International Conference on IoT, Intelligent Computing and Security: Select Proceedings of IICS 2021

Organizations
Preface
Keynote I
Keynote II
Keynote III
Contents
Editors and Contributors
IoT and Intelligent Computing: A Paradigm Shift
Internet of Medical Things Enabled by Permissioned Blockchain on Distributed Storage
	1 Introduction
		1.1 Problem Areas
		1.2 Blockchain
		1.3 Distributed Storage
	2 Schema Setup
	3 Results
		3.1 Distributed Storage with IPFS
		3.2 IPFS-Enabled Distributed Storage for Retard_pandemics
		3.3 blk00000.dat File
	4 Challenges and Discussions
	5 Conclusion
	References
Wearable Location Tracker for Emergency Management
	1 Introduction
	2 Related Work
		2.1 Literature Review
		2.2 Difference from Existing System and Scope
	3 Proposed Methodology
		3.1 System Modules
		3.2 Components Used
	4 System Implementation
	5 Future Work
	6 Conclusion
	References
A Review of Machine Learning Techniques (MLT) in Health Informatics
	1 Introduction
		1.1 Health Informatics (HI)
		1.2 Machine Learning (ML)
		1.3 Role of Machine Learning in Healthcare Disease
	2 Literature Review and Critical Issues
	3 Area of Research and Formulation of Research Problem
	4 Conclusion
	References
A Task Scheduling Algorithm for Optimizing Quality of Service in Smart Healthcare System
	1 Introduction
	2 Literature Review
	3 Proposed Work
	4 Experimental Results
	5 Conclusion and Future Work
	References
Comparative Study of Machine Learning Models for Early Detection of Parkinson’s
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Data Set and Their Analysis
		3.2 Machine Learning Models and Metrics for Evaluation
	4 Result and Discussion
		4.1 Logistic Regression
		4.2 Support Vector Machine
		4.3 Decision Tree
		4.4 Random Forest
		4.5 Artificial Neural Network
	5 Conclusion
	References
Mining Repository for Module Reuse: A Machine Learning-Based Approach
	1 Introduction
	2 Software Repositories
		2.1 Historical Repositories
		2.2 Run Time Repositories
		2.3 Code Repositories
	3 Related Work
	4 Methodology
	5 Mathematical Model
	6 Experimental Set-Up
	7 Performance Analysis
	8 Conclusion
	References
An Approach to Mine Low-Frequency Item-Sets
	1 Introduction
	2 Related Research
	3 Proposed Work
	4 Numerical Example
	5 Experimental Analysis with Large Data Sets
	6 Conclusion and Future Scope
	References
Forecasting Floods in the River Basins of Odisha Using Machine Learning
	1 Introduction
	2 Related Work
	3 ML-Based Flood Forecasting Model
	4 Experimental Results
	5 Conclusion
	References
Emo-Spots: Detection and Analysis of Emotional Attributes Through Bio-Inspired Facial Landmarks
	1 Introduction
		1.1 Bio-Inspired Learning
		1.2 Face Landmarks
	2 Literature Survey
		2.1 Landmark Detection
	3 System Design
		3.1 Problem Finding
		3.2 Proposed Method
	4 Methodology
		4.1 Preprocessing Block
		4.2 Face Detection Block
		4.3 Landmark Mapping Block
		4.4 Classification Block
		4.5 Validation Block
		4.6 Testing Summary
	5 Summary of RESET Algorithm
		5.1 CNN Framing
		5.2 Layers of CNN
		5.3 Proposed Layer Configurations
	6 Results and Discussions
		6.1 Training Images
		6.2 Detection of Emo-Spots and Mappings
		6.3 Predicted Results
		6.4 Weight Updates from Randomly Looped KNN (RLKNN)
	7 Challenges
	8 Conclusion
	References
Rapid Face Mask Detection and Person Identification Model Based on Deep Neural Networks
	1 Introduction
	2 Related Work
	3 Existing System
		3.1 Issues in Existing System
		3.2 Drawbacks in Existing System the Major Limitations of Existing Schemes Are as Follows
