Green Computing and Its Applications

Contents
Preface
Chapter 1
Embedded Internet of Things (IoT) a New Industrial Revolution
Abstract
1.1. Introduction
1.1.1. Evolution of Industry
1.1.2. Industry 1.0
1.1.3. Industry 2.0
1.1.4. Industry 3.0
1.1.5. Industry 4.0
1.2. What Do You Think Industry 5.0 Will Be?
1.2.1. The Advantages and Disadvantages of the Industrial Revolution
1.2.1.1. Pros
1.2.1.2. Cons
1.3. Literature
1.3.1. Premiere Development Technologies for Industrial 4.0
1.3.2. Characteristics of the Internet of Things
1.4. Applications of IoT
1.4.1. Detection and Tracking of Assets in Smart Factories Using Bluetooth Low Energy
1.4.2. Applications for Audio Speech Processing in the Smart Home
1.4.3. Smart Health: Post-Stroke Rehabilitation by Wearable Prototype
1.4.4. Domain of the Application
1.5. Difficulties in IIOT FDSM
References
Chapter 2
Evolution of Green Communication System
Abstract
2.1. Introduction
2.1.1. Section I: UDMT System Model
2.1.1.1. Device to Device communication
2.1.1.2. Co-Operative Communication
2.1.2. Section II: Massive MIMO
2.1.2.1. MIMO Communication
2.1.2.2. Multi‐User MIMO
2.1.2.3. Massive MIMO
2.1.2.4. Challenges of Massive MIMO in 5G
2.2. Results and Discussion
Conclusion
References
Chapter 3
Big Data Analytics Based Green Application in Text Mining and Literary World
Abstract
3.1. Introduction
3.2. State-of-Art: Literary World in Big Data Text Mining
3.3. Sentiment Classification of Literary Test in Big Data Text Mining
3.3.1. Literary Argument Extraction in Big Data Text Mining
3.3.2. Blog Mining for Literary World
3.3.3. Poetry Data-Based Literary Text Mining
3.3.4. Pre-Processing of Poetry Text
3.3.5. Literary Transcript Analysis in Big Data
3.3.6. Machine Learning Algorithm in Literary Text Mining of Big Data
3.3.7. Linear Regression for Literary Text
3.3.8. Logistic Regression for Literary Text
3.3.9. Decision Tree for Literary Text
3.3.10. Support Vector Machine (SVM) for Literary Text
3.3.11. Naïve Bayes for Literary Text
3.3.12. K- Nearest Neighbour’s For Literary Text
3.3.13. Clustering for Literary Text
3.3.14. K-Means Clustering Algorithm in the Literary World of Big Data
3.3.15. Apriori Algorithm in Literary World of Big Data
3.3.16. Hierarchal Algorithm in the Literary World of Big Data
Conclusion
References
Chapter 4
Deep Learning-Based Solution
for Sustainable Agriculture
Abstract
4.1. Introduction
4.2. Deep Learning
4.2.1. Convolutional Neural Network
4.2.2. Recurrent Neural Network (RNN)
4.2.3. Autoencoder
4.3. Problems in Agriculture
4.3.1. Plant Classification
4.3.2. Plant Recognition
4.3.3. Classification of Crops
4.4. Weeds and Crops Classification
4.5. Plant Disease Identification
4.6. Fruits Counting
4.7. Classification of Fruits
4.8. Available Datasets
References
Chapter 5
Analysing Factors Impacting the Adoption of Green Computing in Indian Universities
Abstract
5.1. Introduction
5.2. Literature Review
5.3. Theoretical Framework
5.4. Research Methodology
Sampling
Demographics of the Respondents
5.4.1. Data Analysis
Reliability and Validity
(i) Cronbach’s Alpha
(ii) Composite Reliability
Exploratory Factor Analysis
Construct Validity (CV)
(i) Convergent Validity
