Intelligent Decision Support System for IoT-Enabling Technologies.

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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