Smart City Gnosys
Smart city article details
| Title | Mobile Crowdsensing And Remote Sensing In Smart Cities: An Introduction |
|---|---|
| ID_Doc | 37263 |
| Authors | Tony Santhosh G. |
| Year | 2025 |
| Published | Internet of Things, Part F4006 |
| DOI | http://dx.doi.org/10.1007/978-3-031-72732-0_1 |
| Abstract | The concept of smart cities has emerged as a transformative approach to urban planning and management, leveraging cutting-edge technologies to enhance the quality of life for urban residents. Two pivotal technologies driving the smart city revolution are mobile crowdsensing and remote sensing. This book chapter provides a comprehensive exploration of these technologies and their integration within the context of smart cities. Mobile crowdsensing harnesses the ubiquity of smartphones and wearable devices to gather real-time data from citizens. This data encompasses various aspects of urban life, including traffic patterns, air quality, noise levels, and more. The chapter delves into the intricacies of mobile crowdsensing, from task design and participant recruitment to data collection, fusion, and analysis. It highlights the role of citizens as active contributors to urban data generation and the impact of this approach on informed decision-making by city planners. Remote sensing, on the other hand, offers a bird’s-eye view of urban landscapes through satellites, drones, and other sensor-equipped platforms. This technology provides valuable insights into land use, environmental conditions, infrastructure, and more. The chapter explores the deployment of remote sensing in urban environments, covering sensor placement, data collection, transmission, processing, and interpretation. It underscores the significance of remote sensing in monitoring urban sprawl, environmental changes, and sustainable development. A major focus of the chapter is the integration of mobile crowdsensing and remote sensing within the smart city framework. By combining real-time, citizen-generated data with comprehensive remote sensing insights, cities can gain a holistic understanding of their complex ecosystems. This integrated approach empowers city planners, policymakers, and environmental agencies to make informed decisions regarding urban development, resource allocation, and emergency response. Throughout the chapter, practical examples and case studies illustrate the real-world applications of mobile crowdsensing and remote sensing in smart cities. These examples showcase how cities worldwide are leveraging these technologies to optimize transportation systems, manage public spaces, monitor pollution levels, and respond to urban challenges effectively. In conclusion, this book chapter provides a thorough exploration of mobile crowdsensing and remote sensing as fundamental pillars of smart city development. It emphasizes the role of these technologies in shaping sustainable and efficient urban landscapes, promoting citizen engagement, and enabling data-driven decision-making. The chapter serves as a valuable resource for researchers, urban planners, policymakers, and anyone interested in the dynamic field of smart cities and the technologies that drive them. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. |
| Author Keywords | Algorithm optimization; Feature extraction; Mobile crowdsensing; Remote sensing; Sensor fusion; Ubiquitous mobile devices; Urban planning |
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