Table of Contents
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PREFACE
List of Contributors
Investigating the Features of Physical Layer Structure for Employment of Smart City Models
Abstract
1. INTRODUCTION
2. FUTURE OF DHOLERA SIR SMART CITY
3. DEVELOPMENT OF DHOLERA SIR
4. EMPLOYMENT FRAMEWORK IN DHOLERA
5. FUTURISTIC OPTIONS
6. PROGRAM CODE
CONCLUSION
REFERENCES
Pithy & Comprehensive Review of Practical and Literal Models
Abstract
1. INTRODUCTION
2. COMPREHENSIVE ANALYSIS OF PREVIOUS WORKS
3. SMART CITY COMPONENTS
3.1. Smart Agriculture
3.2. Smart City Services
3.3. Smart Energy
3.4. Smart Health
3.5. Smart Home
3.6. Smart Industry
3.7. Smart Infrastructure
3.8. Smart Transportation
4. INTERNET OF THINGS (IOT) FOR SMART CITIES (SCS)
4.1. IoT Architectures for SCs
5. STATE OF THE ART: SMART CITY (SC) MODELS
6. THE CASE OF VIENNA
6.1. Subsystems and Stakeholders in the Vienna Smart City Initiative
6.2. Vienna Smart City Projects and Dimensions
6.3. Global Trends and Urban Challenges for Vienna
6.4. Global Vision and Guidelines
CONCLUSION AND FUTURE SCOPE
REFERENCES
Categorizing Obstacles in the Implementation of Smart Cities with Probable Solution Models
Abstract
1. INTRODUCTION
1.1. Cloud Computing
1.2. Fog Computing
1.3. Edge Computing
2. COMPREHENSIVE ANALYSIS OF PREVIOUS WORKS
3. WIDE PURVIEW OF PROBLEMS IN SMART CITY
3.1. Technical Challenges in Smart City Plan
3.2. Financial Challenges in Smart City Plan
3.3. Administrative and Governance Challenges in Smart City Plan
3.4. Location Endemic Purview
3.5. Miscellaneous Issues
4. CASE STUDIES
4.1. Fujisawa
4.2. Santander
4.3. Vienna
CONCLUSION AND FUTURE SCOPE
REFERENCES
Understanding the Future of Smart Cities from Technological and Commercial Point of View
Abstract
1. INTRODUCTION
1.1. Components and Characteristic of Smart Cities
1.2. Internet of Things and its Application in Smart Cities
1.3. The Age of Smart Cities
1.4. Smart Cities Mission of India
1.5. Internet of Things (IoT)
1.6. Framework for ROI
1.6.1. Compare ROI of IoT based Projects
1.6.2. Comparing ROI for Different European Countries
1.7. Copenhagen
1.8. Helsinki
1.9. Brussels
1.10. Vienna
1.11. Contribution of Smart Cities in Urbanisation
1.11.1. Better Public Security
1.11.2. Reducing Travel Time
1.11.3. Better Health Care Facilities
1.11.4. Lower Environmental Impact
1.11.5. Smart Cities Can Create Urban Communities
1.12. Smart Cities as a Way of Improving Commercial and Technological Development
1.12.1. Smart Can Provide Better Employment Opportunities to Its Citizens
1.12.2. Smart Cities Open New Avenues for Partnerships Between Government and Private Entities and also Increase Private Sector Participation
1.12.3. Increased Digital Equity
1.12.4. Better Infrastructure
1.12.5. Increasing Workforce Engagement
2. Future Trends of Smart Cities
2.1. Enabling Technologies
2.2. Building and Construction
2.3. Improving Energy Source Management
2.4. Smart Water and Waste Management
Conclusion
REFERENCES
Dynamic Involvement of Deep Learning and Big Data in Smart Cities
Abstract
Introduction
Internet of things (IoT)
Deep Learning
Deep Learning Architecture
Deep Learning Models and Algorithms
Applications of Deep Learning
Use of Deep Learning in Smart City Application
Smart Home
Smart Healthcare
Smart Environment
Smart Transportation
Challenges of Deep Learning in Smart Cities
Future Trends in Smart Cities using Deep Learning
Conclusion
References
IoT Enabled Energy Optimization Through an Intelligent Home Automation
Abstract
1. Introduction
2. Background and Motivation
3. Literature Review
4. Proposed Intelligent Automation System
5. Simulation of an Intelligent Automation System Using Cisco Packet Tracer
5.1. Description of Software
