Оглавление
Группа авторов. AI and IoT-Based Intelligent Automation in Robotics
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
AI and IoT-Based Intelligent Automation in Robotics
Preface
1. Introduction to Robotics
1.1 Introduction
1.2 History and Evolution of Robots
1.3 Applications
1.4 Components Needed for a Robot
1.5 Robot Interaction and Navigation
1.5.1 Humanoid Robot
1.5.2 Control
1.5.3 Autonomy Levels
1.6 Conclusion
References
2. Techniques in Robotics for Automation Using AI and IoT
2.1 Introduction
2.2 Brief History of Robotics
2.3 Some General Terms
2.4 Requirements of AI and IoT for Robotic Automation
2.5 Role of AI and IoT in Robotics
2.6 Diagrammatic Representations of Some Robotic Systems
2.7 Algorithms Used in Robotics
2.8 Application of Robotics
2.9 Case Studies. 2.9.1 Sophia
2.9.2 ASIMO
2.9.3 Cheetah Robot
2.9.4 IBM Watson
2.10 Conclusion
References
3. Robotics, AI and IoT in the Defense Sector
3.1 Introduction
3.2 How Robotics Plays an Important Role in the Defense Sector
3.3 Review of the World’s Current Robotics Capabilities in the Defense Sector
3.3.1 China
3.3.2 United State of America
3.3.3 Russia
3.3.4 India
3.4 Application Areas of Robotics in Warfare
3.4.1 Autonomous Drones
3.4.2 Autonomous Tanks and Vehicles
3.4.3 Autonomous Ships and Submarines
3.4.4 Humanoid Robot Soldiers
3.4.5 Armed Soldier Exoskeletons
3.5 Conclusion
3.6 Future Work
References
4. Robotics, AI and IoT in Medical and Healthcare Applications
4.1 Introduction. 4.1.1 Basics of AI
4.1.1.1 AI in Healthcare
4.1.1.2 Current Trends of AI in Healthcare
4.1.1.3 Limits of AI in Healthcare
4.1.2 Basics of Robotics
4.1.2.1 Robotics for Healthcare
4.1.3 Basics of IoT
4.1.3.1 IoT Scenarios in Healthcare
4.1.3.2 Requirements of Security
4.2 AI, Robotics and IoT: A Logical Combination. 4.2.1 Artificial Intelligence and IoT in Healthcare
4.2.2 AI and Robotics
4.2.2.1 Limitation of Robotics in Medical Healthcare
4.2.3 IoT with Robotics
4.2.3.1 Overview of IoMRT
4.2.3.2 Challenges of IoT Deployment
4.3 Essence of AI, IoT, and Robotics in Healthcare
4.4 Future Applications of Robotics, AI, and IoT
4.5 Conclusion
References
5. Towards Analyzing Skill Transfer to Robots Based on Semantically Represented Activities of Humans
5.1 Introduction
5.2 Related Work
5.3 Overview of Proposed System
5.3.1 Visual Data Retrieval
5.3.2 Data Processing to Attain User Objective
5.3.3 Knowledge Base
5.3.4 Robot Attaining User Goal
5.4 Results and Discussion
5.5 Conclusion
References
6. Healthcare Robots Enabled with IoT and Artificial Intelligence for Elderly Patients
6.1 Introduction. 6.1.1 Past, Present, and Future
6.1.2 Internet of Things
6.1.3 Artificial Intelligence
6.1.4 Using Robotics to Enhance Healthcare Services
6.2 Existing Robots in Healthcare
6.3 Challenges in Implementation and Providing Potential Solutions
6.4 Robotic Solutions for Problems Facing the Elderly in Society. 6.4.1 Solutions for Physical and Functional Challenges
6.4.2 Solutions for Cognitive Challenges
6.5 Healthcare Management. 6.5.1 Internet of Things for Data Acquisition
6.5.2 Robotics for Healthcare Assistance and Medication Management
6.5.3 Robotics for Psychological Issues
6.6 Conclusion and Future Directions
References
7. Robotics, AI, and the IoT in Defense Systems
7.1 AI in Defense. 7.1.1 AI Terminology and Background
7.1.2 Systematic Sensing Applications
7.1.3 Overview of AI in Defense Systems
7.2 Overview of IoT in Defense Systems
7.2.1 Role of IoT in Defense
7.2.2 Ministry of Defense Initiatives
7.2.3 IoT Defense Policy Challenges
7.3 Robotics in Defense
7.3.1 Technical Challenges of Defense Robots
7.4 AI, Robotics, and IoT in Defense: A Logical Mix in Context. 7.4.1 Combination of Robotics and IoT in Defense
7.4.2 Combination of Robotics and AI in Defense
