Search

Browse Subject Areas

For Authors

Submit a Proposal

Digital Cities

Edited by O.V. Gnana Swathika & K. Karthikeyan
Copyright: 2025   |   Expected Pub Date:2025//
ISBN: 9781394233793  |  Hardcover  |  
646 pages
Price: $225 USD
Add To Cart

One Line Description
Drawing on real-world case studies and expert insights, Digital Cities is an essential guide for anyone looking to understand and navigate the innovative technologies that are shaping the future of urban planning in a rapidly changing world.

Audience
Students, educators, researchers, and industry professionals interested in the role of smart technologies in the future of city planning

Description
In the era of high urbanization, there is a rapid shift in people’s demands and needs for housing and accommodations. These demands require city planners to create technology-friendly and future-looking designs for the world’s growing population. The concept of the smart city combines the principle of sustainability with optimal utilization of resources to help reduce overconsumption of resources, ensuring these necessities for future generations. However, this concept has bombarded the market with an exponentially growing number of applications and technologies across many sectors affecting our daily lives, such as surveillance, HVAC, security, and emergency response. Digital Cities uses real-world cases studies and expert insights to comprehensively explore the innovative technologies changing the landscape of smart city planning.

Back to Top
Author / Editor Details
O. V. Gnana Swathika, PhD is an associate professor in the Center for Smart Grid Technologies in the School of Electrical Engineering at the Vellore Institute of Technology. She has over 180 publications to her credit, including book chapters and articles in national and international journals and conferences. Her current research interests include microgrid protection and energy management systems.

K. Karthikeyan is the Chief Engineering Manager of Electrical Designs for Larsen and Toubro Construction, a multinational Indian contracting company, with over two decades of experience in electrical design. His primary role involves preparing and reviewing complete electrical system designs up to 110KV voltage levels and acting as the point of contact for both the client and internal project team. He has contributed immensely tothe building services sector, working in airports, railway stations, hospitals, and educational institutions in India, as well as Sri Lanka, Dubai, and the UK.

Back to Top

Table of Contents
Preface
1. AI Revolution in Healthcare: Digital Health Services Empowered by Machine Learning and Deep Learning

