8.10 Unicode Transmission -- 8.10.1 Receiver -- Solar Panel -- 8.10.2 Text to Speech -- 8.11 Conclusion -- References -- Chapter 9 Survey on Artificial Intelligence Techniques in the Diagnosis of Pleural Mesothelioma -- 9.1 Introduction -- 9.2 Methods -- 9.3 Analysis -- 9.4 Conclusion -- References -- Chapter 10 Handwritten Character Recognition and Genetic Algorithms -- 10.1 Introduction -- 10.2 Recognition Framework for a Handwritten Character Recognition -- 10.3 Offline Character Recognition -- 10.4 Literature Review -- 10.5 Feature Extraction -- 10.6 Pattern Recognition -- 10.7 Noise Reduction -- 10.8 Segmentation -- 10.9 Pre-Processing -- 10.10 Hybrid Recognition -- 10.11 Applying Genetic Algorithm -- 10.12 Multilingual Characters -- 10.12.1 Multilingual Characters -- Hindi -- 10.12.2 Multilingual Characters -- Tamil Language -- 10.12.3 Multilingual Characters -- Malayalam Language -- 10.12.4 Multilingual Characters -- Telugu Language.

10.12.5 Multilingual Characters -- Kannada Language -- 10.12.6 Multilingual Characters -- Egypt Language -- 10.12.7 Multilingual Characters -- Polish Language -- 10.13 Results -- References -- Chapter 11 An Intelligent Agent-Based Approach for COVID-19 Patient Distribution Management -- 11.1 Introduction -- 11.2 Intelligent Agent's Architecture Proposal for COVID-19 Patient Distribution Management -- 11.2.1 A Clinical Scenario of COVID-19 Patient Distributed Management -- 11.2.2 Communication Management -- 11.3 Intelligent Agents Task Management -- 11.3.1 Intelligent Agents Cooperation Management -- 11.3.1.1 Establishing Commitments -- 11.3.1.2 Adaptive Management of Commitment Changes -- 11.4 Java Agent Development Framework -- 11.4.1 Software Implementation -- 11.4.2 Results Comparison -- 11.5 Conclusions -- References -- Chapter 12 Computational Science Role in Medical and Healthcare-Related Approach -- 12.1 Introduction -- 12.2 Background -- 12.3 Healthcare Nowadays -- 12.4 Healthcare Activities and Processes -- 12.5 Organization and Financial Aspects of Healthcare -- 12.6 Health Information Technology is Currently Being Used -- 12.7 Future Healthcare -- 12.8 Research Challenges -- 12.9 Modeling -- 12.10 Automation -- 12.11 Teamwork and Data Exchange -- 12.12 Scaled Data Management -- 12.13 Comprehensive Automated Recording of Exchanges Between Doctors and Patients -- 12.14 Johns Hopkins University: A Case Study -- 12.15 Case Study: Managing Patient Flow -- 12.16 Case Study: Using Electronic Health Records and Human Factors Engineering -- 12.17 Technology, Leadership, Culture, and Increased Learning are Necessary for the Spread of Systems Approaches -- 12.18 Conclusion -- References -- Chapter 13 Impact of e-Business Services on Product Management -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Data Collection and Method Details.