Mobile Crowdsensing and Remote Sensing in Smart Cities

Chaker Abdelaziz Kerrache (Hrsg.), Carlos T. Calafate (Hrsg.), Yesin Sahraoui (Hrsg.), Anna Maria Vegni (Hrsg.)

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Springer Nature Switzerland img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik

Beschreibung

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.

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Schlagwörter

Remote sensing, Community detection, Mobilecrowd sensing, Smart cities, Data Analytics