Mudiyala Aparna, Battula Srinivasa Rao and Mallela Siva Naga Raju
1.1 Introduction
1.2 Background and Motivation
1.3 AI Challenges and Opportunities in Digital Health Services
1.3.1 Empowering Healthcare through Machine Learning
1.3.2 Challenges
1.3.3 Unleashing Deep Learning’s Potential
1.3.4 The Nexus of Machine Learning and Deep Learning
1.4 Navigating Challenges and Opportunities
1.4.1 Challenges in Digital Health
1.4.2 Opportunities in Digital Health
1.4.3 Future Horizons
1.5 Conclusion
References
2. A Multi-Layered Approach for Combatting Misinformation on Online Social Media
Maitreyee Ganguly and Paramita Dey
2.1 Introduction
2.2 Literature Survey
2.3 Methodology
2.3.1 Available Datasets
2.3.2 Data Preprocessing
2.3.3 Classifiers
2.4 Discussion and Future Directions
References
3. Analysis on Political Lenience Using Adaptive Multi-Label Learning for Online Social Network Data
VenkataRamana Mancha, N. Pushpalatha, Naga Jyothi P. and S. Suresh
3.1 Introduction
3.1.1 Basic Preliminaries
3.2 Novel Active Learning-Based Multi-Labeled Categorization Procedure
3.3 Empirical Results
3.3.1 Collection of Data Set
3.3.2 Experimental Setting
3.4 Conclusion
References
4. Smart Pharma Packaging Using IoT
Tata Srivatsava and L. Premalatha
4.1 Introduction
4.2 Block Diagram and Methodology
4.3 Simulation of the Proposed Work
4.4 Hardware Results
4.5 Conclusion
References
5. IoT-Based Smart Driver Safety Device
Ratan Pyla, G. Gugapriya and P. Jeevan Narayana Raju
5.1 Introduction
5.2 Recent Developments in IoT-Driven Driver Safety Systems
5.3 Building an IoT-Driven Smart Driver Safety Device
5.3.1 Block Diagram
5.3.2 Software Architecture
5.3.2.1 Distracted Driver Detection
5.3.2.2 Closest Object Detection
5.3.2.3 Overview
5.4 Design and Implementation: A Dual-Module Approach
5.4.1 Smart Distracted Driver Alert System
5.4.2 Pothole Detection System
5.5 Results and Discussions
5.5.1 Unveiling the IoT-Driven Driver Safety System’s Efficacy
5.5.2 Distracted Driver Alert System
5.5.3 Object Detection Module
5.5.4 Pothole Detection System
5.5.5 Conclusive Reflections
References
6. IoT-Based Sustainable Homes Aided with the Smart Sewage Monitoring System
V. Ananthakrishnan, Dixshant Kumar Jha, Abhishek Kishor, Ashutosh Dwivedi, Jeet Tiwari, Tritoy Mohanty, Aryan Dash, P. Balamurugan, Sitharthan Ramachandran and O.V. Gnana Swathika
6.1 Introduction
6.2 Methodology
6.2.1 Arduino UNO
6.2.2 DS18B20 Model Temperature Sensor
6.2.3 Analog pH Sensor via Gravity
6.2.4 Node MCU
6.2.5 Soil Moisture Sensor
6.3 Results And Discussion
6.4 Conclusion
References
7. Securing Industrial Data Using AI/ML
V. Anantha Krishnan, Anushka Sharma, Akshat Saxena, Amogh Tripathi, Rohan Daga, Sitharthan Ramachandran and O.V. Gnana Swathika
7.1 Introduction
7.2 Literature Survey
7.3 Methodology
7.4 Simulation Results
7.5 Conclusion
Bibliography
8. MediSync Guardian: An IoT-Based Smart Medicine Box to Provide Smart Healthcare Service
Smita Kapse, Gunjan Balpande, Shravani Kale, Manthan Jadhav, Vikrant Jaunjale and Sahil Lawankar
8.1 Introduction
8.2 Related Work
8.3 Proposed Methodology
8.4 Conclusion
References
9. Deep Learning Application on Smart City
Hemang A. Thakar
9.1 Introduction
9.2 Methodology
9.3 Deep Learning Background
9.3.1 Taxonomy in Deep Learning
9.3.2 Motivation for Deep Learning
9.3.3 Benefits of Deep Learning
9.4 Incentives and Benefits of Applying Deep Learning in Smart Cities Compared to Conventional Approaches
9.5 The Concept and Framework of Smart City Endeavors
9.6 Utilizing Deep Learning in Smart Urban Environments
