Mobile Crowdsensing and Remote Sensing in Smart Cities

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations.

• Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities;
• Covers technical details of remote sensing starting from the communication support to the application;
• Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.

Chapter 1: Introduction. - Mobile Crowdsensing and Remote Sensing in Smart Cities. - Part 1: IoT for sustainability & life-quality. - Chapter 2: The Role of IoT in Environmental Sustainability: Advancements and Applications for Smart Cities. - Chapter 3: Sensors and Metaverse-Digital Twin Integration: A Path for Sustainable Smarter Cities. - Chapter 4: Bringing the Green into the Screen: Remote Sensing and Smart Green Governance in Urban Forest Management. - Chapter 5: Advancements in 5G-IoT Technology based Healthcare: A Focus on Healthcare Monitoring for Smart Cities. - Part 2: Smart cities applications based on crowdsensing and remote sensing. - Chapter 6: From Mobile Crowdsensing to Contact Tracing. - Chapter 7: Deep Data Inference on Sparse Mobile Crowdsensing. - Chapter 8: Crowd Management using Mobile Crowdsourcing and Remote Sensing during the COVID-19 Pandemic. - Chapter 9: A Trusted Crowdsensing Approach for Governing Smart Healthcare using Blockchain Technique. - Chapter 10: Advancing Smart City Infrastructure with V2X Vehicle-Road Collaboration Architectural and Algorithmic Innovations. - Chapter 11: Safety in the Sky: Cloud-Powered Smart Security for Vehicular Crowdsensing.