7.5 Conclusion
References
8. Techniques of Robotics for Automation Using AI and the IoT
8.1 Introduction
8.2 Internet of Robotic Things Concept
8.3 Definitions of Commonly Used Terms
8.4 Procedures Used in Making a Robot. 8.4.1 Analyzing Tasks
8.4.2 Designing Robots
8.4.3 Computerized Reasoning
8.4.4 Combining Ideas to Make a Robot
8.4.5 Making a Robot
8.4.6 Designing Interfaces with Different Frameworks or Robots
8.5 IoRT Technologies
8.6 Sensors and Actuators
8.7 Component Selection and Designing Parts
8.7.1 Robot and Controller Structure
8.8 Process Automation
8.8.1 Benefits of Process Automation
8.8.2 Incorporating AI in Process Automation
8.9 Robots and Robotic Automation
8.10 Architecture of the Internet of Robotic Things
8.10.1 Concepts of Open Architecture Platforms
8.11 Basic Abilities. 8.11.1 Discernment Capacity
8.11.2 Motion Capacity
8.11.3 Manipulation Capacity
8.12 More Elevated Level Capacities. 8.12.1 Decisional Self-Sufficiency
8.12.2 Interaction Capacity
8.12.3 Cognitive Capacity
8.13 Conclusion
References
9. An Artificial Intelligence-Based Smart Task Responder: Android Robot for Human Instruction Using LSTM Technique
9.1 Introduction
9.2 Literature Review
9.3 Proposed System
9.4 Results and Discussion
9.5 Conclusion
References
10. AI, IoT and Robotics in the Medical and Healthcare Field
10.1 Introduction
10.2 A Survey of Robots and AI Used in the Health Sector
10.2.1 Surgical Robots
10.2.2 Exoskeletons
10.2.3 Prosthetics
10.2.4 Artificial Organs
10.2.5 Pharmacy and Hospital Automation Robots
10.2.6 Social Robots
10.2.7 Big Data Analytics
10.3 Sociotechnical Considerations
10.3.1 Sociotechnical Influence
10.3.2 Social Valence
10.3.3 The Paradox of Evidence-Based Reasoning
10.4 Legal Considerations. 10.4.1 Liability for Robotics, AI and IoT
10.4.2 Liability for Physicians Using Robotics, AI and IoT
10.4.3 Liability for Institutions Using Robotics, AI and IoT
10.5 Regulating Robotics, AI and IoT as Medical Devices
10.6 Conclusion
References
11. Real-Time Mild and Moderate COVID-19 Human Body Temperature Detection Using Artificial Intelligence
11.1 Introduction
11.2 Contactless Temperature
11.2.1 Bolometers (IR-Based)
11.2.2 Thermopile Radiation Sensors (IR-Based)
11.2.3 Fiber-Optic Pyrometers
11.2.4 RGB Photocell
11.2.5 3D Sensor
11.3 Fever Detection Camera
11.3.1 Facial Recognition
11.3.2 Geometric Approach
11.3.3 Holistic Approach
11.3.4 Model-Based
11.3.5 Vascular Network
11.4 Simulation and Analysis
11.5 Conclusion
References
12. Drones in Smart Cities
12.1 Introduction
12.1.1 Overview of the Literature
12.2 Utilization of UAVs for Wireless Network. 12.2.1 Use Cases for WN Using UAVs
12.2.2 Classifications and Types of UAVs
12.2.3 Deployment of UAVS Using IoT Networks
12.2.4 IoT and 5G Sensor Technologies for UAVs
12.3 Introduced Framework. 12.3.1 Architecture of UAV IoT
12.3.2 Ground Control Station
12.3.3 Data Links
12.4 UAV IoT Applications
12.4.1 UAV Traffic Management
12.4.2 Situation Awareness
12.4.3 Public Safety/Saving Lives
12.5 Conclusion
References
13. UAVs in Agriculture
13.1 Introduction
13.2 UAVs in Smart Farming and Take-Off Panel. 13.2.1 Overview of Systems
13.3 Introduction to UGV Systems and Planning
13.4 UAV-Hyperspectral for Agriculture
13.5 UAV-Based Multisensors for Precision Agriculture
13.6 Automation in Agriculture
13.7 Conclusion
References
14. Semi-Automated Parking System Using DSDV and RFID
14.1 Introduction
14.2 Ad Hoc Network
14.2.1 Destination-Sequenced Distance Vector (DSDV) Routing Protocol
14.3 Radio Frequency Identification (RFID)
14.4 Problem Identification
14.5 Survey of the Literature
14.6 PANet Architecture
14.6.1 Approach for Semi-Automated System Using DSDV
14.6.2 Tables for Parking Available/Occupied
14.6.3 Algorithm for Detecting the Empty Slots
14.6.4 Pseudo Code