	4 Proposed System
		4.1 Advantage of Proposed System
		4.2 Proposed System Pseudocode
		4.3 Proposed System Design
		4.4 Complete System Design
		4.5 Formulating the Dataset
		4.6 Training Process
	5 Simulation Study
		5.1 Dataset
		5.2 Feature Extractor
		5.3 Training Values and Test Size
		5.4 Comparison on WIDER FACE
	6 Result Discussion and Analysis
		6.1 Connectivity
		6.2 Proposed Model Accuracy Samples
		6.3 Embedding Size
		6.4 Evaluation Results
		6.5 Working of Model
		6.6 E-mail Notification
	7 Conclusion and Future Works
		7.1 Conclusion
		7.2 Future Work
	References
An Infrastructure-Less Communication Platform for Android Smartphones Using Wi-Fi Direct
	1 Introduction
		1.1 Wi-Fi Direct Architecture
	2 Fine Time Measurement (FTM) Protocol
		2.1 Wi-Fi Direct Simulator
		2.2 Wi-Fi Direct Interface
		2.3 Proximity Manager
	3 Results and Discussion
		3.1 Positioning of a Mobile Device with Wi-Fi RTT
	4 Conclusion
	References
Prioritization in Data Warehouse Requirements—Incorporating Agility
	1 Introduction
		1.1 Agility Principle in Software Development
		1.2 Agility in Data Warehouse
		1.3 Prioritization Strategies
	2 Overview of Previous Work
	3 Proposed Algorithm
		3.1 Prioritization Strategy in Proposed Algorithm
		3.2 Explanation and Example
	4 Conclusion
	References
Module Allocation Model in Distributed Computing System by Implementing Fuzzy C-means Clustering Technique
	1 Introduction
	2 Problem Statement and Definitions
		2.1 Definitions
		2.2 Assumptions
	3 Proposed Model
	4 Implementation of the Model
	5 Conclusion
	References
A Soft Computing Intelligent Technique Implication for the Comprehensive Audit of Electric Vehicle
	1 Introduction
	2 Intelligent Methods of Charging and Discharging
		2.1 Machine Learning Technique
		2.2 Multi-Variant Deep Learning Approach
		2.3 Dynamic Game Method
		2.4 Artificial Neuro-Fuzzy Control
		2.5 Bi-Level Event-Based Optimization Method
		2.6 An MPC Method
	3 Conclusion
	References
A Review About the Design Methodology and Optimization Techniques of CMOS Using Low Power VLSI
	1 Introduction
		1.1 Dynamic/Switching Power Consumption
		1.2 Short Circuit Power Dissipation
		1.3 Leakage Power Dissipation
	2 Literature Survey
	3 Techniques of Low Power Design Through Voltage Scaling
		3.1 Effects of Voltage Scaling on Power and Delay
		3.2 Variable Threshold CMOS (VTCMOS) Circuit
		3.3 Multiple Threshold CMOS (MTCMOS) Circuit
		3.4 Dual Threshold CMOS Circuits
		3.5 Dynamic Threshold CMOS Circuits
		3.6 Multiple Vdd CMOS Design Technique
		3.7 Standby Leakage Control Using Transistor Stacks
		3.8 Reduction of Switching Events
		3.9 Glitch Reduction
		3.10 Modified Lector Technique
		3.11 Power Gating Technique
	4 CMOS Circuit Characteristics in Low Power VLSI
	5 Comparison Table with Different Techniques
	6 Conclusion
	References
Characterization of SPEC2006 Benchmarks Under Multicore Platform to Identify Critical Architectural Aspects
	1 Introduction
	2 System Configuration and Methodology
	3 Simulation Results
	4 Result Analysis
		4.1 Total Time for Execution
		4.2 CPI Analysis
	5 Conclusion
	References
Design of Buck Converter with Modified P&O Algorithm-Based Fuzzy Logic Controller for Solar Charge Controller for Efficient MPPT
	1 Introduction
	2 Photovoltaic System Electrical Configuration
		2.1 PV Panel Model
		2.2 Buck Converter
	3 Maximum Power Point Algorithm
		3.1 Conventional P&O Algorithm
		3.2 Modified P&O Technique
		3.3 Fuzzy Logic Controller
	4 Discussion and Results
	5 Conclusion
	References
Security in Smart Computing Environment
