Intelligent Decision Support System for IoT-Enabling Technologies: Opportunities, Challenges and Applications
Published on 18. January 2024
342 pages
979-8-89113-333-4 (ISBN)
Description
This book focuses on the Internet of Things (IoT) and Decision Support Systems to proffer preventive and intelligent systems. The major areas covered in this book are IoT challenges and opportunities, IoT-enabling technologies, decision support systems, smart applications, and intelligent systems to satisfy the goals of societal and economic issues. This book includes various problems in healthcare, insurance, and agricultural sectors. Intelligent and IoT-based applications like healthcare systems, intelligent transportation systems, business intelligence, and artificial intelligence in sustainable agriculture are extensively discussed in various chapters. IoT and Machine Learning Applications for the industrial sector are also highlighted. This book is most suitable for data scientists, doctors, engineers, economists, and specialists in the agricultural sector. This book will benefit the UG/PG and research scholars to understand various domains like agriculture, insurance, enviroment and healthcare sectors with applications of IoT, machine learning, Artificial Intelligence etc.
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Subrata Sahana
Intelligent Decision Support System for IoT-Enabling Technologies: Opportunities, Challenges and Applications
Book
02/2024
Nova Science Publishers Inc
€303.05
Shipment within 3-4 weeks
Content
- Intro
- Contents
- Preface
- Chapter 1
- IoT-Based Smart Agriculture: Enhancing Agricultural Practices with Robotics and Cloud Computing Applications
- Abstract
- Introduction
- Background
- Applications in Agriculture Sector
- Soil Sampling
- Irrigation
- Fertilizer
- Disease and Pest Control
- Crop Yield Monitoring
- Communication Technologies in Farming
- Cloud Computing
- Smart Phones
- Cellular
- Zigbee
- Bluetooth
- UAVS and Robotics
- Crop Harvesting Robots
- IOT-Based Tractors
- Wireless Sensors
- FPGA Sensors
- Acoustic Sensors
- Optical Sensors
- Ultrasonic Sensors
- Airflow Sensors
- Optoelectronic Sensors
- Electrochemical Sensors
- Mechanical Sensors
- Electromagnetic Sensors
- Eddy Covariance-based Sensors
- Mass Flow Sensors
- LiDAR
- SWLB Sensors
- Remote Sensors
- Telematics
- Current Challenges and Future Scope
- Wireless Sensors for Agricultural Application
- Machine Learning
- UAVs and Robots
- Renewable and Smart Grids
- Vertical Farming (VF)
- Communication
- Conclusion
- References
- Chapter 2
- The Impact of IoT on the Environment: A Descriptive Study in India
- Abstract
- Introduction
- Literature Review
- Objectives
- Methodology
- Results and Discussion
- Optimization of IoT Devices for Environmental Sustainability
- Architect for Devices to Reduce Anthropocene
- IOT and Small Business in Maintaining Sustainability Standards
- Sustainability-Related Internet of Things Applications
- IOT Applications for Environmental Sustainability
- Water Leak Management
- Predictive Servicing
- Environmental Surveillance
- Case Study 1: Smart Energy Management
- Case Study 2: Air Quality Monitoring
- Case Study 3: Water Quality Monitoring
- Case Study 4: Toxic Gas Detection
- Case Study 5: Smart Waste Management
- Case Study 6: Smart Agriculture
- Case Study 7: Cold-Chain Management
- Discussion from Case Studies
- Decreased Costs Associated with Operations
- Increased Productivity While Maintaining a Secure Working Environment
- Better Client Experiences
- Additional Information Regarding the Company
- Confidentiality and Safety
- Problem with the Technology
- Reliance upon Availability of Power and Connectivity
- Price Increases Overall (Time and Money)
- Conclusion
- References
- Chapter 3
- A Smart Internet of Things (IoT) Enabled Agricultural Farming System
- Abstract
- Introduction
- Problem Statement
- Technical Objectives
- The Process and Elements in the System
- Technical Roll Out
- Sensors Used
- Soil Moisture Sensor
- Digital Humidity and Temperature Sensor (DHT11)
- Modules Used
- Wi-Fi Module (ESP8266) (ESPRESSIF)
- Firebase
- View Data through Mobile Application
- Control of Watering Based on Moisture Value
- Water Pumping Motor
- Control of Temperature Based on DHT11 Temperature Value
- DC Cooling Fan
- Implications
- Social Impact
- Economic Aspect
- Conclusion
- References
- Chapter 4
- IoT and Machine Learning Applications for Industrial Reliability Frameworks
- Abstract
- Introduction
- Research Techniques and Their Impact