(ii) Divergent or Discriminant Validity
Structural Equation Modelling (SEM)
Discussion
Conclusion
Limitations and Future Research
References
Chapter 6
Latest Advancement in Automotive Embedded System Using IoT Computerization
Abstract
6.1. Introduction
6.2. Related Work
6.3. Essential Embedded Systems
6.4. Internet of Things
6.4.1. IoT Based Smart Vehicles Solution
6.4.2. IoT Traffic Agents
6.5. Prologue to IoT and Automotive Cloud Services
6.5.1. IoT and Automotive Cloud Services
6.5.2. IoT Automotive Cloud Services
6.5.3. Network
6.5.4. Equipment Control and Management
6.5.5. Data Collection
6.5.6. Data Analytics
6.5.7. Data Visualization
6.5.8. Management of Configurations
6.5.9. Command Execution
6.6. Interoperability in Time
6.7. Stochastic Analysis
6.8. Multicore ECU
6.9. Utilization of IoT in Automotive Transportation
6.9.1. Intelligent Fleet Management
6.9.2. Insurance of Operational Optimization, Service Competence of Real-Time Tracking Exactness
6.9.3. Real-Time Video Surveillance on Freight Logistics
6.9.4. Risk Reduction, Operational Costs Decrease and Fleet Safety Improvement
6.9.5. Advance Driver Assistance Solution (ADAS)
6.9.6. Workers
6.9.7. Security
6.9.8. Transportation of Goods
6.10. Present Day Applications of Automotive Embedded Systems
6.11. Setup of the Experiment
6.12. GPS Tracking
6.12.1. Arduino Uno Development Board
6.13. Proposed Methodology
6.13.1. Accident Detection
6.13.2. Travelers Safety
6.13.3. Drunk Driver Prevention
6.13.4. Automatic Rain-Sensing Wipers
6.14. Results and Discussion
Conclusion and Future Directions
References
Chapter 7
Integration of Smart-IoT Devices to Enhance Security and Performance of Smart Grids and Smart Energy Systems
Abstract
7.1. Introduction
7.2. Literature Review
7.3. Proposed Smart-IoT Device Architecture Design for Smart Grid and Smart Energy Distribution
7.3.1. The Mode Selection Interface
7.3.2. RS232 Interface with PLI for Scanning and Control
7.3.3. Load Prediction Block for Analysis of Demand and Supply
7.3.4. Stability Analysis Block
7.3.5. Bi-Directional Communication Interface
7.3.6. Blockchain for Improved Attack Detection
7.4. Result Analysis and Comparison
Conclusion
References
Chapter 8
Design of an Adaptive and Flexible Green Computing Architecture for Multi-Domain Social Applications via Artificial Intelligence
Abstract
8.1. Introduction
8.2. Literature Review
8.3. Proposed Artificial Intelligence-Based Flexible Green Computing Model
8.4. Result Analysis and Comparison
Conclusion
References
Chapter 9
Impact on Organizational Performance of Indian SMEs After the Adoption of Green Computing
Abstract
9.1. Introduction
9.2. Literature Review
9.3. Research Framework
9.4. Research Methodology
9.4.1. Sampling
9.4.2. Demographics of the Respondents
9.5. Data Analysis
9.5.1. Reliability and Validity
9.5.1.1. Cronbach’s Alpha
9.5.1.2. Composite Reliability
9.5.2. Exploratory Factor Analysis
9.5.3. Construct Validity (CV)
9.5.3.1. Validity Divergent or Discriminatory
9.5.4. Structural Equation Modeling
9.5. Discussion
9.6. Managerial Implications
Conclusion
References
Chapter 10
High-Performance Computing and Fault Tolerance Technique Implementation in Cloud Computing