9.7 Comprehensive Examination of Deep Learning Applications in Smart Urban Environments
9.7.1 Transportation and Mobility
9.7.2 Energy Management
9.7.3 Public Safety and Security
9.7.4 Urban Planning and Infrastructure
9.7.5 Healthcare
9.7.6 Waste Management
9.7.7 Water Management
9.7.8 Governance and Citizen Engagement
9.7.9 Education and Innovation
9.7.10 Economic Development
9.8 Application Domains in Smart Cities
9.9 Challenges and Future Research Opportunities in Deep Learning Applications for Smart Cities
9.9.1 Data Privacy and Security
9.9.2 Data Quality and Heterogeneity
9.9.3 Resource Constraints
9.9.4 Interpretable Models
9.9.5 Adaptability to Dynamic Environments
9.9.6 Ethical and Social Considerations
9.9.7 Future Research Opportunities
9.10 Conclusion
References
10. Diabetic Retinopathy Detection Using SVM
Sharvari Natekar, Anushka Singh, Neeraja Pillai and Hannah Grace G.
10.1 Introduction
10.1.1 Diabetic Retinopathy
10.1.2 SVM (Support Vector Machine)
10.1.3 Random Forest
10.2 Literature Survey
10.3 Dataset Description
10.4 Methodology
10.4.1 Data Preprocessing
10.4.2 SVM
10.4.3 SVM with Random Forest
10.4.4 SVM with Naïve Bayes Classifier
10.4.5 SVM with KNN
10.4.6 SVM with LDA
10.5 Results
10.6 Prediction
10.7 Conclusion
References
11. Secure Digital Health Data Transmission in Healthcare Industry 4.0—An Overview
Dhivya Ravichandran, W. Sylvia Jebarani, Amrutha Gopinath, Chanthini Baskar and Amirtharajan Rengarajan
11.1 Introduction
11.2 Security and Privacy Issues in e-Healthcare
11.3 Security Requirement
11.4 Security Solutions for e-Healthcare 4.0
11.4.1 Wearable Device-Based Solutions for e-Healthcare 4.0
11.4.2 Machine Learning-Based Solutions for e-Healthcare 4.0
11.4.3 IoT-Based Solutions for e-Healthcare 4.0
11.4.3.1 Keyed Technique
11.4.3.2 Keyless Schemes
11.4.3.3 Blockchain-Based Schemes
11.4.3.4 Proxy-Based Schemes
11.4.3.5 Biometrics-Based Schemes
11.4.4 Processing-Based Solutions for e-Healthcare 4.0
11.5 Conclusion
References
12. Emotion Detection System Using Skin Temperature and Heartbeat for Healthcare Applications
Niveditha Sivan, Ganti Venkata Varshini, Annsley Mohan Joseph, V. Berlin Hency and Shola Usharani
12.1 Introduction
12.2 Literature Survey
12.3 Proposed System
12.4 Implementation Details
12.4.1 Hardware
12.4.2 Software
12.5 Result and Discussion
12.6 Conclusion and Future Work
References
13. Role of Sensors in Food Quality Monitoring
Alapati Hemalatha, Ankith S. R., Lakshmi Priya G., Chanthini Baskar and Dhivya Ravichandran
13.1 Introduction
13.2 Literature Survey
13.3 Data Analytics in Food Quality Analysis
13.3.1 Supervised
13.3.2 Unsupervised
13.3.3 Reinforcement
13.4 Conclusion
References
14. Sustainable Social, Environmental, and Economic Developments Based on Digital Systems
Akhil Nigam
14.1 Introduction
14.2 Challenges of Social, Environmental, and Economic Development
14.3 Impact of Digital Systems on Sustainable Development
14.4 Role of Digital Systems in Social Development
14.5 Role of Digital Systems in Environmental Development
14.6 Role of Digital Systems in Economic Development
14.7 Impact of AI on Sustainable Development
References
15. Machine Learning and Image Processing Based Leaf Disease Detection System
V. Anantha Krishnan, P. Balamurugan, Sitharthan Ramachandran and O.V. Gnana Swathika
15.1 Introduction
15.2 Literature Survey
15.3 Methodology
15.4 Simulation Results
15.5 Conclusion
References
16. Heart Rate Monitoring System Using IoT: Hardware Implementation and Data Storage in Django
Sritama Roy
16.1 Introduction