Algorithm
6. Hardware implementation
6.1. Wi-Fi Module Interface Circuit
7. NOVELTY OF THE PROPOSED METHOD
CONCLUSION
References
Garbage Management and Monitoring System Using IOT Applications
Abstract
1. Introduction
2. Literature Survey
3. Proposed System
3.1. Proposed Module-1
3.2. Proposed Module-2
3.2.1. Sensible Dumpsters
3.2.2. Sensor Usage
3.2.3. Wi-Fi Module
3.2.4. Arduino-Uno Controller
3.2.5. Management and Control System
3.2.6. Transport System
3.2.7. Webpage of Garbage Management System
4. Novelty of this Proposed Work
Conclusion
References
Power Generation Prediction in Solar PV system by Machine Learning Approach
Abstract
1. Introduction
2. Related works
3. Issues in Artificial Neural Training
3.1. Weights Initial Value
3.2. Rate of Learning
3.3. Oversampling or Overfitting
3.4. Scaling of the Input
4. Important Elements in Artificial Neural Network (ANN) for PV
4.1. Feed-forward ANN Network
4.2. Feed-backward ANN Network
The Following Algorithm 1 Depicts the Simplified Operation of an ANN
Algorithm 2: Proposed Functionality of PV Prediction System
Machine Learning Algorithm 3
5. Proposed Methodology
5.1. Current Sensing Unit
5.2. Voltage Sensing Unit
5.3. The PV Generation Prediction Process and Implementation with Sensor Outputs
6. Variability in data
6.1. Data Processing
7. Results
7.1. Temperature Values
7.2. Power Generated Values
8. The outcome of this methodology
Conclusion
References
An Efficient Framework and Implementation of a Weather Prediction System
Abstract
1. Introduction
2. Related Works
3. Proposed system
3.1. System Architecture
3.1.1. Node-MCU
3.1.2. DHT22 Humidity Sensors
3.1.3. BMP Sensors
3.1.4. Rain Intrusion Sensors (FC37)
3.2. Artificial Neural Network (ANN) and Components
3.2.1. Variations in ANN
3.2.2. ANN Methodology and its Background
3.2.3. Analytical Eorking of ANN
3.2.4. Types of Manipulation in Intermediate Layers
4. DATA PROCUREMENT AND ANALYSIS
Algorithm 2: Proposed Functionality of Smart Weather Prediction System
5. Hardware Implementation and Sensor Outputs
6. Novelty of this Research Work
Conclusion
References
Hybrid Machine Learning Techniques for Secure IoT Applications
Abstract
1. Introduction
2. ML Algorithm
2.1. Supervised and Unsupervised Learning
3. Introduction to IoT
4. Methods of ML for the Learning
4.1. Improved Understanding Techniques
4.2. Acquiring Implicit Data
4.3. ML and Repetition
5. Models and Methods for Hybrid ML
6. Hybrid Algorithms in IoT Applications
6.1. Energy
6.2. Routing
6.3. In Living
6.4. Industry
7. ML techniques in IoT Security
8. Discussion
Conclusion
REFERENCES
Pragmatic Internet of Everything (IOE) for Smart Cities: 360-Degree Perspective
Edited by
Satya Prakash Yadav
Department of Computer Science and Engineering
GL Bajaj Institute of Technology and Management
India
Graduate Program in Telecommunications Engineering (PPGET)
Federal Institute of Education, Science and Technology of Ceará (IFCE)
Brazil
Sansar Singh Chauhan
Department of Computer Science & Engineering
Noida Institute of Engineering & Technology
India
Sanjeev Kumar Pippal
NSBT MGM University, Cidco, Aurangabad
Maharashtra 431003
India
&
Victor Hugo C. de Albuquerque
Department of Teleinformatics Engineering (DETI) Federal University of Ceará
Brazil
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PREFACE
Pragmatic Internet of Everything (IOE) for Smart Cities: 360-degree perspective has emerged as a powerful paradigm for representing and solving complex problems. Pragmatic Internet of Everything (IOE) for Smart Cities: 360-degree perspective is the branch of Internet of Everything (IOE) concerned with coordinating behaviour among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives.