- Several Machine Learning Paradigms
- Industrial Applications
- Design
- Organizing Processes
- The Identification and Handling of Machining Features
- Group Technologies and Machining Cells
- Organization and Decision-Making
- Planning the Order of Operations
- Breach during Development of ML Solution
- An Archive of Attacks That Have Been Carefully Selected
- Machine Learning with Adversarial Security Code
- Machine Learning Systems: Dynamic and Static Analysis
- Systems Using Machine Learning for Logging and Auditing
- Monitoring and Detection of ML Systems
- Analytics, Machine Learning, and Data
- Analytics for Manufacturing Using Machine Learning
- Machine Learning Analytics for Banking and Finance
- Machine Learning-Based Healthcare Analytics
- Analytics for Marketing Using Machine Learning
- Artificial Intelligence in the Retail Industry
- Consumer Analytics Using Machine Learning
- Research on Predictive Maintenance
- The Proposed Approach
- Possibilities for Further Research
- Conclusion
- References
- Chapter 5
- An IoT-Enabled Model for COVID-19 Patient Healthcare
- Abstract
- Introduction
- Therapeutic and Medicinal Services
- Literature Review
- IoT Healthcare Uses
- Diminishing Emergency Room Wait Times
- Remote Health and Monitoring
- Guaranteeing This Availability and Accessibility of Critical Hardware
- Following Staff, Patients and Inventory
- Improved Drug Management
- Tending to Chronic Disease
- Difficulties to Embrace IoT in Healthcare
- Security and Security of Patient Information
- Lack of Consistency among Associated Cell Phones
- Vulnerable Information Transmissions
- Patient Status
- Awareness About IoTs
- Analysis Paralysis
- Examples of IoT in Healthcare
- Treating This Development of Cancer
- Shot Circle (Mechanized) Insulin Convection
- Associated In-Halers
- The Vast Land scape of Healthcare Stakeholders and IoT Possibilités
- Accélération in All IoT Use Case and Applications in Healthcare Ahead
- The Internet of Things and Healthcare Information System
- Healthcare Data: Working with Propose and Security in Mind
- IoT and Its Background for COVID-19 Pandemic
- Proposed Model Covid Med Map: A Health Monitoring System
- Issues and Future Scope of the Study
- Conclusion
- References
- Chapter 6
- A Healthcare Revolution in Cross Domain Applications Using Advanced Computational Techniques
- Abstract
- Introduction
- Forensic Science
- Molecular Imprinting
- Deoxyribonucleic Acid (DNA)
- Fingerprint
- MEMS and Machine Learning
- MEMS and ML as Smart Wearable Health Monitoring Devices
- MEMS and ML in Real Time Robot status prediction
- MEMS and ML in Rainfall Prediction
- Machine Learning for Speaker Recognition in MEMS Microphone
- Corona Virus a Pandemic
- COVID-19 Tests
- Genetic Antigenic and Serological Tests
- FET Based Biosensor
- MEMS Based RT-PCR Chip
- BIO FED's Based Biosensor
- Conclusion
- References
- Chapter 7
- Predictive Analytics and Deep Learning Models for the Prediction of the Length of Stay, Diabetes, Colorectal Cancer and Cardiovascular Diseases in Patients
- Abstract
- Abbreviations
- Introduction
- Deep Learning and Predictive Health Care Analytics
- Healthcare Prediction Modelling
- Overview for Prediction in Length of Stay (LOS), Diabetes, Cardiovascular Diseases, and Colorectal Cancer
- Colorectal Cancer
- Literature Review Based on Predictive Analytics for Length of Stay (LOS), Diabetes, Cardiovascular Diseases, and Colorectal Cancer
- Predictive Modelling for Predicting Diabetes in Patients Related Work
- Predictive Analytics for Cardiovascular Diseases Prediction Related Work
- Predictive Modeling to Predict Colorectal Cancer Related Work
- Predictive Methods for Length of Stay (LOS), Diabetes, Cardiovascular Diseases, and Colorectal Cancer
- Modelling and Evaluation Length of Stay (LOS) Prediction in Patients
- Modelling
- Evaluation
- Modelling and Evaluation in Diabetes Prediction
- Modelling
- Evaluation
- Modelling and Evaluation for Prediction of Cardiovascular Diseases
- Modelling
- Apriori Algorithm
- Weighted Confidence
- Evaluation
- Modelling and Evaluation for Colorectal Cancer Prediction
- Modelling
- Evaluation
- Results and Discussion
- Results Matrix for Predicting Length of Stay (LOS) in patients
- Results Matrix for Diabetes Prediction
- Results Matrix for Prediction of Cardiovascular Diseases
- Results Matrix for Colorectal Cancer Prediction
- Future Work
- Conclusion
- Length of Stay (LOS)
- Diabetes
- Cardiovascular Diseases
- Colorectal Cancer
- References
- Chapter 8