16.2 Problem Statement
16.3 System Architecture
16.4 Hardware Components
16.4.1 Heart Rate Sensor
16.4.2 Microcontroller (IoT device)
16.4.3 Connectivity Module (e.g., Wi-Fi, Bluetooth)
16.5 Software Components
16.5.1 IoT Firmware and Communication Protocols
16.5.2 Django Web Framework
16.5.3 Database Management System
16.6 Heart Rate Monitoring Algorithm
16.7 Data Acquisition from the Heart Rate Sensor
16.8 Signal Processing and Filtering
16.9 Real-Time Heart Rate Calculation
16.10 Alerting Mechanism for Abnormal Heart Rates
16.11 IoT Data Communication and Storage
16.12 Data Transmission to Django Server
16.13 Data Security and Privacy Measures
16.14 Data Storage and Organization in Django
16.15 User Access and Authentication
16.16 Django Web Interface
16.17 Dashboard for Real-Time Monitoring
16.18 Historical Data Visualization
16.19 User Management and Roles
16.20 Alerts and Notifications
16.21 System Implementation
16.22 Hardware Setup and Integration
16.23 IoT Firmware Development
16.24 Django Application Development
16.25 Testing and Validation
16.26 Performance Evaluation
16.27 Data Accuracy and Reliability
16.28 Real-Time Responsiveness
16.29 Scalability and Performance of the Django Backend
16.30 Future Enhancements
16.30.1 Advanced Analytics
16.30.2 Integration with Wearable Devices
16.30.3 Cloud-Based Storage and Analysis
16.30.4 Real-Time Data Analytics
16.30.5 Enhanced Security Measures
Conclusion
References
17. IoE-Based Smart Cities: Challenges and Future Trends
Anjan Kumar Sahoo and Girija Sankar Panigrahi
17.I Introduction
17.2 Literature Review
17.3 Research Methodology
17.4 Challenges
17.5 Future Trends
17.6 Conclusion
References
18. Digital Systems as Transformative Agents of Change to Measure Economic Development and Social Inclusion
Luke Gerard Christie and Snegha Priya
18.1 Introduction
18.2 Seminal Observations of the Benefits of Digital Systems
18.3 Organizational and Technological Innovation – A Brief Observation
18.4 Science and Technology in India
18.5 Research and Development on Technology in India
18.6 New-Age Technology Investments and Setting Up of Advanced R&D Facilities
18.7 Conclusion
Bibliography
19. Maze Solver Robot Using a Wi-Fi Module
Ayush, Akshat Singh, Abhishek Misra and Sritama Roy
19.1 Introduction
19.2 System Architecture
19.3 Software Implementation
19.4 Proposed Methedology
19.5 Results and Analysis
Conclusion
References
20. ParkPilot—An Automated Parking System with Automatic Number Plate Detection
S. Pranaav, M.S. Bhuvan Raj, K. Gowtham Baalaji and V. Berlin Hency
20.1 Introduction
20.2 Literature Review
20.3 Methodology
20.4 Observations
20.5 Results
20.6 Conclusion
References
21. Fingerprint-Based Door Automation System Using RFID and Bluetooth
Sritama Roy
21.1 Introduction
21.2 Components and Hardware
21.3 Computing Concepts and Methodology
21.4 Software Representation and Development
21.5 Results and Discussion
Conclusion
References
22. A Review of Deep Learning Approaches in Smart City Applications
Senthil Kumar Paramasivan and Siva Sankari Subbiah
22.1 Introduction
22.2 Research Perspective on Smart City Applications
22.3 Sensors in Smart City Infrastructure
22.4 Applications of Deep Learning Approaches in Smart Cities
22.5 Conclusion
References
23. Smartphone-Based Train Safety Mechanism Using Sensor Data Analysis
Doreen Dilip and Sritama Roy
23.1 Introduction
23.2 System Architecture
23.3 Sensor Data Analysis
23.4 Communication and Alert Mechanism
23.5 Experimantal Setup and Results
23.6 Discussion
Conclusion
References
