Machine Intelligence for Smart Applications: Opportunities and Risks (Studies in Computational Intelligence, 1105)

✍ Scribed by Amina Adadi (editor), Saad Motahhir (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 243
• Category: Library

✦ Synopsis

This book provides insights into recent advances in Machine Intelligence (MI) and related technologies, identifies risks and challenges that are, or could be, slowing down overall MI mainstream adoption and innovation efforts, and discusses potential solutions to address these limitations. All these aspects are explored through the lens of smart applications.

The book navigates the landscape of the most recent, prominent, and impactful MI smart applications. The broad set of smart applications for MI is organized into four themes covering all areas of the economy and social life, namely (i) Smart Environment, (ii) Smart Social Living, (iii) Smart Business and Manufacturing, and (iv) Smart Government. The book examines not only present smart applications but also takes a look at how MI may potentially be applied in the future.

This book is aimed at researchers and postgraduate students in applied artificial intelligence and allied technologies. The book is also valuable for practitioners, and it serves as a bridge between researchers and practitioners. It also helps connect researchers interested in MI technologies who come from different social and business disciplines and who can benefit from sharing ideas and results.

✦ Table of Contents

Preface
Contents
Application of Machine Intelligence in Smart Societies: A Critical Review of the Opportunities and Risks
1 Introduction
2 Opportunities of MI for Smart Societies
2.1 MI Applications in Smart Societies
2.2 Socio-economic Impacts of Machine Intelligence in Smart Societies
3 Risks and Challenges of Machine Intelligence for Smart Societies
4 Addressing the Challenges and Risks of MI in Smart Societies
4.1 Need for Robust Regulation and Governance Frameworks for Machine Intelligence in Smart Societies
4.2 Need for Research to Address the Challenges and Risks and Ensure the Responsible Deployment of Machine Intelligence in Smart Societies
5 Concluding Remarks
References
Machine Intelligence for Smart Environment
Machine Learning Based Recommender Systems for Crop Selection: A Systematic Literature Review
1 Introduction
2 Overview of Existing Recommender Systems
3 Research Formulation
3.1 Questions Formulation
3.2 Search Strategy
3.3 Exclusion Criteria (EC)
3.4 Data Collection Process
4 Results of the Study
4.1 Filtering Process
4.2 Literature Review Information Matrix (LRIM)
4.3 How Did Research About CR Evolved Over Time?
4.4 What Are the Main Techniques That Were Used in the Literature for CR?
4.5 What Are the Main Input Features?
4.6 Which Evaluation Metrics and Evaluation Approaches Have Been Used?
4.7 Current Challenges in CR
5 Discussion
6 Conclusion and Future Work
References
Convolutional Neural Network for Identification and Classification of Weeds in Buckwheat Crops
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Cluster Analysis as a Tool for the Territorial Categorization of Energy Consumption in Buildings Based on Weather Patterns
1 Introduction
2 Description of the Benchmark Case
2.1 Case Study: State Social Housing in Mexico
3 Unsupervised Machine Learning
3.1 K-means Clustering Classification
3.2 Cluster Evaluation
3.3 Clustering Workflow
4 Case Study: K-Means-Based Categorization of Energy Consumption of Mexican SSH
4.1 Impact of Operational and Environmental Patterns
4.2 Computational Approach by K-means Clustering
4.3 Energy Consumption Categorization Analysis in SSH
5 Conclusions
References
Machine Intelligence for Smart Social Living
A Quantum Machine Learning Model for Medical Data Classification
1 Introduction
2 Background and Methodology
2.1 Quantum Mechanics
3 Support Vector Classifier
4 Quantum Support Vector Classifier
5 The Proposed Intelligent Medical Classification Model
6 Dataset Description
7 Data Preprocessing Phase
8 Feature Selection Phase
9 Data Encoding Phase
10 Classification Phase
