This book informs the reader about applications of ArtificialIntelligence (AI) and nature-inspired algorithms in different situations. Eachchapter in this book is written by topic experts on AI, nature-inspired algorithmsand data science. Chapters are structured to provide an introduction to the topic, the computational methodology required for experimentation and analysis, and a discussion of results results The basic concepts relevant to these topics are explained, includingevolutionary computing (EC), artificial neural networks (ANN), swarmintelligence (SI), and fuzzy systems (FS). Additionally, the book also covers optimizationalgorithms for data analysis. The contents include algorithms that can be used in systems designedfor plant science research, environmental analysis, computer vision andhealthcare. There are a variety of use cases highlighted in the book that demonstrate how computer algorithms can be used to simulate and understand natural phenomena, such as moving object detection, COVID-19 detection, genetic diversity, physiology and much more. Additionally, the contributors provide useful tips specific to some algorithsm such as load balancing techniques and fuzzy PID controls. The goal of the book is to equip the reader - students and data analysts- with the information needed to apply basic AI algorithms to resolve actualproblems encountered in a professional environment.
Table of Contents
- Preface
- List of Contributors
- Applications
- Vani Kansal and Sunil K. Singh
- Introduction
- Survey Strategies
- Big Data
- Cloud Computing
- Pervasive Computing
- Reconfigurable Computing
- Green Computing
- Embedded Computing
- Parallel Computing
- Fog Computing
- Internet of Things and Computing Technology
- Blockchain
- Ngs-Throughput
- Digital Image Processing
- E-Commerce
- Healthcare Informatics and Clinical Research
- Survey Outcomes
- Data Computing Challenges
- Reliable Industry 4.0 Based on Machine Learning and IoT For
- Analyzing
- Conclusion
- Consent for Publication
- Conflict of Interest
- Acknowledgement
- References
- Harsh Pratap Singh, Bhaskar Singh, Rashmi Singh and Vaseem Naiyer
- Introduction
- Accumulating and Sending Information
- Receiving and Acting on Information
- Doing Both
- Key Challenges of IoT
- Data Fusion Archtechture
- Centralized Fusion Architecture
- Distributed Fusion Architecture
- Hybrid Fusion Architecture
- Literature Review
- Multi-Sensor Data Fusion
- Fuzzy Logic-Based Data Fusion
- Bayesian-Based Technique
- Markov Process-Based Technique
- Demspter-Shafer Theory Based Technique
- Thresholding Techniques and Others
- Application of IoT
- Smart Environment
- Health Care
- Iot in Agriculture
- Associated Industry
- Smart Retail
- Smart Energy and Smart Grid
- Traffic Monitoring
- Smart Parking
- Conclusion
- Consent for Publication
- Conflict of Interest
- Acknowledgements
- References
- Care
- Upasana Pandey and Arvinda Kushwaha
- Introduction
- Recent Applications of Ai in Medicine and Health Care
- Diagnosis of Disease and Prediction
- In Reduction of Complications
- Taking Care of Patients Under Treatment
- In Assisting to Improve the Success Ratio of Treatment
- Living Assistance
- Biomedical Information Processing
- Ai in Biomedical Research
- Ai in Medical Imaging
- Latest Ai Techniques in Medical Sciences
- Effects of Usage of Ai Techniques
- Fast and Accurate Diagnostics Reduce the Mortality Rate
- Reduce Errors Related to Human Fatigue
- Decrease in Medical Cost
- Area of Concerns
- Care of Old Age People
- Replacement of Humans With Ai Techniques
- Data Collection and Its Security
- Recently Used Ai-Based Medical Tools
- Conclusion
- Consent of Publication
- Conflict of Interest
- Acknowledgements