24. The Role of AI and Big Data Analytics in Smart Cities: Leveraging Digital Platforms, Cloud Computing, and IoT
Vikas Sharma, Tarun Kumar Vashishth, Kewal Krishan Sharma,Sachin Chaudhary, Bhupendra Kumar and Rajneesh Panwar
24.1 Introduction
24.1.1 The Essence of Smart Cities: A New Paradigm for Urban Development
24.1.2 AI: The Intelligent Catalyst
24.1.3 Big Data Analytics: Unveiling Insights in the Data Deluge
24.1.4 The Confluence of AI and Big Data: A Transformative Synergy
24.2 Understanding Smart Cities in the Digital Era
24.2.1 Optimizing Resource Allocation
24.2.2 Enhancing Operational Efficiency
24.2.3 Enhancing Quality of Life
24.3 The Confluence of AI, Big Data, and IoT
24.3.1 Proliferation of IoT Devices and Data Collection
24.3.2 IoT’s Role in Connectivity and Data Generation
24.3.3 AI and Big Data Analytics: Extracting Insights from Complexity
24.3.4 Synergy in Action: Uncovering Insights for Smart Cities
24.3.5 Empowering City Stakeholders
24.4 Literature Review
24.5 Empowering Decision-Making through Data Analytics
24.5.1 Unleashing Insights from Massive Datasets
24.5.2 Identifying Trends, Correlations, and Anomalies
24.5.3 Predictive Analytics: Shaping the Future
24.5.4 Efficient Energy Usage: A Case Study
24.6 AI’s Role in Enabling Smart Services
24.6.1 Enhancing Engagement with Chatbots and Virtual Assistants
24.6.2 Personalization through Recommendation Systems
24.6.3 Anticipating Needs with Predictive Analytics
24.6.4 Striking a Balance: Privacy and Transparency
24.7 Cloud Computing as the Backbone of Smart Cities
24.7.1 Scalability and Computational Prowess
24.7.2 Real-Time Data Analysis and Storage
24.7.3 Seamless Collaboration and Integration
24.7.4 Enhanced Disaster Recovery Capabilities
24.8 Ensuring Privacy and Security
24.8.1 The Challenge of Data Privacy and Cybersecurity
24.8.2 The Role of AI and Big Data in Privacy Concerns
24.8.3 Ensuring Privacy and Security: Encryption and Anonymization
24.8.4 Transparent Data Governance and Public Trust
24.9 Towards Inclusive and Sustainable Smart Cities
24.9.1 Understanding Inclusion and Sustainability
24.9.2 Data Insights for Inclusion
24.9.3 Optimizing Resource Utilization for Sustainability
24.9.4 Smart Mobility for Accessibility
24.9.5 Balancing Growth and Equitability
24.10 Future Directions and Challenges
24.10.1 Future Directions
24.10.2 Challenges to Address
24.11 Conclusion
References
25. Urbiverse: A Metaverse Environment for Future Digital Cities and Digital Urban Services
Robertas Damasevicius
25.1 Introduction
25.2 The Urbiverse: A Metaverse Environment for Digital Cities
25.2.1 Definition and Characteristics of Urbiverse
25.2.2 Technologies Powering the Urbiverse
25.2.3 Potential Impact of Urbiverse on Urban Life
25.3 Transforming Digital Urban Services through Urbiverse
25.3.1 Digital Health Services in Urbiverse
25.3.2 Digital Education Services in Urbiverse
25.3.3 Digital Transportation Services in Urbiverse
25.3.4 Digital Waste Management in Urbiverse
25.3.5 Identification and Suppression of Dissenters in Urbiverse
25.4 Role of Stakeholders in Shaping the Urbiverse
25.4.1 City Planners
25.4.2 Policymakers
25.4.3 Citizens
25.5 Conclusion
References
26. Transforming Healthcare: Digital Health Services Empowered by Deep Learning
Mallela Siva Naga Raju, Battula Srinivasa Rao and Mudiyala Aparna
26.1 Introduction
26.2 The Role of Deep Learning in Healthcare
26.2.1 Diagnosis and Disease Prediction
26.2.2 Drug Discovery and Treatment Optimization
26.2.3 Genomic Medicine
26.2.4 Natural Language Processing and Electronic Health Records
