Research Trends in Artificial Intelligence: Internet of Things
1st Edition
Published on 13. March 2001
245 pages
978-981-5136-44-9 (ISBN)
Description
Stay informed about recent trends and groundbreaking research driving innovation in the AI-IoT landscape.
AI, a simulated form of natural intelligence within machines, has revolutionized various industries, simplifying daily tasks for end-users. This book serves as a handy reference, offering insights into the latest research and applications where AI and IoT intersect. The book includes 12 edited chapters that provide a comprehensive exploration of the synergies between AI and IoT. The contributors attempt to address engineering opportunities and challenges in different fields.
Key Topics:
AI and IoT in Smart Farming: Explore how these technologies enhance crop yield and sustainability, revolutionizing agricultural practices.
AIoT (Artificial Intelligence of Things): Understand the amalgamation of AI and IoT and its applications, particularly focusing on smart cities and agriculture.
Smart Healthcare and Predictive Disease Analysis: Uncover the crucial role of AI and IoT in early disease prediction and improving healthcare outcomes.
Applications of AI in Various Sectors: Explore how AI contributes to sustainable development, sentiment analysis, education, autonomous vehicles, fashion, virtual trial rooms, and more.
Each chapter has structured sections with summaries and reference lists, making it an invaluable resource for researchers, professionals, and enthusiasts keen on understanding the potential and impact of these technologies in today's rapidly evolving world.
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Vijayshri Nitin Khedkar | Ujwala Kshirsagar | Gitanjali Rahul Shinde
Research Trends in Artificial Intelligence
Internet of Things
Book
12/2023
Bentham Science Publishers
€91.71
Shipment within 3-4 weeks
Content
- Cover
- Title
- Copyright
- End User License Agreement
- Contents
- Foreword
- Preface
- List of Contributors
- IoT and AI-based Smart Farm: Optimizing Crop Yield and Sustainability
- Namrata Nishant Wasatkar1,*, Pranali Gajanan Chavhan1 and Vikas Kanifnath Kolekar1
- INTRODUCTION
- CHALLENGES AND ISSUES
- PROCESS OF SMART FARMING
- Predictive Analytics
- Precision Farming
- Autonomous Equipment
- Image Processing
- Blockchain Technology
- Decision Support Systems
- AUTONOMOUS EQUIPMENT FOR SMART FARMING
- Autonomous Tractors
- Drones
- Robotic Harvesters
- Autonomous Seeders
- Autonomous Weeders
- SENSORS IN SMART FARMS
- Soil Sensors
- Weather Sensors
- Plant Sensors
- Nutrient Sensors
- GPS Sensors
- BENEFITS OF SMART FARMING
- Improved Efficiency
- Increased Yields
- Reduced Environmental Impact
- Improved Quality and Safety
- Increased Profitability
- THE IMPACT OF CLIMATE ON SMART FARMING
- CASE STUDY OF SMART FARMING USING IOT
- HOW TO USE AI FOR OPTIMIZING AND PREDICTING YIELD
- Data Collection and Analysis
- Predictive Modeling
- Machine Learning
- Crop Monitoring
- Precision Agriculture
- Automated Irrigation Systems
- Crop Monitoring
- Livestock Monitoring
- Automated Machinery
- CASE STUDY -AUTOMATED IRRIGATION SYSTEMS
- Water Conservation
- Increased Crop Yield
- Reduced Labor Costs
- Improved Accuracy
- Flexibility
- CONCLUSION
- REFERENCES
- Impact of Automation, Artificial Intelligence and Deep Learning on Agriculture Crop Yield