- Wireless Sensor Network Based Crop-Growth Monitoring Using Derived-Parameters in an Intelligent Greenhouse
- Abstract
- Introduction
- Intelligent Greenhouse (IGH)
- WSN Based Monitoring in Intelligent Green house
- Hardware Unit
- Sensors
- Data Acquisition Unit
- Data Processing Unit
- Communication Unit (RF Transceiver)
- Power Supply Unit
- Software Modules
- Operating System
- Sensor/Actuator Drivers
- Data Networking Stack
- Factors Affecting Plant Growth in Greenhouse
- Micro-Climatic Parameters
- Temperature of the Atmosphere Inside Greenhouse
- Humidity Inside the Green House
- Photosynthetic Active Radiation
- Carbon Dioxide Concentration
- Soil Parameters
- Soil Moisture
- Soil Temperature
- Micro-Nutrient Level in Soil
- Derived Micro-Climatic Parameters
- Vapor Pressure Deficit (VPD)
- Temperature Humidity Index (THI)
- Soil Respiration (SR)
- Mathematical Models for Derived Parameters
- Vapor Pressure Deficit (VPD)
- Temperature Humidity Index Models
- Regression Models
- Rothfusz Model
- National Weather Service (NWS) Model
- Formula Based Models
- Kibler Model
- NOAA (1979) Model
- Carl Scheon Model
- SR Models
- Monitoring Algorithmes
- Individual Parameters Monitoring
- VPD Monitoring Algorithm
- THI Monitoring Module
- SR Monitoring Module
- Conclusion
- References
- Chapter 9
- Machine Learning-Based Google App Store Cataloging Using a Naive Bayes Algorithm
- Abstract
- Introduction
- Prediction and Analysis
- Problem Statement
- Review of Literature
- Classification Issues Solvés Using Naive Bayes Algorithm
- Algorithms
- Random Forest
- Support Vector Machines
- Naive Bayes Algorithm
- Random Forest Algorithm
- System Implementation
- Input and Output Designs
- Logical Layout
- Design of Physical Architecture
- Representation of Input and Output
- Input Design
- Purposes
- Output Layout Design
- Output Screens
- Graphs
- Predictions
- Output of Predictions
- Conclusion
- References
- Chapter 10
- Barriers to Digital Transformation: A Case Study of the Insurance Industry
- Abstract
- Introduction
- Digital Transformation
- Internet of Things
- Artificial Intelligence
- Activities in Change - The Insurance Industry
- Framework - Barriers
- Competence Barriers
- Technical Barriers
- Individual Barriers
- Organizational and Cultural Barriers
- Environmental Barriers
- Method
- Case Study - Policybazaar and Bankbazaar
- Data Collection
- Data Analysis
- Method Discussion
- Results and Analysis
- Competence Barriers
- Technical Barriers
- Data Analysis
- Individual Barriers
- Organizational and Cultural Barriers
- Environmental Barriers
- Discussion
- Digital Transformation of the Insurance Industry
- Identified Barriers in the Insurance Company
- Barrier Framework for the Service Sector
- Conclusion
- References
- Chapter 11
- An IoT-Based Intelligent Healthcare System for Diabetes Prediction
- Abstract
- Introduction
- IoT Architecture
- Objective
- Organization of Chapter
- Literature Review
- IoT Protocols in Healthcare
- Machine Learning in Healthcare
- Common Issues with Existing System
- Suggested Design and Mechanism
- Methodology
- Performance Analysis and Results
- Results of Machine Learning Classifier
- Conclusion
- References
- Chapter 12
- Technological Scrutiny on Energy-Harvested Wireless Sensors for IoMT Healthcare Systems
- Abstract
- Introduction
- Methodology
- IoMT Ecosystem
- Benefits and Limitations of IoMT
- Patient Advantages
- Equipment Manufacturers
- Healthcare Providers
- Technical Challenges
- Market Challenges
- Technologies Enduing IoMT
- Local System and Control Layer
- Device Connectivity and Data Layer
- Application and Analytic Solution Layer
- Connected Medical Devices
- Stationary Medical Devices
- Benefits of Stationary Medical Devices in IoMT
- Limitations of Stationary Medical Devices in IoMT
- Implanted Medical Devices
- Some Examples of Implanted Medical Devices in IoMT
- Benefits of Implanted Medical Devices in IoMT
- Limitations of Implanted Medical Devices in IoMT
- Wearable External Medical Devices
- Some Examples of Wearable External Medical Devices in IoMT
- Benefits of Wearable External Medical Devices in IoMT
- Limitations of Wearable External Medical Devices in IoMT
- IoMT-Based Energy Efficiency System
- Energy Conservation
- Factors for Energy Wastage and Communication
- Applications of IoMT
- Tele Heath
- Improved Drug Management
- Chronic Disease Management
- Prospects of IoMT
- Conclusion
- References
- About the Editors
- Index
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