Wireless Technology for Monitoring Site-specific Landslide in Vietnam

Quoc-Anh, G; Nguyen, Dinh-Chinh; Tran, Duc-Nghia; Tran, Duc–Tan; Nguyen, Kim Thuy; Sandrasegaran, Kumbesan

doi:10.11591/ijece.v8i6.pp4448-4455

Cited by 6 publications

(11 citation statements)

References 20 publications

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“…The moving element deforms up to the point of instability. This point can be expressed by a certain distance which is calculated: Under static equilibrium, 𝐹 𝑚 has equal magnitude but opposite direction as the 3) in the previous equation, we will have (7).…”

Section: Research Methods 21 Principe Working Of Cantilever Mems Switchmentioning

confidence: 99%

Features measurement analysis of pull-in voltage for embedded MEMS

Baghdadi

Lamhamdi

Rhofir

2022

IJRES

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<p>The embedded micro electro mechanical systems (MEMS) is a technology that is creating a new era in all fields and especially in the internet of things (IoT) field. MEMS are necessary components for the realization of tiny micro/nano circuits. For this reason, designers are facing many challenges in designing embedded MEMS for achieving efficient products. The pull-in voltage is one of the most important parameters of MEMS design. In this work, we are interested in the analysis of some geometrical and mechanical parameters for the pull-in. The objective is to study of the concept of pull-in voltage in order to reduce it. First, we made a simulation to choose the appropriate material achieving a lower pull-in voltage. Then, we analysed the impact of geometrical parameters on the pull-in voltage. In this work, Finite element method using COMSOL Multiphysics® software is employed to compute the Pull-in voltage and study the behaviour of the MEMS Switch in order to optimize it. Pull-in voltage can be reduced by careful selection of the cantilever material and it can be further reduced by changing the beam parameters.</p>

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Section: Research Methods 21 Principe Working Of Cantilever Mems Switchmentioning

confidence: 99%

Features measurement analysis of pull-in voltage for embedded MEMS

Baghdadi

Lamhamdi

Rhofir

2022

IJRES

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“…Tilt measurements can indirectly detect two-dimensional shear deformation and determine the rotational direction in terms of tilt angle and sign convention [95]. When combined with MEMS and WSNS techniques, tilt sensors can provide the following benefits: (1) minimal cost, (2) simple installation (no deep boreholes required), and (3) real-time data [96]. Gian et al [96] used a tiltmeter combined with other sensors to provide real-time data through WSNs.…”

Section: Electromechanical Tilt Sensorsmentioning

confidence: 99%

Recent Phenomenal and Investigational Subsurface Landslide Monitoring Techniques: A Mixed Review

Ebrahim,

Gomaa,

Zayed

et al. 2024

Remote Sensing

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Landslides are a common and challenging geohazard that may be caused by earthquakes, rainfall, or manmade activity. Various monitoring strategies are used in order to safeguard populations at risk from landslides. This task frequently depends on the utilization of remote sensing methods, which include the observation of Earth from space, laser scanning, and ground-based interferometry. In recent years, there have been notable advancements in technologies utilized for monitoring landslides. The literature lacks a comprehensive study of subsurface monitoring systems using a mixed review approach that combines systematic and scientometric methods. In this study, scientometric and systematic analysis was used to perform a mixed review. An in-depth analysis of existing research on landslide-monitoring techniques was conducted. Surface-monitoring methods for large-scale landslides are given first. Next, local-scale landslide subsurface monitoring methods (movement, forces and stresses, water, temperature, and warning signs) were examined. Next, data-gathering techniques are shown. Finally, the physical modeling and prototype field systems are highlighted. Consequently, key findings about landslide monitoring are reviewed. While the monitoring technique selection is mainly controlled by the initial conditions of the case study, the superior monitoring technique is determined by the measurement accuracy, spatiotemporal resolution, measuring range, cost, durability, and applicability for field deployment. Finally, research suggestions are proposed, where developing a superior distributed subsurface monitoring system for wide-area monitoring is still challenging. Interpolating the complex nonlinear relationship between subsurface monitoring readings is a clear gap to overcome. Warning sign systems are still under development.

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“…Recent years have witnessed an increased interest in the use of wireless sensor networks (WSNs) in numerous applications such as forest monitoring, disaster management, space exploration, factory automation, secure installation, border protection, and battlefield surveillance [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Solving wireless sensor network coverage problem using LAEDA

Khezri

2020

IJEECS

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<p>Coverage improvement is one of the main problems in wireless sensor networks. Given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. For achieving good coverage, the sensors should be placed in adequate places. In this article, estimation of distribution algorithm based on learning automata is presented for solving the sensor placement (LAEDA-SP) in distributed sensor networks by considering two factors: 1) the complete coverage and 2) the minimum costs. The proposed algorithm is a model based on search optimization method that uses a set of learning automata as a probabilistic model of high-quality solutions seen in the search process. It is applied in a various area with different size. The results not only confirmed the successes of using the new method in sensor replacement but also they showed that the proposed method performs more efficiently compared to the state-of-the-art methods such as simulated annealing (SA) and population-based incremental learning algorithms (PBIL).</p>

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Wireless Technology for Monitoring Site-specific Landslide in Vietnam

Cited by 6 publications

References 20 publications

Features measurement analysis of pull-in voltage for embedded MEMS

Features measurement analysis of pull-in voltage for embedded MEMS

Recent Phenomenal and Investigational Subsurface Landslide Monitoring Techniques: A Mixed Review

Solving wireless sensor network coverage problem using LAEDA

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