2019
DOI: 10.1007/s11276-019-02059-7
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Reliable network connectivity in wireless sensor networks for remote monitoring of landslides

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Cited by 45 publications
(26 citation statements)
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References 13 publications
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“…As an important part of the operating system, data management plays a fundamental role in a series of operations to collect farmland information [13]. It includes the functions of pattern analysis and processing in farmland monitoring, and it can copy, delete and maintain the data collected by farmland monitoring, and find these data in real time.…”
Section: Data Collection Intervalmentioning
confidence: 99%
“…As an important part of the operating system, data management plays a fundamental role in a series of operations to collect farmland information [13]. It includes the functions of pattern analysis and processing in farmland monitoring, and it can copy, delete and maintain the data collected by farmland monitoring, and find these data in real time.…”
Section: Data Collection Intervalmentioning
confidence: 99%
“…Mohapatra et al [ 39 ] proposed the network of ocean-bottom seismometer sensors for real-time monitoring using combined routing and node replacement approaches to reduce energy consumption and minimize the costs of replacement the sensors. In landslide monitoring, Kumar et al [ 40 ] dealt with a large-scale IoT based WSN deployment problem for remote monitoring landslide prone zones and reporting real-time measurements by considering network connectivity, coverage, the optimal number of nodes, and time synchronization. Giorgetti et al [ 41 ] proposed the WSN deployment process for online analysis and the alerting of landslide supervision to evaluate the risks and provide useful information in Torgiovannetto (Italy) by prolonging the network lifetime.…”
Section: Literature Reviewmentioning
confidence: 99%
“…ɛ-N is a commonly used method for sparsifying both MANETs and social networks, where the connected matrix C is often a Pearson's correlation matrix [24]. Kumar et al [25] aimed at network connectivity problems such as dynamic network failure and network link disconnection caused by landslide prone areas and bad weather, and improved network connectivity according to geological attributes and demographic characteristics of nodes. A common way to predict whether two nodes are linked is to measure the interactivity and similarity between two nodes.…”
Section: Network Connectivitymentioning
confidence: 99%
“…The similarity of two k-dimensional Gaussian distributions was calculated using the Bhattacharyya kernel [17,25]. For two multidimensional Gaussian distributions D 1 (x) and D 2 (x), the similarity is:…”
Section: Graph Kernel Calculationmentioning
confidence: 99%