Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications

Abstract

Cover -- Half Title -- Title -- Copyright -- Contents -- Preface -- About the Editors -- List of Contributors -- Chapter 1 ◾ A Detailed Study on Deep Learning versus Machine Learning Approaches for Pest Classification in Field Crops -- 1.1 Introduction -- 1.1.1 Background -- 1.1.2 Dataset -- 1.1.3 Machine Learning -- 1.1.4 Deep Learning -- 1.2 Related Work -- 1.2.1 Pest Classification in Field Crops Based on ML Techniques -- 1.2.2 Pest Classification in Field Crops Based on DL Algorithms -- 1.3 Open-Source Tools for Deep Learning Frameworks -- 1.4 Challenges in the Area of Pest Classification Using ML/DL -- 1.4.1 Lack of Dataset -- 1.4.2 Selection of Hyperparameters -- 1.4.3 Algorithm Selection -- 1.4.4 Performance Metric Selection -- 1.5 Conclusion -- References -- Chapter 2 ◾ Integration of Artificial Intelligence (AI) and Other Cutting-Edge Technologies -- 2.1 Introduction -- 2.2 Functional Blocks of an IoT Ecosystem -- 2.2.1 Sensors -- 2.2.2 Processors -- 2.2.3 Gateways -- 2.2.4 Applications -- 2.3 Technologies Involved in IoT Development -- 2.4 Working of IoT -- 2.5 IoT Platform -- 2.6 IoT Platforms Overview -- 2.6.1 Arduino -- 2.6.2 Raspberry Pi -- 2.7 Wearable IoT Technology -- 2.7.1 IoT Connectivity - 5G, Wi-Fi 6, LORA WAN -- 2.7.2 AIoT - Artificial Intelligence and IoT Technology -- 2.8 Applications -- 2.8.1 IoT for Smart Cities: Real-Time Examples -- 2.8.2 IoT in Smart Home -- 2.8.3 IoT in Healthcare -- 2.8.4 Automation in Agriculture -- 2.8.5 Industrial Automation -- 2.8.6 IoT in Transportation -- 2.9 Conclusion -- References -- Chapter 3 ◾ A Detailed Case Study on Various Challenges in Vehicular Networks for Smart Traffic Control System Using Machine Learning Algorithms -- 3.1 Introduction -- 3.1.1 Benefits of Using STCS -- 3.1.2 Reinforcement Learning (RL) -- 3.1.3 Traffic Light Management System (TLMS) -- 3.1.4 Machine Learning (ML).