IoT and Smart Devices for Sustainable Environment

Description

This book presents research related to smart devices and Internet of Things (IoT) that are intended to advance environmental sustainability. With sustainability as the focus, the topics covered include designing and controlling of smart systems, networking and machine learning, monitoring and controlling the environment, smart metering, authentication and authorization, and software and systems solution. The authors discuss how IoT can aid in sustainability through its implementation of systems interconnecting several objects, whether in the physical or in the virtual worlds. The chapters also present several applications including in smart homes, transportation, and healthcare. The book pertains to researchers, academics, and professionals. Preface Organization of the Book Acknowledgments Contents Detection of Some Water Elements Based on IoT: Review Study 1 Introduction 2 Background 3 Features of Comparison 4 Results and Discussion 5 Conclusion and Future Research References Simulation of the Treatment Performance of a Purification Plant for a Dairy Effluent 1 Introduction 2 Materials and Methods 2.1 Parameter Analysis 2.2 Software Uses 2.3 Model Selection 3 Results and Discussions 3.1 Input Effluent Characteristics 3.2 Simulation of WWTP Operations 4 Conclusion References Study of Piroxicam Removal from Wastewater by Artichoke Waste Using NemrodW® Software: Statistical Analysis 1 Introduction 2 Materials and Methods 2.1 Preparation of Artichoke Waste 2.2 Preparation of Piroxicam Solutions 2.3 Statistical Analysis: Determination of Piroxicam Key Adsorption Parameters 3 Results and Discussion 3.1 Statistical Analysis 3.2 Determination of the Key Parameters for Piroxicam Adsorption via Artichoke Waste 3.3 Pareto Analysis 3.4 Residue Study of Piroxicam Removal Rate (Henry Plots) 4 Conclusions References Theoretical Study of Thermoelectric Transport Properties of Dicalcium Silicide and Dicalcium Germanide Compounds 1 Introduction 2 Method of Computation 3 Results and Discussion 3.1 Energy Band Structure 3.2 Electrical Conductivity (σ) 3.3 Electronic Thermal Conductivity () 3.4 Seebeck Coefficient 3.5 Power Factor 4 Conclusions References Modeling and Design of Water Treatment Processes by Biosorption Method Using JMP®11 Software 1 Introduction 2 Materials and Methods 2.1 Materials 2.1.1 Adsorbents 2.1.2 Adsorbates 3 Methods 3.1 Experimental Method 4 Design of Experiments 5 Selected Parameters 6 Coefficient of Determination R2 7 Analysis of Variance 8 Study of the Interactions by the Response Surface 9 Optimization 10 Results and Discussion 10.1 Experimental Design 11 Coefficient of Determination 12 Analysis of Variance (ANOVA) 13 Development of Regression Model Equation 14 Analysis of Interactions 15 Optimization 15.1 Prediction Profiler 16 Three-Dimensional Response Surface (3-D) 17 Conclusions References Mathematical and Statistical Study for the Wastewater Adsorbent Regeneration Using the Central Composite Design 1 Introduction 2 Method of Computation 3 Results and Discussion 3.1 Model Validation 4 Prediction Profiler 4.1 Regeneration Cycle 5 Conclusion References IoT and Reality Mining for Real-Time Disease Prediction 1 Introduction 2 Data Mining for Predictive Analytics: Background 3 The Prediction System 3.1 Reality Mining for Prediction 3.1.1 Gathering Process Overview 3.1.2 IoT Implementation 3.2 Prediction Process 4 Case Study on Miscarriage Prediction 4.1 State of the Art of Miscarriage Prediction 4.2 Miscarriage Risk Factors 4.3 System Dataset 4.4 Experiment Results 4.4.1 Performance and Efficiency 4.4.2 Clusters Definition and Distribution 4.4.3 K-Means Scatter Plot 4.5 Evaluation and Validation 4.5.1 Evaluation Using a Random K 4.5.2 Clustering Validation Metrics 5 Conclusion References Smart System for Monitoring and Controlling of Agricultural Production by the IoT 1 Introduction 2 Related Works 3 System Development Materials 3.1 Processing Module 3.2 Sensing Module 3.2.1 Temperature and Humidity Sensors 3.2.2 Light Sensor 3.2.3 Water Flow Sensor 3.2.4 Soil Moisture 3.3 Actuator Module 3.4 Communication Module 3.4.1 Bluetooth 3.4.2 Wi-Fi 4 The Proposed System 4.1 System Overview 4.2 System Implementation 5 Results and Discussion 6 Conclusion References Simulation of Groundwater Quality: Case Study of the Limestone Chain of the Western Rif of Morocco 1 Introduction 2 Study Area 3 Materials and Methods 3.1 General Water Quality Status 4 Results and Discussion 4.1 Coefficients of Biochemistry Action 4.2 Simulation and Monitoring of Concentrations 4.3 Stability Analysis 5 Conclusions References A Novel Anomaly Network Intrusion Detection System for Internet of Things Security 1 Introduction 2 Related Work 3 Background 3.1 Internet of Things Security 3.2 Machine Learning Techniques 4 New Approach 5 Experimental Study and Assessments 6 Conclusion and Future Works References Precision Agriculture: Assessing Water Status in Plants Using Unmanned Aerial Vehicle 1 Remote Sensing Using an Unmanned Aerial Vehicle 1.1 Unmanned Aerial Vehicle Surveillance of Crops 1.2 Unmanned Aerial Vehicle System Technologies 1.2.1 Ground Control Station (GCS) 1.2.2 UAV Control System (UAV CS) 1.2.3 Data Collection Using Sensors 1.3 Unmanned Aerial Vehicle advantages 2 Precision Agriculture Using Unmanned Aerial Vehicle 2.1 Unmanned Aerial Vehicle Data Acquisition 2.1.1 Visible Light Sensors (RGB) 2.1.2 Multispectral Imaging Sensors 2.1.3 Thermal Infrared Sensors 2.2 UAS Data Processing 2.3 Techniques to Analyze UAV Imagery 2.3.1 Photogrammetry Techniques 2.3.2 Machine Learning Techniques 2.3.3 Vegetation Indices Calculation 3 The Thermal-Based Crop Stress Sensing 3.1 Unmanned Aerial Vehicle and Thermal Imaging 3.1.1 Water Stress Cumulative Integration 3.1.2 Measurement of the Crop Water Stress Indicator 4 Conclusion References Smart Healthcare Using Evolutionary Algorithm 1 Introduction 1.1 Motivation 1.2 Our Contribution 1.3 Organization of the Chapter 2 Related Work 3 Proposed System Model 3.1 Scenario 3.2 Workflow Between Patient and Doctor IoT Device with Edge Layers 4 Proposed Scheme for SMC Prediction 4.1 Genetic Algorithm 4.2 Population Initialization 4.3 Selection 4.4 Objective Functions 4.5 Crossover and Mutation 4.6 Multi-Criteria Objective Model for SMC Prediction 5 Analysis and Experimental Results 5.1 Analysis 5.2 Results 6 Conclusion References Index