This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions.
Key Themes
- AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring
- IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming
- AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection
- Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains.
This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.
Readership
Researchers, academics, professionals, and students interested in sustainable AI and IoT.
Table of Contents
Chapter 1 Advanced Rival Combatant Identification With Hybrid Machine Learning Techniques in War Field
- Introduction
- Aim of the Study
- Motivation for the Study
- Literature Review
- Research Methodology - Hybrid Machine Learning Model for Real
- Time Rival Combatant Identification (Hmlmrci)
- Hybrid Machine Learning Model for Real-Time Identification Of
- Rival Combatant
- Model Training and Testing
- Data Acquisition
- Parameter Setting
- Detectability Analysis
- Training Procedure
- Performance Evaluation
- Methodology for Conducting Tests in the Field
- In-Situ Testing Results
- Concluding Remarks
- Acknowledgment
- References
Chapter 2 An IoT-Based Battery Condition Monitoring System for Electric Vehicles
- Introduction
- Related Work
- System Level Architecture
- Proposed Hardware Architecture
- Middleware Integration
- Model Estimation
- Wbms Working Principle Using IoT
- Performance Analysis
- Experimental Setup for Battery Parameter Measurement
- Experimental Validation and Results
- Drive Cycle Characteristics Evaluation
- Storage Server Read &Write Performance
- Mqtt Client Application Output
- Conclusion
- References
Chapter 3 IoT Covid Patient Health Monitoring System
- Introduction
- Related Works
- Methodology
- Hardware Description
- Atmega Microcontroller
- Temperature Sensor
- Heart Beat Sensor
- Blood Pressure Sensor
- Wi-Fi Module
- Display Devices
- Led
- Lcd
- Software Description
- Part 1
- Part 2
- Step 1
- Step 2
- Step 3
- Step 4
- Result and Discussion
- Conclusion
- References
Chapter 4 Artificial Intelligence in Healthcare
- Introduction
- Evolution of Ai
- Concepts in Ai
- Current Areas of Ai
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Applications of AI in Healthcare
- Ai in Oncology
- Ai in Cardiology
- Ai in Neurology
- Ai in Surgery
- Future Aspects of Artificial Intelligence in Healthcare
- Concluding Remarks
- References
Chapter 5 Image-Based Plant Disease Detection Using IoT and Deep Learning
- Introduction
- Related Work
- Materials and Methods
- Data Acquisition
- Mango Plant and Disease
- Proposed Work
- Contrast Enhancement
- K-Means Clustering
- Glcm for Feature Extraction
- Pso-Cnn Approach
- Results
- Conclusion and Future Work
- References
Chapter 6 Artificial Intelligence (Ai): a Potential Technology in the Healthcare Sector
- Introduction
- Types of Ai
- Supervised Type of Ai
- Unsupervised Type of Ai
- Semi-Supervised Type of Ai
- Reinforcement Type of Ai
- Deep Learning
- Applications of AI in Healthcare
- Artificial Neural Network and Ai-Devices
- Ai-Aided Medical Diagnosis
- Robot-Aided Surgery
- Virtual Nursing Aid
- Clinical Trial Support
- Research Based on Drug Discovery
- Ai-Assisted Stroke Management
- Cardiac Tissue Chips (Ctcs)
- Artificial Neurons
- Plastic Surgery
- Organ Transplantation
- Conclusion
- Acknowledgments
- References
Chapter 7 Precision Farming Using IoT for Smart Farming
- Introduction
- Literature Survey
- The Smart Farming Cycle Using IoT
- Digitization in Smart Farming Using Precision Farming
- The Advantages of Precision Farming in Agriculture
- More Evaluation and Monitoring Metrics
- Farm Records Are Accessible
- Improved Crop Protection
- Irrigation Management
- Resource Waste Has Been Reduced
- Future of Smart Farming
- Concluding Remarks
- References
Chapter 8 Impact of Artificial Intelligence (Ai) and Internet of Things (IoT) on the Healthcare Sector: a Review
- Introduction
- Section a
- Artificial Intelligence in Health Care
- Improve the Healthcare System
- Implementation of Medicines
- Healthcare Robotics
- Ai Powered Stethoscope
- Patient Care
- Improving Surgery
- Supports Mental Health
- Patient Empowerment
- Section B
- Internet of Things in Healthcare
- Smartphone Solutions
- Wearable Devices
- Section C
- Economic & Social Benefits
- Section D
- Ambient Assisted Residing
- User Studies
- Smart Home
- Outcomes
- Section a
- Section B
- Section C
- Section D
- Future Perceptions
- Conclusion
- References
Chapter 9 Curvelet-Based Seed Point Segmentation Methodology Using Digital Biomarker for Abnormality Detection in Fetal Spine Disorder
- Introduction
- Existing Works
- Proposed Methodologies
- Segmentation Based on Seed Point Selection from Curvelets
- Selection of Seed Points Using Curvelets
- K-Means Analysis on Segmentation
- Experimental Settings
- Discussion
- Motion Toward Mean Square Error's Effect (Smse)
- Impact of Segmentation Accuracy
- Effect of Abnormality Detection Rate
- Conclusion
- References
Chapter 10 The Effect of the Internet of Things, Artificial Intelligent and Tracking on Smart Transportation
- Introduction
- Review of the Literature and Development of Hypotheses
- Smart Transportation (St)
Author
- Biswadip Basu Mallik
- Gunjan Mukherjee
- Rahul Kar
- Ashok Kumar