- Prabhakar Laxmanrao Ramteke1,*
- INTRODUCTION
- AI TECHNIQUES FOR PROBLEM SOLVING IN AGRICULTURE SECTOR
- Fuzzy Logic
- Artificial Neural Networks
- Neuro- Fuzzy Logic
- Expert System
- OBSTACLES IN THE FIELD OF AGRICULTURE AND IN AI ADAPTATION
- Consumer Inclinations
- Lack of Labour
- Environmental Accountability
- Tiny and Dispersed Landholdings
- Seeds
- Land Mechanization
- Farm Automation or Smart Farming
- REQUIREMENT OF ARTIFICIAL INTELLIGENCE IN THE AGRICULTURE SECTOR
- Numerous Applications of AI & other Technologies that can Boost Agriculture Yield
- Development Driven by the IoT
- Ingenious Agriculture
- Advantages of Intelligent Farming
- AGRICULTURE APPLICATIONS AND USE CASES
- Climate Conditions Monitoring
- Greenhouse Automation
- Cattle Management and Monitoring
- Precision Agriculture
- Smart Farming Predictive Analytics
- A SMART FARMING SOLUTION
- IoT Hardware
- Connectivity
- Data Gathering Intervals
- The Farming Sector's Data Integrity
- Disease Detection
- AUTOMATION TECHNIQUES FOR IRRIGATION AND RE-ASSISTING FARMER ABILITY
- Using Drones and Robots to Automate Agriculture
- Robots and Autonomous Machines
- Robotic Weeding and Seeding
- Automatic Irrigation
- Automation of Harvest
- AGRICULTURE AUTOMATION BENEFITS
- The Agricultural Sector Satisfies Consumer Demand
- The Industry's Labour Deficit is Becoming Better
- Agriculture is Becoming More Environmental-friendly
- MODERN AI-BASED PREDICTION MODEL APPLICATIONS IN AGRICULTURE RELATING TO SOIL, CROP, DISEASES, AND PEST MANAGEMENT
- Soil Administration
- Crop and Yield Management
- Plant Disease Control
- Weed Management
- Pest Management
- Monitoring and Storage Control Management for Agricultural Products
- Manage Yield Prediction
- SOLUTIONS FOR MONITORING SMART FARMING
- Monitoring the State of Soil
- Agriculture Weather Monitoring
- Systems for Automating Greenhouses
- System for Monitoring Crops
- CONCLUDING REMARKS
- ACKNOWLEDGEMENTS
- REFERENCES
- AIoT: Role of AI in IoT, Applications and Future Trends
- Reena Thakur1,*, Prashant Panse2, Parul Bhanarkar1 and Pradnya Borkar3
- INTRODUCTION
- ROLE OF AI IN IOT
- VOICE ASSISTANTS
- ROBOTS
- SMART DEVICES
- INDUSTRIAL IOT
- APPLICATIONS
- Impact of A IoT on Society
- CONCLUSION
- REFERENCES
- The Role of Machine Intelligence in Agriculture: A Case Study
- Prabhakar Laxmanrao Ramteke1,* and Ujwala Kshirsagar2,*
- INTRODUCTION
- Understanding Essential Agriculture Stages
- Agriculture's Stages
- CASE STUDIES
- An IOT-based System for Crop Irrigation
- Applications of Machine Learning Algorithms in High Precision Agriculture
- Soil Characteristics and Weather Forecasting
- MODELLING SOIL WATER BALANCE
- DESIGN AND IMPLEMENTATION OF A SENSOR NETWORK-BASED SMART NODE
- Smart-node Hardware
- Acquisition Programme, Connectivity Architecture and Software
- IN IRRIGATION MANAGEMENT DECISION SUPPORT SYSTEM: ANALYSIS AND APPLICATION
- MACHINE LEARNING RECOMMENDED IRRIGATION METHODS
- Cotton Centre Pivot Irrigation is Efficiently Scheduled and Controlled by a Mechanism based on Canopy Temperature
- Intelligent Irrigation Monitoring with Thermal Imaging in Smart Agriculture with the Internet of Things
- IRRIGATION SENSOR COUPLED TO AUTOMATIC WATERING SYSTEM
- PREDICTION FOR CROP YIELD AND FERTILISER
- CLASSIFICATION MODEL FOR RICE PLANT DISEASE DETECTION THAT IS OPTIMAL
