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Machine Learning for Drone-Enabled IoT Networks: Opportunities, Developments, and Trends (Advances in Science, Technology & Innovation) by Jahan Hassan, Sara Khalifa, Prasant Misra is a computer science book available to read on EtoBox.
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Preface Contents Unmanned Aerial Vehicles Enabled IoT Platform for Effective Disaster Management Abstract 1 Introduction 1.1 IoT 1.2 UAVs 1.3 Current Trends Due to UAVs and IoT in Disaster Management 1.4 Legal Framework for UAVs and IoT Deployment in Disaster Management 2 Machine Learning Algorithms for UAV-Enabled IOT Networks 2.1 ML in Disaster Management (Predictive Analysis) 2.2 Anomaly Detection in Sensor Data 2.3 Object Detection & Semantic Segmentation 2.4 NLP for Text Analysis 2.5 Challenges in Using ML for Disaster Management: 3 Technological Integration and Data Collection in Disaster Management 3.1 Integration of UAVs and IOT in Disaster Management 3.1.1 Challenges in Integrating UAVs and IoT for Disaster Management 3.2 Real-Time Data Collection Using UAVs 3.3 Implementation of YOLO in Disaster Scenarios 3.4 Usage of Text Analysis for Disaster Alerts 4 Obstacles in Implementing UAV-Enabled IOT Devices for Disaster Management 4.1 Technology Limitations 4.1.1 Previous Efforts and Recommendations 4.2 Network Coverage Challenges 4.2.1 Previous Efforts and Recommendations 4.3 Guidelines for Efficient and Effective Usage 4.3.1 Previous Efforts and Recommendations 4.4 Privacy a
Who reads Machine Learning for Drone-Enabled IoT Networks: Opportunities, Developments, and Trends (Advances in Science, Technology & Innovation)?
It is typically read by working professionals who need an authoritative practice reference.
Common subject areas: medicine, law, business, engineering.
- Author
- Jahan Hassan, Sara Khalifa, Prasant Misra
- Publisher
- Springer Nature Switzerland AG
- Published
- 2025
- Language
- EN
- ISBN
- 9783031809606
- Category
- computer science
- Subjects
- Science, Computer Science, Computers
- Updated
- 2026-03-25
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