Abstract
10.1. Introduction
10.2. Related Work
10.2.1. Supercomputers
10.3. Cloud Computing
10.3.1. Cloud Characterization
10.3.2. Cloud Services
10.3.3. HPC in the Cloud
10.3.4. All-Cloud
10.3.4.1. Cloud Blasting
10.3.4.2. All-Cloud: Minimize the Local Footprint
10.3.5. Cloud Bursting: Expanding from Local
10.3.5.1. All-Cloud or Bursting?
10.3.5.2. HPC Performance Benchmarking
10.3.5.3. Superior Computing Requirements in Cloud
10.3.6. HPC versus HSC
10.3.7. GPU-Accelerated Computing
10.3.7.1. How GPUs Accelerate Software Applications
10.3.7.2. Memory Modes for Increased Performance on Intel Xeon Phi
10.3.7.3. HPC Software
10.3.8. Execution Penalties
10.3.9. Difficulties for High-Performance Computing Applications in the cloud
10.3.10. Cloud Benefits for High-Performance Computing
10.4. Proposed Method
10.4.1. Relocation Policy Based on Proposed Method
10.4.2. Control Module in Proposed Method
10.5. Result and Simulation
Conclusion
References
Chapter 11
An Analysis of Internet of Things (IoT)–Based Home Appliances
Abstract
11.1. Introduction
11.1.1. Identification
11.1.2. Sensing
11.1.3. Communication
11.1.4. Computation
11.1.5. Services
11.1.6. Semantics
11.1.6.1. Saving Time
11.1.6.2. Saving Energy
11.1.6.3. Cost-Efficient
11.1.6.4. Security Enhancement
11.1.6.5. Convenience
11.1.6.6. Adaptability
11.1.6.7. Integration
11.1.6.8. Task Management
11.2. IoT Technology
11.2.1. Radiofrequency Identification (RFID)
11.2.2. Wireless Sensor Networks (WSNs)
11.2.2.1. Barcodes
11.2.2.2. Near Field Communication (NFC)
11.2.2.3. Cloud Computing
11.3. IoT Based Home Appliances
11.3.1. Amazon Echo
11.3.2. Google Nest Hub
11.3.3. Nest Cam Indoor and Outdoor Camera
11.3.4. Smart Mat Intelligent Yoga Mat
11.3.5. Smart LED Bulb
11.3.6. TrackR Bravo Tracking Device
11.3.7. Honeywell Wi-Fi Smart Thermostat
11.3.8. Logitech Pop Smart Button Controller
11.3.9. June Intelligent Oven
11.3.10. Ring Pro Smart Video Doorbell
11.3.11. LG Web OS Smart OLED TV
11.4 Composition of an Advanced Smart Home
Conclusion
References
Chapter 12
Internet of Things (IoT) in Agriculture
Abstract
12.1. Introduction
12.2. Iot Transformation in THE FUTURE of Agriculture
12.2.1. Use of Smart Agriculture Iot Technology
12.2.2. Usage of Greenhouse Can Be Automated Using Iot Applications in Farming
12.2.3. Reduced Water Consumption in Agriculture
12.2.4. Pest Monitoring
12.2.5. Livestock Tracking
12.2.6. Big Data in Farming
12.2.7. Smart Agriculture Predictive Analytics
12.3. Applications of Iot in Agriculture
12.3.1. Weed Robots
12.3.2. Harvesting Robotics
12.3.3. Drones
12.3.4. Machine Navigation
12.3.5. Climatic Conditions
12.3.6. Soil Quality
12.4. Sensors Used for Agriculture
12.4.1. Agricultural Temperature Sensors
12.4.2. Smart Cameras Use in Agriculture
12.4.3. pH Sensors in Agriculture
12.4.4. GPS Sensors
12.4.5. Sensors for Resource Monitoring
12.4.6. Accelerometer Sensor
12.5. IoT Challenges in Agriculture
12.5.1. Connectivity
12.5.2. Design and Durability
12.5.3. Limited Resources and Time
12.5.4. Adaptability of Farmers’ Technology
Conclusion
References
About the Editors
Index
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