26.3 Remote Patient Monitoring and Telemedicine
26.3.1 Remote Patient Monitoring
26.3.2 Telemedicine and Virtual Health Assistants
26.4 Future Directions and Challenges
26.5 Conclusion
References
27. Digital Waste Management
Srividya P. and Siddharth A.
27.1 Introduction to Waste Management
27.2 Solid Waste Management
27.2.1 Components Involved in Solid Waste Management System
27.2.2 Common Solid Waste Disposal Methods
27.3 Liquid Waste Management
27.3.1 Common Liquid Waste Disposal Methods
27.4 Gaseous Waste Management
27.4.1 Gaseous Waste Management Methods
27.5 Residential and Municipal Smart Solid Waste Management and Segregation System
27.5.1 Waste Collection and Initial Level of Segregation
27.5.2 Waste Segregation at the Disposal Location
27.6 Conclusion
References
28. Advancing Healthcare in Smart Cities: A Comprehensive Understanding of Knowledge Graphs for Enhanced Efficiency and Future Innovations
Shridevi S., Vishakhavel Shanmuganathan, Masooma Aliraza Suleman and Ratan Pyla
28.1 Introduction
28.2 The Breakdown of the Chapter
28.3 Q1-Related Works
28.4 Q2-Related Works
28.4.1 Problem Description and Model Overview
28.4.2 Building the Knowledge Graph and Knowledge Retrieval Framework
28.4.3 Drawing Inference from Semantic Health Knowledge Graph
28.5 Q3-Related Works
28.5.1 Human Annotation
28.5.2 Partial Gold Standard
28.5.3 Knowledge Graph as Silver Standard
28.6 Discussion
28.6.1 KG Data Quality, Privacy, and Credibility
28.6.2 Knowledge Resources and Expansion
28.6.3 KG Construction Algorithms
28.6.4 Time-Aware KG
28.6.5 KG Evaluation in the Healthcare Sector
28.6.6 Performance Evaluation of BIG Healthcare KG
28.6.7 Room for Further Research in Healthcare Knowledge Graphs
28.7 Conclusion
References
29. An Automated Challan Generation System Leveraging Deep Neural Networks for Precise Violation Detection and License Plate Recognition
S. Sravanth, E. Shamitha, M. Venkat Sai and Y. Raju
29.1 Introduction
29.2 Methodology
29.2.1 Basic Flow
29.2.2 Violation Detection
29.2.3 License Plate Detection
29.2.4 Character Detection
29.2.5 Optical Character Recognition
29.2.6 Challan Generation
29.3 Comparison of Existing Models
29.4 Conclusion
Bibliography
30. Real-Time Detection and Alert System for Potholes and Speed Breakers
Kandkkekaar SaiTej, Palakura Rithika, Vennam Mahesh and Yeligeti Raju
30.1 Introduction
30.1.1 Problem Statement
30.1.2 Objectives
30.2 Literature Review
30.3 Data Collection and Preprocessing
30.3.1 Dataset Collection
30.3.2 Annotation Process
30.3.3 Dataset Preprocessing
30.3.4 Dataset Split
30.4 Methodology
30.4.1 Model Training and Evaluation
30.4.2 Data Integration
30.4.3 Map API Integration
30.4.4 Live Location Tracking
30.4.5 Alert Mechanism
30.4.6 User Interface
30.4.7 Data Privacy and Security
30.5 Implementation Process
30.5.1 Machine Learning Model Integration
30.5.2 Accuracy Assessment
30.5.3 Map API Integration
30.5.4 Real-Time Tracking
30.5.5 Alert Mechanism
30.5.6 User Interface
30.5.7 Data Privacy and Security
30.5.8 Testing and Quality Assurance
30.6 Results and Impact
30.6.1 Accident Reduction
30.6.2 Improved Driving Habits
30.6.3 Enhanced Traffic Flow
30.6.4 Data-Driven Road Maintenance
30.6.5 Limitations and Challenges
30.7 Conclusion
Bibliography
31. Context-Aware Suicide Rate Prediction for Significant Mental Health Monitoring in Smart Cities
Aravinda Boovaraghavan, V. Maheysh, Anova Pandey, Christy Jackson J. and Abraham Sudharson Ponraj
31.1 Introduction
31.2 Literature Survey
31.3 Problem Statement
31.4 Proposed Methodology