DDoS Attack Detection Using Artificial Neural Network on IoT Devices in a Simulated Environment
	1 Introduction
	2 Basic Concepts and Terminologies
		2.1 Artificial Neural Networks
		2.2 Intrusion Detection System
		2.3 DDoS Attack
	3 Literature Review
	4 Proposed Methodology
		4.1 Detailed Configuration of Our Model
		4.2 Workflow and Algorithms of Our Proposed Methodology
		4.3 The Process of DDoS Attack Classification by the ANN Model
	5 Observations and Results
	6 Conclusion and Future Scope
	References
ABBDIoT: Anomaly-Based Botnet Detection Using Machine Learning Model in the Internet of Things Network
	1 Introduction
	2 Machine Learning Based IoT Botnet Detection—Related Work
	3 Proposed Work
		3.1 Description and Analysis of IoT Botnet Dataset
		3.2 Model Architecture
		3.3 Model Training and Evaluation Metrics
		3.4 Result Analysis
	4 Comparison with Existing Results
	5 Conclusion
	References
A Hybrid Mechanism for Advance IoT Malware Detection
	1 Introduction
	2 Related Works
	3 Market Perspective of IoT and Malware Impact
	4 Existing Approaches for IoT Malware Detection
		4.1 Machine Learning-Based Approach for Malicious  Traffic Detection
		4.2 Graph-Based Analysis
		4.3 Image-Based Detection
		4.4 Opcode-Based Detection
		4.5 Static Analysis
	5 Hybrid Solution
	6 Research Directions
	7 Conclusion
	References
A Cloud-Edge Server-Based Cypher Scheme for Secure Data Sharing in IoT Environment
	1 Introduction
	2 Related Works
	3 The Proposed Cypher Scheme for Secure Data Sharing
		3.1 Key Generation
		3.2 Data and Keyword Uploading
		3.3 Data Downloading and Sharing
		3.4 Data Search and Retrieval
	4 Experimental Results
	5 Conclusion and Future Scope
	References
Attack Detection Based on Machine Learning Techniques to Safe and Secure for CPS—A Review
	1 Introduction
		1.1 Security Objectives of CPS
	2 Reliability and Security of CPS
	3 Design Challenges for Security Measures of CPS
	4 Literature Review
		4.1 Attack Detection Models
		4.2 ML in CPS
	5 Analysis of Prior Works
		5.1 Analysis Based on Publication years
		5.2 Analysis Based on Performance Measures
		5.3 Analysis Based on Attack Detection Techniques
	6 Conclusion
	References
Fake Account Detection in Social Networks with Supervised Machine Learning
	1 Introduction
	2 Related Work
	3 The Proposed Method
		3.1 Data Collection
		3.2 Preprocessing and Feature Selection
	4 Results and Analysis
	5 Conclusion
	References
Peak Detector Circuits for Safeguarding Against Fault Injection Attacks
	1 Introduction
	2 Contributions
	3 Related Work
	4 Glitch Detector Circuit
		4.1 Simulated Response of Glitch Detector Circuit
	5 Conclusion
	6 Future Work
	References
An Intuitionistic Fuzzy Approach to Analysis Financial Risk Tolerance with MATLAB in Business
	1 Introduction
	2 Preliminaries
	3 Components of the Proposed Intuitionistic Fuzzy Inference System (IFIS)
	4 Fuzzification of Input and Output Variables
	5 Intuitionistic Fuzzy Inference Rules
	6 Defuzzification Using Centroid Method (COA)
	7 Conclusion
	References
Contemporary Computing Applications
Deep Learning for Self-learning in Yoga and Fitness: A Literature Review
	1 Introduction
	2 Methodology
		2.1 Backbone Architecture
		2.2 Loss Functions
		2.3 Evaluation Metrics
	3 Result and Discussion
	4 Future Work
	5 Conclusion
	References
Cardio Vascular Disease Prediction Using Ensemble Machine Learning Techniques
	1 Introduction and Background
	2 Methodology
		2.1 Dataset
		2.2 Preprocessing
		2.3 Model Building
		2.4 Performance Metrics
	3 Results and Discussions
