Читать книгу The Smart Cyber Ecosystem for Sustainable Development - Группа авторов - Страница 3

1 Chapter 1Figure 1.1 Three-layer IoT architecture.Figure 1.2 Evolution of IoT.Figure 1.3 IoT networking.Figure 1.4 Arduino UNO board [21].Figure 1.5 Raspberry Pi 4 [24].Figure 1.6 DHT sensor [29].Figure 1.7 Future smart farm [28].

2 Chapter 2Figure 2.1 SON features.Figure 2.2 Machine learning types.Figure 2.3 Illustration of SVM.Figure 2.4 Illustration of KNN.Figure 2.5 Illustration of K-means clustering.Figure 2.6 The SDN architecture with knowledge plane.Figure 2.7 The OpenFlow architecture.Figure 2.8 The transmission cycle of SU.

3 Chapter 3Figure 3.1 Process of IoT communication.Figure 3.2 IoT communication devices.Figure 3.3 IoT architecture.

4 Chapter 4Figure 4.1 Steps involved in using AI and Big Data together.Figure 4.2 A typical neural network with two hidden layers.Figure 4.3 Three V’s of Big Data.Figure 4.4 Applications of Big Data.Figure 4.5 Major contribution of Big Data in education.Figure 4.6 Statistical data of AI-powered IoT [81].

5 Chapter 5Figure 5.1 Components of Apache Spark.Figure 5.2 Apache Hadoop MapReduce.Figure 5.3 Resilient distributed dataset.Figure 5.4 Spark RDD operations—transformation and action.Figure 5.5 Types of discrete APIs characteristics in datasets.Figure 5.6 Spark SQL architecture.Figure 5.7 Spark SQL pipeline.Figure 5.8 Architecture of Hive tables.

6 Chapter 6Figure 6.1 Components of sensor nodes and WSN’s architecture.Figure 6.2 Components of WSNs.Figure 6.3 Categories of trust.Figure 6.4 Properties of trust in WSNs.Figure 6.5 Elements of trust model.Figure 6.6 Motivation, designing criteria, types, and attacks against trust in W...Figure 6.7 Clustered WSN topology.Figure 6.8 Successful interaction between SN x and SN y.Figure 6.9 Change in trust values with respect to ϕ.Figure 6.10 Trust value vs. success rate and ϕ.Figure 6.11 Average trust value vs. success rate.Figure 6.12 False-negative and false-positive alarms.

7 Chapter 7Figure 7.1 Smart infrastructure.Figure 7.2 Diagram of construction of IoT for all applications.Figure 7.3 A broad overview of various components needed in a smart city.Figure 7.4 A smart city ecosystem.Figure 7.5 Architecture of smart hospital system.Figure 7.6 A modern IoT livestock paradigm.Figure 7.7 An example of cloud IoT solution for greenhouse plantation.Figure 7.8 Smart building architecture.Figure 7.9 Food supply chain.

8 Chapter 8Figure 8.1 Architecture of the system.Figure 8.2 Sequence tree for the whole system from center node to station nodes.Figure 8.3 Connection diagram for each sensor station.Process Chart 8.1 Flow chart for the system.Process Chart 8.2 Use case for the system.Figure 8.4 Raspberry Pi Board, Halfacree Gareth, and Raspberry Pi 3 B + single-b...Figure 8.5 Arduino Uno Development Board, Electronics SparkFun, and Arduino Uno ...Figure 8.6 DHT-11 Sensor, DHT-11 Sensor Pinout, features and datasheet, DHT11–te...Figure 8.7 Soil moisture sensor with the precautionary warning threshold for ins...Testing Figure 8.1 (a) Installation of the device in the field for real-time dat...Testing Figure 8.1 (b) Device installed and delivering the data to the center no...Testing Figure 8.2 (a) Test application interaction UI.Testing Figure 8.2 (b) Fetched testing data screen.

9 Chapter 9Figure 9.1 Timeline evolution of Artificial Intelligence.Figure 9.2 Relationship between AI, ML, and DP.Figure 9.3 Components of Artificial Intelligence.Figure 9.4 Sample Gujarati joint-characters.Figure 9.5 Test characters.Figure 9.6 Neural network training details.Figure 9.7 Output window.

10 Chapter 10Figure 10.1 Architecture of IoT.Figure 10.2 Dimensions of interoperability.Figure 10.3 Future challenges of IoT.Figure 10.4 Applications of IoT.Figure 10.5 Essential IoT technologies.

11 Chapter 11Figure 11.1 MAs in color image of the fundus image. (a) Color image of the fundu...Figure 11.2 Representation of hard exudates and Soft exudates from retinal fundu...Figure 11.3 Hemorrhages in the color fundus image. (a) Color fundus image and (b...Figure 11.4 Color images of the retinal fundus of both eyes (left and right) and...Figure 11.5 Illustration of the problem of low and varying contrast in color fun...Figure 11.6 Problem with segmentation of retinal vessels, especially small vesse...Figure 11.7 Pictorial representation of the conversion of the color image of the...Figure 11.8 The proposed CNN architecture. The encoder network and the decoder n...Figure 11.9 Qualitative results of the retinal vessel segmentation. From top to ...

12 Chapter 12Figure 12.1 IoT architecture.Figure 12.2 Basic architecture for IoT in healthcare.Figure 12.3 IoT for mental health: A mechanism to alert caregiver.Figure 12.4 A simple frame work for the blockchain in IoT figure from [55].Figure 12.5 Healthcare IoT blockchain platform implementation from [56].