- References
- Devika Bihani, Saransh Sharma and Harshit Jain
- Introduction
- Related Work
- Proposed Method
- Weapon Detection
- Violence Detection
- Medical Emergency Detection
- Dataset & Pseudocode
- Pseudocode
- Conclusion
- Current & Future Developments
- Consent for Publication
- Conflict of Interest
- Acknowledgements
- References
- For Job Scheduling
- Anand Singh Rajawat, Kanishk Barhanpurkar and Romil Rawat
- Introduction
- Related Work
- Proposed Work
- Hybrid Approach
- Produce Population (Pp)
- Fitness Function (Ff)
- Native Preeminent (Np)
- Crossway
- Update Global Preeminent
- Random Forest Training
- Proposed Training Algorithm
- Procedure
- Proposed Algorithm
- Improved Genetic Algorithm With Hybrid Algorithm (Ha (Ga, Kmc
- And Rf))
- Load Balancing Under Cloud Computing Environment
- Relevant Operations of Ga
- Simulation Result Analysis
- Result Analysis
- Conclusion and Future Work
- Future Scope
- Consent of Publication
- Conflict of Interest
- Acknowledgements
- References
- Miner for Stream Data Classification
- Harsh Pratap Singh, Vinay Singh, Divakar Singh and Rashmi Singh
- Introduction
- Related Work for Stream Classification
- Proposed Algorithm for Pattern Classification in Mcm
- Result Analysis
- Conclusion
- Consent for Publication
- Conflict of Interest
- Acknowledgements
- References
- Major Shift With Opportunities and Challenges
- Nahid Sami and Asfia Aziz
- Introduction
- Why Ai in Healthcare
- Ai Techniques in Healthcare
- Machine Learning
- Support Vector Machine
- Neural Network
- Deep Learning
- Natural Language Processing
- Opportunity and Its Impact
- Diagnosis
- Therapy
- Drug Development and Research
- Rehabilitation of Elderly
- The Future
- Challenges and Limitations
- Digitization of Clinical Data
- Privacy and Security
- Role of Stakeholder
- Facing the Causality
- Black Box Issue
- Conclusion
- Consent of Publication
- Conflict of Interest
- Acknowledgements
- References
- Leaf Image Using Machine Learning in Indian Ecological System
- Sugandha Chakraverti, Ashish Kumar Chakraverti, Jyoti Kumar, Piyush Bhushan
- Singh and Rakesh Ranjan
- Introduction
- Image Processing
- A Typical Image-Based Plant Identification System (Satti Et Al. 2013)
- Image Acquisition
- Pre-Processing
- Feature Extraction
- Color Features
- Shape Features
- A). Geometric Features
- B). Morphological Features
- C). Tooth Features
- Indian Plants Image Data Sets
- Machine Learning Techniques for Leaf Recognition
- Developments of Automatic Systems/Mobile Apps for Leaf
- Recognition
- Plantifier
- Garden
- Plantnet
- Inaturalist
- Key Attributes
- Flowerchecker
- Agrobase
- Leaf Recognition App
- Methodology
- Integration of the Front-End With the Backend
- Description
- Conclusion
- Consent for Publication
- Conflict of Interest
- Acknowledgement
- References
- Learning
- Taranjeet Singh, Krishna Kumar, S. S. Bedi and Harshit Bhadwaj
- Introduction
- Paddy Diseases
- Deep Learning (Dl)
- Pretrained Neural Network (Pnn)
- Concluding Remarks
- Consent of Publication
- Conflict of Interest
- Acknowledgements
- References
- Image Segmentation
- Amreen Ahmad, Chanchal Kumar, Ajay Kumar Yadav and Agnik Guha
- Introduction
- What Are Shallow Clouds?
- Why is It Important to Study Shallow Clouds?
- Motivation for An Automated System for Cloud Classification
- Benefits
- Related Work
- Proposed Methodology
- Data Preprocessing
- Data Analysis
- Model Used
- Unet
- Idea Behind Unet
- Architecture Unet
- Unet on Resnet34 Backbone: Residual Network
- Residual Blocks
- Architecture
- Cross Entropy
- Dice Loss
- Radam Optima
- Evaluation Metric
- Data Set
- Experimental Analysis
Contributors
- Rijwan Khan
- Pawan Kumar Sharma
- Sugam Sharma
