Application of an ultra-wide band sensor-free wireless network for ground monitoring

Intrieri, Emanuele; Gigli, Giovanni; Gracchi, Teresa; Nocentini, Massimiliano; Lombardi, Luca; Mugnai, Francesco; Frodella, William; Bertolini, Giovanni; Carnevale, Ennio Antonio; Favalli, Massimiliano; Alavedra, Jordi Marturiá; Mucchi, Lorenzo; Nannipieri, Luca; Rodríguez-Lloveras, Xavier; Pizziolo, Marco; Schina, Rosa; Trippi, Federico; Casagli, Nicola

doi:10.1016/j.enggeo.2018.02.017

Cited by 33 publications

(26 citation statements)

References 19 publications

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“…The method was applied in the field for the installation of the Wi-GIM system, a Wireless Sensor Network measuring node inter-distance by means of ultrawide-band technology. For more details about the system, please refer to Mucchi et al [18] and Intrieri et al [28]. The devices worked properly in LOS conditions; thus, aimed deployment of the sensors could widely improve their efficiency.…”

Section: Field Applicationmentioning

confidence: 99%

“…The devices worked properly in LOS conditions; thus, aimed deployment of the sensors could widely improve their efficiency. For better evaluation of the improvement, Wi-GIM was installed in the Roncovetro landslide, as previously done by Intrieri et al [28]. During this first monitoring period, system accuracy and precision were analyzed.…”

Section: Field Applicationmentioning

confidence: 99%

“…During this first monitoring period, system accuracy and precision were analyzed. While precision ranged from 2 to 5 cm, the medium recorded error of the distance was about 75 cm, and it was strictly connected to both the presence of obstacles and the low-cost nature of the system [28]. However, this large error did not compromise the effectiveness of the system since it focused on relative distances and not absolute ones.…”

Section: Field Applicationmentioning

confidence: 99%

“…As in 2016, sensors were installed on 1.5 m high iron poles, as consequently considered in the parameter settings. The ROI was fixed at 100 m, i.e., the maximum distance at which Wi-GIM sensors properly communicate [28].…”

Section: Field Applicationmentioning

confidence: 99%

“…These are defined as networks of usually low-size and low-cost devices denoted as nodes that are Romagna Region, Central Italy. At the same site, a first monitoring campaign with the system was carried out in 2016 by Intrieri et al [28]. It was then possible to compare the data acquired in the two campaigns and evaluate the performance of the proposed method in a real serviceable case.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Wireless Sensor Network Installations by Visibility Analysis on 3D Point Clouds

Gracchi

Gigli

Noël

et al. 2019

IJGI

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In this paper, a MATLAB tool for the automatic detection of the best locations to install a wireless sensor network (WSN) is presented. The implemented code works directly on high-resolution 3D point clouds and aims to help in positioning sensors that are part of a network requiring inter-visibility, namely, a clear line of sight (LOS). Indeed, with the development of LiDAR and Structure from Motion technologies, there is an opportunity to directly use 3D point cloud data to perform visibility analyses. By doing so, many disadvantages of traditional modelling and analysis methods can be bypassed. The algorithm points out the optimal deployment of devices following mainly two criteria: inter-visibility (using a modified version of the Hidden Point Removal operator) and inter-distance. Furthermore, an option to prioritize significant areas is provided. The proposed method was first validated on an artificial 3D model, and then on a landslide 3D point cloud acquired from terrestrial laser scanning for the real positioning of an ultrawide-band WSN already installed in 2016. The comparison between collected data and data acquired by the WSN installed following traditional patterns has demonstrated its ability for the optimal deployment of a WSN requiring inter-visibility.integrated with sensors that can gather information through wireless links [7]. Their use presents several advantages over traditional monitoring techniques, such as the capability to work in rough and hardly accessible terrain, thanks to the absence of wired structures [8]; the possibility to analyze data from a multipoint perspective [9]; the ease and speed of installation [10]; and the adaptability of sensors to be integrated with existing monitoring techniques [11,12]. To make the most out of a WSN, optimal sensor deployment (i.e., equal and thoughtful distribution) is essential, and, to this aim, sensor-deployment problems were studied in several contexts [13]. For instance, Wang et al. [14] geometrically analyzed the relationship between coverage and connectivity in a WSN considering an obstacle-free environment, and Zou and Chakrabarty [15] proposed a virtual force algorithm as a sensor-deployment strategy after an initial random placement of sensors. For some types of sensors, line of sight (LOS) cannot be neglected. Information is in fact properly transmitted if the transmitter and receiver stations are in view of each other without any obstacle. The LOS of each emitting sensor is therefore an important issue to consider when positioning two or more receivers.Researchers are increasingly focusing on LOS-based WSNs that use the same signal both for communication and ranging purposes, allowing the relative distance between nodes to be detected and landslide deformation to be assessed [16][17][18][19]. Depending mainly on their wavelength and the characteristics of the material to cross, waves can follow several types of behavior, and problems connected to unfavorable LOS may lead to the absence of data or inaccurate measurements due to a delay ...

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Section: Field Applicationmentioning

confidence: 99%

Section: Field Applicationmentioning

confidence: 99%

Section: Field Applicationmentioning

confidence: 99%

Section: Field Applicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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