The inspiration and need for this book specifically on smart cities arose due to the sheer absence of any literature which amalgamates different perspectives, thereby giving a 360 degree perspective to the reader, even though there is plenty of literature available on the topic. An insight from subject matter experts from various vivid fields will not only substantiate the knowledge on the subject but, also give some inputs towards the implementation of practical ventures of the same. This process not only included excessive research and review of available literature and practical ventures but also included extensive surveys to get the gist of the topic from citizens of smart cities, along with the analysis of the same from a financial or business perspective and using policymakers’ mind to optimize the same.
This book presents a collection of articles surveying several major recent developments in the Pragmatic Internet of Everything (IOE) for Smart Cities: 360-degree perspective. The book focuses on issues and challenges that arise in building practical Internet of Everything (IOE) for Smart Cities systems in real-world settings, and covers some solutions to the issues faced. It provides a synthesis of recent thinking, both theoretical and applied, on major problems of the Internet of Everything (IOE).
Satya Prakash Yadav
Department of Computer Science and Engineering
GL Bajaj Institute of Technology and Management
India
Graduate Program in Telecommunications Engineering (PPGET)
Federal Institute of Education, Science and Technology of Ceará (IFCE)
BrazilSansar Singh Chauhan
Department of Computer Science & Engineering
Noida Institute of Engineering & Technology
IndiaSanjeev Kumar Pippal
NSBT MGM University, Cidco, Aurangabad
Maharashtra 431003
India
&Victor Hugo C. de Albuquerque
List of Contributors
Arushi KapoorRobert R Mcormick School of Engineering and Applied Science, Northwestern University, Illinois, United StatesArushi KapoorDepartment of Biotechnology, Amity Institute of Biotechnology, Amity University, Noida, IndiaA. KumaraswamySri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, IndiaChandra Sekhar KolliDepartment of Computer Science, Gandhi Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, IndiaC. MuruganandamDepartment of Computer Science, AVVM Sri Pushpam College, Affiliated to Bharathidasan University, Poondi, Thanjavur, Tamil Nadu - 613503, IndiaDimitrios A. KarrasNational and Kapodistrian University of Athens (NKUA), Hellas, GreeceDebajit MishraDepartment of Ocean Studies & Marine Biology, Pondicherry University, Port Blair Campus, IndiaG. HarishDepartment of Computer Science & Engineering, Dr. Ambedkar Institute of Technology, Mallathahalli, Bangalore, Karnataka - 560056, IndiaJ. Viswanatha RaoVNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, IndiaK. N. AshaDepartment of Computer Science & Engineering, Dr. Ambedkar Institute of Technology, Mallathahalli, Bangalore, Karnataka - 560056, IndiaK. P. Asha RaniDepartment of Computer Science & Engineering, Dr. Ambedkar Institute of Technology, Mallathahalli, Bangalore, Karnataka - 560056, IndiaK. R. SwethaDepartment of CSE, BGS Institute of Technology, Adichunchanagiri University, Mandya, Karnataka, IndiaMuskan JindalDepartment of Computer Science, Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, IndiaMahaveer Singh NarukaG.L. Bajaj Institute of Technology and Management, Greater Noida, U.P, IndiaMuskan JindalAmity School of Engineering and Technology, Noida, Uttar Pradesh, IndiaM. G. SkandaDepartment of Industrial & Production Engineering, JSS S&T University, (SJCE) Mysore, IndiaM. LakshminarayanaDepartment of Medical Electronics Engineering, M S Ramaiah Institute Of