11 Evaluation Phase
12 Experimental Results and Discussion
13 Conclusion and Future Work
References
Supporting and Shaping Human Decisions Through Internet of Behaviors (IoB): Perspectives and Implications
1 Introduction
2 Literature Review
3 Conceptual Framework of IoB
3.1 Key Concepts and Relationships
3.2 IoB-Human Interaction Model
3.3 Reference Model of IoB
3.4 Reference Architecture
3.5 Deployment
4 Scenarios of Human Decision-Shaping Using IoB
4.1 Physical Activity Tracking
4.2 Home Security
4.3 Traffic Management
5 IoB Systems and Applications
5.1 Smart Homes and Cities
5.2 Health and Wellness
5.3 Retail and Marketing
5.4 Public Services and Administration
6 Results and Analysis
6.1 Impact of IoB on Human Decision-Making
6.2 Ethical and Privacy Concerns of IoB
7 Answers to Research Questions
7.1 How Does IoB Impact Human Decision-Making Processes and Behavior?
7.2 What Are the Factors that Influence the Extent to Which IoB Systems Can Shape Human Behavior and Decision-Making?
7.3 How Does the Use of IoB Systems Affect Individual Autonomy and Free Will in Decision-Making?
7.4 How Can the Unintended Consequences of IoB Be Mitigated or Avoided?
7.5 What Future Developments Can Be Expected in the Field of IoB and How Will They Impact Human Decision-Making Processes and Behavior?
7.6 Implications for Researchers, Policymakers, and Practitioners
7.7 Limitations and Suggestions for Future Research
8 Future of IoB
8.1 Emerging Trends and Innovations
8.2 Predicted Impact on Society and Economy
8.3 Challenges and Opportunities
8.4 Roadmap for Development and Deployment
9 Conclusion
References
A Machine Learning Based Approach for Diagnosing Pneumonia with Boosting Techniques
1 Introduction
1.1 Related Works
2 Materials and Methods
2.1 Data Set
2.2 Traditional Machine Learning Approach
3 Implementation and Result Analysis
4 Conclusion
References
Harnessing the Power of ChatGPT for Mastering the Maltese Language: A Journey of Breaking Barriers and Charting New Paths
1 Introduction
1.1 Background Information
1.2 Statement of the Problem
1.3 The Aims of the Study
2 Literature Review
3 Methodology
4 Analysis of Results and Discussion
4.1 ChatGPT's Ineffectiveness for Maltese Learning
4.2 ChatGPT Usage Frequency Regression Analysis
4.3 Sentiment Analysis of Focus Group Responses
4.4 ChatGPT's Training in Maltese Language
4.5 ChatGPT's Effectiveness for Learning Foreign Languages, Especially English
4.6 ChatGPT's Knowledge of Maltese Culture
4.7 ChatGPT's Need for Improvement in Maltese
5 Limitations
6 Recommendations
7 Conclusion
References
Machine Intelligence for Smart Business and Manufacturing
A New Autonomous Navigation System of a Mobile Robot Using Supervised Learning
1 Introduction
2 Background and Problem Formulation
2.1 Grid Map
2.2 A-RRT*
2.3 Robot Configuration
2.4 Supervised Learning with XGBoost
3 Data Collection Methodology
3.1 Data Collection Process
3.2 Data-Set Generation
4 System Design
4.1 Preprocessing and Model Selection
4.2 Model Corrector
5 Simulation and Results
6 Conclusion
References
Evolutionary AI-Based Algorithms for the Optimization of the Tensile Strength of Additively Manufactured Specimens
1 Introduction
2 Background
2.1 Additive Manufacturing in Industrial Sectors
2.2 Evolutionary Based Algorithms in Manufacturing
3 Materials and Methods
4 Results and Discussion
4.1 Data Analysis and Visualization
4.2 Particle Swarm Optimization (PSO) Algorithm for Finding Optimal Parameters
4.3 Differential Evolution (DE) Algorithm for Finding the Optimal Parameters
5 Conclusions
References
Securing Data Conveyance for Dynamic Source Routing Protocol by Using SDSR-ANNETG Technique
1 Introduction
2 Related Works
3 Study Method
4 Result and Discussions
5 Conclusions
References
Machine Intelligence for Smart Government
Regional Language Translator and Event Detection Using Natural Language Processing
1 Introduction
2 Related Works
3 Proposed System Architecture
3.1 Text and Image Translation
3.2 Event Detection
4 Results Evaluation
4.1 Performance Analysis
4.2 Results Analysis
5 Conclusion and Future Work
References