14.7 Conclusion
References
15. Survey of Various Technologies Involved in Vehicle-to-Vehicle Communication
15.1 Introduction
15.2 Survey of the Literature
15.3 Brief Description of the Techniques. 15.3.1 ARM and Zigbee Technology
15.3.2 VANET-Based Prototype
15.3.2.1 Calculating Distance by Considering Parameters
15.3.2.2 Calculating Speed by Considering Parameters
15.3.3 Wi-Fi–Based Technology
15.3.4 Li-Fi–Based Technique
15.3.5 Real-Time Wireless System
15.4 Various Technologies Involved in V2V Communication
15.5 Results and Analysis
15.6 Conclusion
References
16. Smart Wheelchair
16.1 Background
16.2 System Overview
16.3 Health-Monitoring System Using IoT
16.4 Driver Circuit of Wheelchair Interfaced with Amazon Alexa
16.5 MATLAB Simulations
16.5.1 Obstacle Detection
16.5.2 Implementing Path Planning Algorithms
16.5.3 Differential Drive Robot for Path Following
16.6 Conclusion
16.7 Future Work
Acknowledgment
References
17. Defaulter List Using Facial Recognition
17.1 Introduction
17.2 System Analysis. 17.2.1 Problem Description
17.2.2 Existing System
17.2.3 Proposed System
17.3 Implementation. 17.3.1 Image Pre-Processing
17.3.2 Polygon Shape Family Pre-Processing
17.3.3 Image Segmentation
17.3.4 Threshold
17.3.5 Edge Detection
17.3.6 Region Growing Technique
17.3.7 Background Subtraction
17.3.8 Morphological Operations
17.3.9 Object Detection
17.4 Inputs and Outputs
17.5 Conclusion
References
18. Visitor/Intruder Monitoring System Using Machine Learning
18.1 Introduction
18.2 Machine Learning
18.2.1 Machine Learning in Home Security
18.3 System Design
18.4 Haar-Cascade Classifier Algorithm
18.4.1 Creating the Dataset
18.4.2 Training the Model
18.4.3 Recognizing the Face
18.5 Components
18.5.1 Raspberry Pi
18.5.2 Web Camera
18.6 Experimental Results
18.7 Conclusion
Acknowledgment
References
19. Comparison of Machine Learning Algorithms for Air Pollution Monitoring System
19.1 Introduction
19.2 System Design
19.3 Model Description and Architecture
19.4 Dataset
19.5 Models
19.6 Line of Best Fit for the Dataset
19.7 Feature Importance
19.8 Comparisons
19.9 Results
19.10 Conclusion
References
20. A Novel Approach Towards Audio Watermarking Using FFT and CORDIC-Based QR Decomposition
20.1 Introduction and Related Work
20.2 Proposed Methodology
20.2.1 Fast Fourier Transform
20.2.2 CORDIC-Based QR Decomposition
20.2.3 Concept of Cyclic Codes
20.2.4 Concept of Arnold’s Cat Map
20.3 Algorithm Design
20.4 Experiment Results
20.5 Conclusion
References
21. Performance of DC-Biased Optical Orthogonal Frequency Division Multiplexing in Visible Light Communication
21.1 Introduction
21.2 System Model. 21.2.1 Transmitter Block
21.2.2 Receiver Block
21.3 Proposed Method
21.3.1 Simulation Parameters for OptSim
21.3.2 Block Diagram of DCO-OFDM in OptSim
21.4 Results and Discussion
21.5 Conclusion
References
22. Microcontroller-Based Variable Rate Syringe Pump for Microfluidic Application
22.1 Introduction
22.2 Related Work
22.3 Methodology
22.3.1 Hardware Design
22.3.2 Hardware Interface with Software
22.3.3 Programming and Debugging
22.4 Result
22.5 Inference
22.5.1 Viscosity (η)
22.5.2 Time Taken
22.5.3 Syringe Diameter
22.5.4 Deviation
22.6 Conclusion and Future Works
References
23. Analysis of Emotion in Speech Signal Processing and Rejection of Noise Using HMM
23.1 Introduction
23.2 Existing Method
23.3 Proposed Method
23.3.1 Proposed Module Description
23.3.2 MFCC
23.3.3 Hidden Markov Models
23.4 Conclusion
References
24. Securing Cloud Data by Using Blend Cryptography with AWS Services
24.1 Introduction
24.1.1 AWS
24.1.2 Quantum Cryptography
24.1.3 ECDSA
24.2 Background
24.3 Proposed Technique
24.3.1 How the System Works
24.4 Results
24.5 Conclusion
References
Index
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