13 Chapter 14Figure 14.1 Supervised, unsupervised, and reinforcement learning.Figure 14.2 The clinician can pass the finding plan through artificial intellige...Figure 14.3 Current clinical framework.Figure 14.4 Pipeline for building image-based machine learning models.

14 Chapter 15Figure 15.1 Big data 4Vs.Figure 15.2 Big data architecture.Figure 15.3 AI-based method to conquer COVID-19 [18].Figure 15.4 MRI mages [19].Figure 15.5 Summary of wearable sensors [30].

15 Chapter 16Figure 16.1 The precautionary steps to be followed by individuals in quarantine ...Figure 16.2 The happiness index of metro city.Figure 16.3 The happiness index of rural city.Figure 16.4 The happiness index vs. age correlation of metro city.Figure 16.5 The happiness index vs. age correlation of rural city.Figure 16.6 The radiation analysis of different gadgets in metro city.Figure 16.7 The radiation analysis of different gadgets in metro city.Figure 16.8 All sample location distribution visualization.Figure 16.9 Left- and right-hand happiness index analysis before and after Yagya...Figure 16.10 Average improvement left- and right-hand analysis after Yagya activ...

16 Chapter 17Figure 17.1 Types of depression.Figure 17.2 Text mining.Figure 17.3 Pie chart of social networking sites as per the number of users.Figure 17.4 Symptom extraction process.Figure 17.5 Word frequency for depression related words.Figure 17.6 Word embedding.Figure 17.7 Word clustering.Figure 17.8 Sentiment analysis of text.

17 Chapter 18Figure 18.1 Characteristics of fog computing.Figure 18.2 Reference architecture of fog computing.Figure 18.3 CISCO IOx architecture.Figure 18.4 Fog architecture.Figure 18.5 Flow chart for privacy preservation mechanism.

18 Chapter 19Figure 19.1 Various types of web based attacks.Figure 19.2 Various types of system based attacks.Figure 19.3 Process of cryptography between sender and receiver.Figure 19.4 Process of digital signature in cybersecurity.Figure 19.5 Installation of firewall between internet and intranet network.Figure 19.6 Essential elements of cybersecurity.Figure 19.7 Cybersecurity concern.

19 Chapter 20Figure 20.1 Immutability in blockchain.Figure 20.2 Types of consensus mechanism.Figure 20.3 Basic features of consensus protocol.Figure 20.4 Commonly known consensus algorithms.Figure 20.5 Comparison of proof of work and proof of stake.Figure 20.6 History of blockchain technology—Timeline infographic.Figure 20.7 Flow chart of the process.Figure 20.8 Screenshot of bitcoin core.Figure 20.9 Screenshot of transactions per day.Figure 20.10 Median time confirmation of transactions.Figure 20.11 Algorithm modification.Figure 20.12 Execution of new algorithm.Figure 20.13 Block services.Figure 20.14 Block services.Figure 20.15 Transaction services.Figure 20.16 Working directory.Figure 20.17 Number of transactions per day.Figure 20.18 Energy consumption per day.Figure 20.19 Block size.Figure 20.20 Future scopes of blockchain.

20 Chapter 21Figure 21.1 Linking of multiple blocks in a blockchain system.Figure 21.2 Typical block structure in a blockchain system.Figure 21.3 SHA-256 Hash Function.Figure 21.4 SHA-256 Hash Function after block segmentation.Figure 21.5 Insertion/encryption of a new block into the blockchain.Figure 21.6 Vote count process in online voting system using blockchain approach...Figure 21.7 General interaction in online voting system using blockchain.Figure 21.8 Potential framework of an online voting system using blockchain.Figure 21.9 Steganographic system framework [3].Figure 21.10 Steganographic embedding process [3].Figure 21.11 Proposed system framework using visual cryptography [4].Figure 21.12 Sample image share generation in proposed system [4].Figure 21.13 Creation of the cover image [5].Figure 21.14 Use of stego image to envelope secret message [5].Figure 21.15 Candidate insertion into database [6].Figure 21.16 Eligible voter registration and validation [6].Figure 21.17 Voting process and winner determining algorithm [6].Figure 21.18 Mobile website interface samples [6].Figure 21.19 Blockchain structure used by the proposed system [7].Figure 21.20 Proposed system framework using blockchain [7].Figure 21.21 Voter registration page [8].Figure 21.22 Voting page [8].Figure 21.23 Hash value of the image with the secret ink [8].Figure 21.24 Login procedures of the proposed system [9].Figure 21.25 Iris image registration process [9].Figure 21.26 Iris image authentication process [9].Figure 21.27 Voter NID and SIM registration phase [10].Figure 21.28 SIM login verification phase [10].Figure 21.29 Preferred candidate vote count incrementing [10].Figure 21.30 Results outcome at the end of polling [10].Figure 21.31 Error messages during an unsuccessful login [10].Figure 21.32 Image steganography and visual cryptography system framework [11].Figure 21.33 User registration phase and password hashing [11].Figure 21.34 Voter and administrator authentication using hash and salt value [1...Figure 21.35 Administrator homepage [11].Figure 21.36 Voting system based on secret sharing authentication framework [12]...Figure 21.37 Algorithm to form shares [12].Figure 21.38 Algorithm to reconstruct shares [12].

21 Chapter 22Figure 22.1 Variants of cybersecurity.Figure 22.2 Categories of machine learning methods for cybersecurity.