	4 Conclusion and Future Work
	References
Deep Learning Approach for Breast Cancer Detection
	1 Introduction
	2 Literature Review
	3 Machine Learning Algorithms Used for Classification
	4 Dataset Description
	5 Exploratory Analysis of Dataset
	6 Statistical Parameters Used for Testing the Performance of Model
	7 Results and Comparison
	8 Conclusion
	References
Iterated Shape-Bias Graph Cut-Based Segmentation for Detecting Cervical Cancer from Pap Smear Cells
	1 Introduction
	2 Related Works
	3 Proposed Iterated Shape-Bias Graph Cut-Based Segmentation (ISBGCS) Method
	4 Experimental Results and Discussion
	5 Conclusion
	References
Evaluation of Deep Learning Approaches for Lung Pneumonia Classification
	1 Introduction
	2 Literature Survey
		2.1 LeNet-5
	3 Proposed Model and Implementation
	4 Materials and Methods
	5 Results and Discussions
	6 Conclusion and Future Work
	References
Comparative Analysis to Classify Human Brain Anomalies for Brain Tumour
	1 Introduction
	2 Segmentation Methods and Performance Criteria
		2.1 Otsu
		2.2 Kapur
		2.3 Kittler
		2.4 Markov Random Field (MRF)
	3 Performance Measurement Metrics
	4 Comparative Result Analysis
	5 Conclusion
	References
Review on Customer Segmentation Methods Using Machine Learning
	1 Introduction
	2 Background
	3 Customer Segmentation
		3.1 Demographic Segmentation
		3.2 Psychographic Segmentation
		3.3 Behavioral Segmentation
		3.4 Geographic Segmentation
	4 Pros and Cons
		4.1 Demographic Segmentation
		4.2 Behavioral Segmentation
		4.3 Psychographic Segmentation
		4.4 Geographic Segmentation
	5 Methodology
		5.1 Data Collection
		5.2 Data Preprocessing
		5.3 Data Analysis
		5.4 Segmentation
	6 Methods Available
		6.1 Rule-Based
		6.2 Supervised Clustering with Decision Tree
		6.3 k-means
		6.4 k-prototype
		6.5 k-medoid (PAM)
	7 Conclusion
	References
Fish Species Classification Using Convolutional Neural Networks
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Dataset
		3.2 Approach Used
	4 Results and Discussions
	5 Conclusion and Future Work
	References
Disease Detection in Tomato Leaves Using Raspberry Pi-Based Machine Learning Model
	1 Introduction
	2 Literature Review
	3 Proposed Methodology
		3.1 Image Acquisition
		3.2 Image Segmentation
		3.3 Feature Extraction
		3.4 Data Set Used
		3.5 Hardware Implementation
		3.6 Classification
	4 Results
	5 Conclusion
	References
A Review on Crop Disease Detection Techniques
	1 Introduction
	2 Crop Diseases
		2.1 Fungal Diseases
		2.2 Bacterial Diseases
		2.3 Viral Diseases
	3 Crop Disease Detection and Classification Techniques—Review
		3.1 Crop Disease Detection Methods Without IoT
		3.2 Crop Disease Detection Methods with IoT
	4 Conclusion and Suggestions
	References
Energy-Efficient Model (ARIMA) for Forecasting of Modal Price of Cod Pea Using Cloud Platform
	1 Introduction
	2 Methodology
		2.1 Autoregressive Model
		2.2 Forecasting Model of Peas’ Modal Prices
	3 Result and Discussion
	4 Conclusion
	References
Investigation of Micro-Parameters Towards Green Computing in Multi-Core Systems
	1 Introduction
	2 Mi-Bench Benchmark Suite Characterization
	3 Experiment
	4 Results and Analysis
	5 Conclusion
	References
Hope Project: Development of Mobile Applications with Augmented Reality to Teach Dance to Children with ASD
	1 Introduction
	2 Material and Method
		2.1 Population
		2.2 Work Plan
		2.3 Phases of the Intervention
		2.4 Resources Used in the Intervention Plan
		2.5 Activities Designed to Reinforce Teaching–Learning Processes
	3 Results
	4 Discussion
	5 Conclusions
	References