Technology, Bengaluru, Karnataka, IndiaN. Chitra KiranDepartment of Electronics and Communication Engineering, Alliance University, Bengaluru, Karnataka, IndiaNamith GuptaAmity School of Engineering and Technology, Amity University, Noida, IndiaNidhi ShahDepartment of Life Sciences, University of Mumbai, Mumbai, IndiaN. MohanDepartment of EEE, JSS Science and Technology University Mysuru, Karnataka-570006, IndiaP. Vasantha KumarSchool of Excellence in Law, The Tamil Nadu Dr. Ambedkar Law University, Chennai, IndiaRishabh JainAjay Kumar Garg Engineering College (AKTU), Ghaziabad, Uttar Pradesh, IndiaRajesh Kumar PatnaikDepartment of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh-532127, IndiaRanjan WaliaDepartment of Electrical Engineering, Model Institute of Engineering and Technology, Jammu, Jammu & Kashmir - 181122, IndiaShashank AwasthiDepartment of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida, U.P., IndiaSrishti JainIndira Gandhi Delhi Technical University for Women, IndiaSumedha JainChandigarh College of Engineering and Technology, Chandigarh, IndiaSatya Prakash YadavDepartment of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida, U.P, IndiaSagaya AureliaDepartment of Computer Science, CHRIST University, Bengaluru, Karnataka, IndiaS. KirubakaranDepartment of ECE, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu-641407, IndiaSmitha ShekarDepartment of Computer Science & Engineering, Dr. Ambedkar Institute of Technology, Mallathahalli, Bangalore, Karnataka - 560056, IndiaS. B. PrathibhaDepartment of Computer Science and Engineering, Sri Siddartha Institute of Technology, Tumakuru, Karnataka, IndiaUdayabalan BalasingamDepartment of Information Science and Engineering, East Point College of Engineering and Technology, Bengaluru, Karnataka, IndiaUrmila R. PolDepartment of Computer Science, Shivaji University, Kolhapur, Maharashtra-416003, IndiaVartika AgarwalDepartment of Biotechnology, Savitribai Phule Pune University, Pune, Maharashtra, IndiaVartika AgarwalAmity School of Engineering and Technology, Noida, Uttar Pradesh, India
Investigating the Features of Physical Layer Structure for Employment of Smart City Models
Rishabh Jain1,*,Srishti Jain2,Muskan Jindal3,Mahaveer Singh Naruka4
1 Ajay Kumar Garg Engineering College (AKTU), Ghaziabad, Uttar Pradesh, India
2 Indira Gandhi Delhi Technical University for Women, India
3 Amity School of Engineering and Technology, Noida, Uttar Pradesh, India
4 G.L. Bajaj Institute of Technology and Management, Greater Noida, U.P, India
Abstract
In today’s world, when everything around us is getting smart, be it the “phone” or “television”, there is an utter need and high time for the cities to get smart to solve the major problems of mankind. It is a futuristic approach to alleviate obstacles caused due to day by day increasing population of India. It will help the government as well as the common people to fight daily life problems such as water scarcity, waste management, and lack of interconnectivity in a city that can cause serious problems like delayed responses to emergency situations. This paper mainly focuses on the salient features of the smart city “Dholera” in Gujarat, India. The city uses futuristic technologies like Artificial Intelligence (AI) and the Internet of Things(IoT) to automate city resources. It has AI-based smart grids, transportation, water and waste management. This paper explains why Cholera is a smart, intelligent and fast-responsive city and how it is a boon for the masses.
Keywords: Case Study, Employment Framework, IOT, Smart City.
*Corresponding author Rishabh Jain: Ajay Kumar Garg Engineering College(AKTU), Ghaziabad, Uttar Pradesh, India; E-mail:
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