31.5 Analysis of Results
31.5.1 Data Cleaning
31.5.2 Data Visualization
31.5.3 Machine Learning
31.6 Conclusion and Future Work
References
32. Cyberattack on Smart Cities: A Digital Approach
Adarsh Mohapatra, Amit Hota, Bhupesh Singh Kushwaha, Mridulay Dixit, Utkarsh Rajesh and O.V. Gnana Swathika
32.1 Introduction
32.2 Comprehensive Insights into Cyber Threat, Privacy and Development Challenges in Smart Cities
32.2.1 Cyberattack Prediction and Countermeasures
32.2.2 Smart City Cybersecurity and Privacy Challenges
32.2.3 IoT and Smart Cities
32.2.4 Comprehensive Studies and Assessments
32.2.5 Future Challenges and Consideration in Smart Cities
32.3 Investigating Cyber Threat Identification Techniques and Adaptive Cybersecurity Strategies in Smart City
32.3.1 Uncovering Cyber Threats and Crafting Effective Solutions in Smart Cities
32.3.2 Securing Smart City and Internet of Things Environments: Cyber and Survey, Resilience and Solutions
32.3.3 Enhancing Cybersecurity in Smart Cities: Challenges, Strategies and Future Directions
32.4 Emerging Technological Solutions for Cyber-Related Issues in Smart Cities: Blockchain and CPS
32.4.1 Blockchain Technology
32.4.1.1 Introduction
32.4.1.2 Applications
32.4.1.3 Challenges
32.4.1.4 Technological Developments in Cybersecurity Using Blockchain
32.4.2 Cyber-Physical Systems (CPSs)
32.4.2.1 Introduction
32.4.2.2 Applications
32.4.2.3 Challenges
32.4.2.4 Technological Developments in Cybersecurity Using CPS
32.5 Cybersecurity Using AI, ML and Deep Learning
32.5.1 Introduction
32.5.2 Methods of Detection for Cyberattacks
32.5.3 Deep Learning Methods for Enhancing Cybersecurity in Various Scenarios
32.5.4 Role Use of AI in Smart Cities
32.5.5 Applications
32.6 Conclusion
References
33. Exploring Emerging Frontiers in Optical Communication: A Comprehensive Review
Kasthuri P., Sowmyaa Vathsan M.S., Prakash P. and Sasithradevi A.
33.1 Introduction
33.2 Historical Developments of Optical Communication
33.2.1 Wavelength Division Multiplexing
33.2.2 Radio-over-Fiber (RoF)
33.2.3 Optical Modulation Techniques
33.3 Recent Trends on Optical Communication
33.3.1 Data Center and Photonic Switches
33.3.2 Comb Lasers
33.3.3 FSO/RF System
33.4 Machine Learning/Deep Learning in Optical Communication
33.4.1 Machine Learning Techniques
33.4.2 Quantum Key Distribution (QKD) in FSO/Fiber Communication
33.5 Conclusion
References
34. Improving Occupant Comfort through Real-Time Predictive Control of Indoor Environment Using the Predicted Mean Vote Model and MLP
Madhan Kumar S., Yaswanth Kannan G., Kavin Krishna K. and Berlin Hency V.
34.1 Introduction
34.2 Literature Review
34.3 Methodology
34.4 Experiments and Results
34.5 Conclusion
Acknowledgments
References
35. Recognizing Real-Time Objects Using Yolov5
Dayance, Swetha S. and Hannah Grace G.
35.1 Introduction
35.2 Literature Review
35.3 Research Methodology
35.4 Result and Discussion
35.5 Conclusion
References
36. Aesthetic Vision and User Engagement: Illuminating the Role of Aesthetics in Digital City Planning
Andrew Veda W.S. and Luke Gerard Christie
36.1 Introduction
36.2 Objective Elements in Urban Spaces—Physical City and Digital Twin City
36.3 Aesthetic Usability Effect
36.4 Continuous Aesthetic Evaluation
36.5 Buildings
36.6 Roads
36.7 Digital Design
36.8 Gestalt Aesthetics
36.8.1 Proximity
36.8.2 Similarity
36.8.3 Continuity
36.8.4 Closure
36.8.5 Figure-Ground Perception
36.9 Privacy Risks
36.10 Conclusion
References
Index

Back to Top



Description
Author/Editor Details
Table of Contents
Bookmark this page