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Table of Contents
Intro
Preface
Introduction
Contents
About the Editors
Internet of Things: Technologies and Applications
1 Introducton
2 State-of-the-Art Technologies and Applicatons of IoT
2.1 Technologies
2.2 Internet of Things in Smart Cities
2.2.1 Smart Lighting System
Lamp Unit (LU)
Local Control Unit (LCU)
Control Center (CC)
2.2.2 Waste and Garbage Management
2.3 Internet of Things in Smart Homes Domain
2.4 Internet of Things in Agriculture Domain
2.4.1 Sampling and Mapping of Soil
2.4.2 Irrigation
2.4.3 Fertilizer
2.4.4 Crop Disease and Pest Management
2.4.5 Crop Monitoring, Forecasting, and Harvesting
2.5 Industrial Internet of Things (IIOT)
2.6 Internet of Things in Energy Conservation
2.7 Internet of Things in Healthcare
2.7.1 IoT Healthcare Applications
Monitoring of Blood Glucose Level
Electrocardiogram Monitoring
Blood Pressure Monitoring
Body Temperature Monitoring
Monitoring of Blood Oxygen Saturation
Rehabilitation System
Wheelchair Management
3 Case Studies
3.1 Efficient Water Supply and Management
3.1.1 Water Usage and Management: City of Surrey, Canada
3.2 IoT in Traffic Control and Management
3.2.1 Dallas ́Traffic Management System, Texas
3.2.2 Management of Railway in Germany
3.3 Garbage and Waste Management
3.3.1 A Case Study: Pennsula Santary Servce Inc. (PSSI) Implements Contaner Montorng Sensors
3.3.2 How One Waste Hauler Implemented Image-Based Container Sensors to Manage Inventory and Streamline Services
The Challenge
The Solution
The Results
3.4 Smart and Efficient Parking
3.4.1 Smart Parking System in Burlington, Canada
3.4.2 Solution for Guided Parking
Services End-to-End
Advantages of the Result
4 Conclusion and Future Prospects of IoT
References
Prescriptive Analytics in Internet of Things with Concentration on Deep Learning
1 Introduction
2 Literature Review
2.1 Internet of Things (IoT)
2.2 IoT Architecture
2.2.1 Coding Layer
2.2.2 Perception Layer
2.2.3 Network Layer
2.2.4 Middleware Layer
2.2.5 Application Layer
2.2.6 Business Layer
2.3 Automated Controlling
2.4 Data Analytics
2.5 Information Sharing
3 Deep Learning
3.1 Deep Belief Network (DBN)
3.2 Convolutional Neural Network (CNN)
3.3 Artificial Neural Network (ANN)
3.4 Deep Neural Network (DNN)
4 Prescriptive Analytics
4.1 Descriptive Analytics
4.2 Predictive Analytics
4.3 Prescriptive Analytics
4.4 Detective Analytics
4.5 Cognitive Analytics
5 Methodology
6 Prescriptive Analytics in IoT Through Deep Learning
7 Research Model and Discussion
7.1 Deep Learning and Prescriptive Analytics
7.2 Optimization Algorithms and Prescriptive Algorithms
7.3 Prescriptive Analytics and Exploitation Capability
Preface
Introduction
Contents
About the Editors
Internet of Things: Technologies and Applications
1 Introducton
2 State-of-the-Art Technologies and Applicatons of IoT
2.1 Technologies
2.2 Internet of Things in Smart Cities
2.2.1 Smart Lighting System
Lamp Unit (LU)
Local Control Unit (LCU)
Control Center (CC)
2.2.2 Waste and Garbage Management
2.3 Internet of Things in Smart Homes Domain
2.4 Internet of Things in Agriculture Domain
2.4.1 Sampling and Mapping of Soil
2.4.2 Irrigation
2.4.3 Fertilizer
2.4.4 Crop Disease and Pest Management
2.4.5 Crop Monitoring, Forecasting, and Harvesting
2.5 Industrial Internet of Things (IIOT)
2.6 Internet of Things in Energy Conservation
2.7 Internet of Things in Healthcare
2.7.1 IoT Healthcare Applications
Monitoring of Blood Glucose Level
Electrocardiogram Monitoring
Blood Pressure Monitoring
Body Temperature Monitoring
Monitoring of Blood Oxygen Saturation
Rehabilitation System
Wheelchair Management
3 Case Studies
3.1 Efficient Water Supply and Management
3.1.1 Water Usage and Management: City of Surrey, Canada
3.2 IoT in Traffic Control and Management
3.2.1 Dallas ́Traffic Management System, Texas
3.2.2 Management of Railway in Germany
3.3 Garbage and Waste Management
3.3.1 A Case Study: Pennsula Santary Servce Inc. (PSSI) Implements Contaner Montorng Sensors
3.3.2 How One Waste Hauler Implemented Image-Based Container Sensors to Manage Inventory and Streamline Services
The Challenge
The Solution
The Results
3.4 Smart and Efficient Parking
3.4.1 Smart Parking System in Burlington, Canada
3.4.2 Solution for Guided Parking
Services End-to-End
Advantages of the Result
4 Conclusion and Future Prospects of IoT
References
Prescriptive Analytics in Internet of Things with Concentration on Deep Learning
1 Introduction
2 Literature Review
2.1 Internet of Things (IoT)
2.2 IoT Architecture
2.2.1 Coding Layer
2.2.2 Perception Layer
2.2.3 Network Layer
2.2.4 Middleware Layer
2.2.5 Application Layer
2.2.6 Business Layer
2.3 Automated Controlling
2.4 Data Analytics
2.5 Information Sharing
3 Deep Learning
3.1 Deep Belief Network (DBN)
3.2 Convolutional Neural Network (CNN)
3.3 Artificial Neural Network (ANN)
3.4 Deep Neural Network (DNN)
4 Prescriptive Analytics
4.1 Descriptive Analytics
4.2 Predictive Analytics
4.3 Prescriptive Analytics
4.4 Detective Analytics
4.5 Cognitive Analytics
5 Methodology
6 Prescriptive Analytics in IoT Through Deep Learning
7 Research Model and Discussion
7.1 Deep Learning and Prescriptive Analytics
7.2 Optimization Algorithms and Prescriptive Algorithms
7.3 Prescriptive Analytics and Exploitation Capability