
Intelligent Decision Support System for IoT-Enabling Technologies: Opportunities, Challenges and Applications
Beschreibung
Weitere Details
Weitere Ausgaben
Inhalt
- 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
- Blank Page
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