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Feasibility study for detecting shallow landslides using IoT devices in smart cities

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Author(s):
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Santos, Alessandro S. ; Corsi, Alessandra C. ; Almeida, Rynaldo Z. H. ; Noda, Mauro K. ; Goncales, Icaro ; Ribeiro, Rodrigo N. ; Machado, Cezar O. ; Polkorny, Matheus ; Otero, Malena D'Elia ; Abreu, Ana Elisa S. ; Azevedo, Caio ; Spinola, Mauro ; IEEE
Total Authors: 13
Document type: Journal article
Source: 2021 IEEE INTERNATIONAL SMART CITIES CONFERENCE (ISC2); v. N/A, p. 6-pg., 2021-01-01.
Abstract

Inertial sensors are considered a new strategy to assess the slope movement prior to landslides in risk areas. It is a challenge to understand limitations, advantages, and disadvantages of the signals analysis from inertial sensors embedded in IoT devices for monitoring this phenomenon. Landslides can take a long time to collapse completely, and collecting data in real situations can imply a long-term collection, with no guarantees of recording the phenomenon. Promoting accelerated experiments can be an alternative for evaluating algorithms to detect soil movement. Therefore, this paper presents the results of two experiments performed for data collection by inertial sensors deployed in sandy soil in a dump truck. The signals were collected during sand unloading to evaluate the performance of the IoT devices in events similar to a landslide phenomenon. (AU)

FAPESP's process: 17/50343-2 - Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp)
Grantee:Zehbour Panossian
Support Opportunities: Research Grants - State Research Institutes Modernization Program