- Multi-Rotor Drone
- Fixed-Wing Drone
- Single-Rotor Helicopter Drone
- FARMING USING ARTIFICIAL INTELLIGENCE
- THE USE OF THE INTERNET OF THINGS AND CLOUD COMPUTING TO CREATE A CUSTOM AGRICULTURAL DRONE
- Autonomous Quadcopter
- On-Ground Sensor Nodes
- Image Processing
- Cloud Analytics and Data Storage
- Frontend
- INTERACTIVE CULTIVATION SENSING SYSTEM POWERED BY IOT
- Use of Weather Forecasting
- Using Drones to Assess Crop Health
- Predictive Analytics and Precision Agriculture
- A System Using AI that can Identify Pests
- IMPACT OF ARTIFICIAL INTELLIGENCE ON AGRICULTURAL CROP YIELD
- The Internet of Things (IoT) Driven Development
- The Development of Understanding via Images
- Identifying Diseases
- Determine the Crop's Readiness
- Field Administration
- Determining the Best Combination of Agronomic Goods
- Crop Health Surveillance
- Irrigation Automation Methods that Help Farmers
- Precision Farming
- APPLICATIONS OF AI TO AGRICULTURE
- PRODUCT RECOMMENDATIONS USING AI: CASE STUDY
- Solution Overview
- Artificial Intelligence in Agriculture Sector: Case Study of Blue River Technology
- CONCLUDING REMARKS
- ACKNOWLEDGEMENTS
- REFERENCES
- Optimal Feature Selection and Prediction of Diabetes using Boruta- LASSO Techniques
- Vijayshri Nitin Khedkar1,*, Sonali Mahendra Kothari1, Sina Patel1 and Saurabh Sathe2
- INTRODUCTION
- RELATED WORKS
- DATASET USED
- Handling Class Imbalance
- RESEARCH APPROACH
- FEATURE SELECTION METHODS
- ReliefF
- Boruta
- Lasso
- RESULT ANALYSIS
- Feature Selection Results
- Evaluation Metrics
- Cross-Validation
- Classification Method Results
- Evaluation of Receiver Operating Characteristics (ROC)
- DISCUSSION
- CONCLUSION
- FUTURE SCOPE
- REFERENCES
- Empowered Internet of Things for Sustainable Development Using Artificial Intelligence
- Pranali Gajanan Chavhan1,*, Namrata Nishant Wasatkar1 and Gitanjali Rahul Shinde2
- INTRODUCTION
- Artificial Intelligence
- Significance of Artificial Intelligence
- Benefits of AI
- Improving Sustainability in AI
- IOT AND ITS SIGNIFICANCE
- ROLE OF AI IN IOT
- SUSTAINABLE SECURITY FOR THE IOT USING AI
- A General Pseudo-code for a Sustainable Security Solution for IoT using AI
- Process
- DDoS (Distributed Denial of Service) Attacks
- Types of Attack
- Methods of Attack
- Source of Attack
- ENERGY MANAGEMENT USING AI
- THE IMPACT OF THE IOT ON SUSTAINABLE WATER MANAGEMENT
- When and Where to Irrigate with the Right Amount of Water Using IoT
- Smart Irrigation
- Leak Detection
- CLIMATE CONTROL SYSTEMS WITH AI
- General Circulation Models (GCMs)
- Earth System Models (ESMs)
- AI-IOT USE CASES
- Smart Home Automation
- Intelligent Transportation Systems
- Smart and Sustainable Transportation
- Intelligent Traffic Management
- Intelligent Transportation Systems (ITS)
- Autonomous Vehicles
- Predictive Maintenance
- Ride-sharing and Carpooling
- Smart Parking
- Predictive Maintenance
- Agricultural Monitoring
- Healthcare Monitoring
- Energy Management
- FUTURE OF IOT IN SUPPORT OF SUSTAINABILITY
- Smart Energy Management
- Resource Conservation
- Smart Transportation
- Sustainable Agriculture
- CONCLUSIONS
- FUTURE SCOPE
- REFERENCES
- Digital Twin and Its Applications
- Kiran Wani1,*, Nitin Khedekar1, Varad Vishwarupe1 and N. Pushyanth2
- INRODUCTION
- DIGITAL TWINS
- AUGMENTED REALITY
- Hardware for Augmented Reality
