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IoT for Landslides: Applications, Technologies and Challenges

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Paradigms of Smart and Intelligent Communication, 5G and Beyond

Abstract

The most common existing human-induced and natural geohazard causing damage to infrastructure and property loss are landslides occurring in hilly regions of India. Landslide involves excessive surface movements, including rock failure, slope failure, debris flow, etc. Landslide prevention is based on the principles of slope stability engineering and developing techniques to reduce its effects on natural resources, river ecosystems, and infrastructure loss. Early warning and monitoring of landslides are the most critical detection/prevention strategies. With advancements in the evolution of the Internet of Things (IoT) technique, the recent innovative concept involves the utilization of IoT to strengthen particularly capability and accuracy of early warning and monitoring frameworks to prevent landslides. This chapter presents a brief overview of related research and technological advancements in IoT techniques used for landslide studies. First, it studies the importance and application of IoT for landslide monitoring and early warning system design, then investigates the fundamental layers in IoT along with the application and key technologies involved in landslide prevention. This chapter also highlights challenges with IoT-based landslide early warning and monitoring systems.

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Correspondence to Amrita Mohan .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Mohan, A., Dwivedi, R., Kumar, B. (2023). IoT for Landslides: Applications, Technologies and Challenges. In: Rai, A., Kumar Singh, D., Sehgal, A., Cengiz, K. (eds) Paradigms of Smart and Intelligent Communication, 5G and Beyond. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-99-0109-8_13

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  • DOI: https://doi.org/10.1007/978-981-99-0109-8_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0108-1

  • Online ISBN: 978-981-99-0109-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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