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.
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.
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.
Table of Contents
- Contents
- Foreword
- Preface
- List of Contributors
- Sustainability
- Namrata Nishant Wasatkar, Pranali Gajanan Chavhan and Vikas Kanifnath Kolekar
- 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
- Learning on Agriculture Crop Yield
- Prabhakar Laxmanrao Ramteke
- 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
- Reena Thakur, Prashant Panse, Parul Bhanarkar and Pradnya Borkar
- Introduction
- Role of Ai in IoT
- Voice Assistants
- Robots
- Smart Devices
- Industrial IoT
- Applications
- Impact of a IoT on Society
- Conclusion
- References
- Study
- Prabhakar Laxmanrao Ramteke and Ujwala Kshirsagar
- 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
- Boruta- Lasso Techniques
- Vijayshri Nitin Khedkar, Sonali Mahendra Kothari, Sina Patel and Saurabh Sathe
- Introduction
- Related Works
- Dataset Used
- Handling Class Imbalance
- Research Approach
- Feature Selection Methods
- Relieff
- Boruta
- Lasso
- Result Analysis
Author
- Sonali Mahendra Kothari
- Vijayshri Nitin Khedkar
- Ujwala Kshirsagar
- Gitanjali Rahul Shinde