- VISUALIZATION OF THE DIGITAL TWIN DATA
- REAL-TIME MONITORING
- DIGITAL TWINS USAGE & APPLICATIONS
- CONCLUSION
- REFERENCES
- Ontology Based Information Retrieval By Using Semantic Query
- Rupali R. Deshmukh1,* and Anjali B. Raut2
- INTRODUCTION
- Historical Background
- Growth of Information Retrieval
- Ontology
- MOTIVATION
- LITERATURE REVIEW
- ISSUES IN INFORMATION RETRIEVAL
- AIM
- PROPOSED RESEARCH METHODOLOGY
- CONCLUSION
- REFERENCES
- Paradigm Shift of Online Education System Due to COVID-19 Pandemic: A Sentiment Analysis Using Machine Learning
- Prajkta P. Chapke1,* and Anjali B. Raut1
- INTRODUCTION
- HISTORICAL BACKGROUND
- Social Network Analysis
- Impact of Social Networks
- Positive Impact
- Negative Impact
- Characteristics of Social Networks
- User-based
- Interactive
- Community-driven
- Relationships
- Emotion Over Content
- Growth and Development in Sentiment Analysis
- CONTRIBUTION IN THE AREA OF RESEARCH
- Institution Involves in Area & Research
- Trends in the Area of Development
- Changing Prospective
- Industrial Trends and International Trends
- MOTIVATION
- LITERATURE REVIEW
- RESEARCH ISSUES
- GAP IN RESEARCH
- PROBLEM STATEMENT
- Aim and Objectives
- Aim
- Objectives
- IMPLICATIONS
- EXPECTED RESULT
- CONCLUSION
- REFERENCES
- Image Processing for Autonomous Vehicle Based on Deep Learning
- Tanvi Raut1, Ishan Sarode1, Riddhi Mirajkar2,* and Ruchi Doshi3
- INTRODUCTION
- Levels of Autonomous Driving
- Camera vs LiDAR: The Better Hardware for the Detection of Vehicles
- CHALLENGES FACED BY AUTONOMOUS VEHICLES
- LITERATURE SURVEY
- IMAGE RECOGNITION BASED ON DEEP LEARNING
- Advantages of CNN Over Traditional Algorithms
- SYSTEM ARCHITECTURE
- Proposed Algorithm
- Object Detection
- You Only Look Once (YOLO)
- Lane Detection
- CONCLUSION
- REFERENCES
- Applications of AI and IoT for Smart Cities
- A. Kannammal1,* and S. Chandia1
- INTRODUCTION
- Internet of Things
- AI-Enabled IoT
- POTENTIAL USE CASES OF AI AND IOT IN SMART CITIES
- Smart Home
- Smart Management of Equipment
- Human Activity Recognition
- Smart Healthcare
- Role of AI Algorithms in Smart Healthcare
- Fitness-Tracking System
- Glucose-Level Monitoring System
- Body-Temperature Monitoring System
- Stress Detection System
- Oxygen-Saturation Monitoring System
- Other Healthcare Applications
- Smart Transport
- Connected-Vehicle Infrastructure Pedestrian (VIP)
- Smart Parking System (SPS)
- Automated Incident Detection System (AID)
- Smart Infrastructure
- Smart Grid and Energy
- Energy Consumption Forecasting
- Smart Grid Monitoring and Management
- Structural Health Monitoring
- Smart Water
- Leakage Detection and Isolation
- Efficient Distribution and Consumption
- Real Estate Investment
- CONCLUSION
- REFERENCES
- Analysis of RGB Depth Sensors on Fashion Dataset for Virtual Trial Room Implementation
- Sonali Mahendra Kothari1,*, Vijayshri Nitin Khedkar1, Rahul Jadhav1 and Madhumita Bawiskar1
- INTRODUCTION
- Internet of Things (IoT)
- Components of IoT
- AUGMENTED REALITY (AR)
- VIRTUAL REALITY
- FASHION ANALYSIS AND RECOMMENDATION
- RGB-DEPTH SENSOR
- VIRTUAL TRIAL ROOM TECHNIQUES AND FASHION DATASETS
- 12.6.1. Virtual Trial Room Techniques
- Fashion Datasets
- DISCUSSION AND FUTURE DIRECTIONS
- SUMMARY
- CHALLENGES IN SENSOR SELECTION AND TRIAL ROOM SETUP
- FUTURE DIRECTION
- CONCLUSION
- REFERENCES
- Subject Index
- Back Cover
